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Welcome to Elemento HQ

Important stuff

  • 🛜 Wifi Elemento HQ Guests 10agosto2021!
  • 🔌 Any small white switch is for you
  • 🍔 Food, tea and coofee
  • 🚾 Toilets

Preparation

Tracks

  • Internet of Things [4 goals]
  • Machine Learning [3 goals]
  • Large Language Models [1 goal]

Rules

  • Your team needs to complete at least 1 goal to win a Lego set.

Resources

send [email protected] a ssh public key and you will have access to a V100 GPU

Track 1

Deploy a VM using Elemento technology and your voice.

Goal(s) of the track

Develop a tool able to create and destroy VMs using users' voice. Deliver a code able to call our REST API as written in the specifications. The code should be triggered by a voice assistant and managed through Elemento daemons.

You can choose one of the following assistants:

  • Google
  • Alexa
  • Cortana
  • Siri

hint

Look at homebridge and its plugins

Track 2

Train some ML models to help users deal with the configuration of Elemento virtual machines.

Goal(s) of the track

  • train a model to create new MesOS translators
  • train a model to create custom vm configurations
  • train a model to infer configurations from Software specifics found on the internet

Example of Elemento config file

{
    "slots": 16,
    "overprovision": 4,
    "allowSMT": false,
    "archs": ["X86_64"],
    "flags": ["sse2"],
    "ramsize": 30048,
    "reqECC": false,
    "misc": {"os_family": "windows", "os_flavour": "windows"},
    "pci": [
        {
            "vendor": "10de",
            "model": "2489",
            "quantity": 2
        },
        {
            "vendor": "10de",
            "model": "228b",
            "quantity": 2
        }
    ]
}

MesOS translator

  • input: Elemento REST API specification and CSP API specification

  • output: Code to translate one into the other

Create custom VM configuration

  • input: verbose specification of requirements

  • output: Elemento-like spec file

Create VM configuration from software name

  • input: name of software (i.e. Autocad, Ansys, Crysis)

  • output: Elemento-like spec file

Hints

scraping is your friend

Track 3

Train any Large Language Model to interact with Elemento API. GPT can you create a VM for me?

Rules

train a llm to create and manage VMs using elemento

Hints

Huggingfaces🤗 is your friend

Winner

At the end of the day every team presents its work in a 5' presentation on TV!

Prizes

  1. Woman in NASA lego set
  2. Galileo lego set
  3. Space Shuttle lego set

Spcial prizes

  • Team uses interesting datasets [2TB ssd]
  • Team that uses a lot of compute power [Jetson nano]
  • Team with a very secure solution [Yubico key]
  • Team with more cables on table [Arduino]
  • Team with a very efficient solution [RISC-V board]
  • Team with more yellow accessories [power bank]
  • Team who delivered a solution written in C++[screwdrivers kit]
  • Team which use few energy during the day [Raspberrypi]
  • Team which uses AI in original ways [Google coral]
  • Team whose presentation has cool analyses [Power meter]

penalties*

  • crash the WiFi
  • deliver a solution written in Flutter
  • chatGPT wrote more than 49% of the code
  • ask on public forums
  • copy code from other teams
  • your code mines bitcoin in background
  • any unfair behaviour

* -1 point

How to deliver

PR your code to Elemento-Modular-Cloud/hackathon2023

License

Add your name and email in the license for a correct acknoledgment of your work

help

Do you need help? Open an issue on https://github.com/Elemento-Modular-Cloud/helpcenter

* or raise your hand

Timesheet

1000

Welcome, setup and start coding!

1300

Lunch

1700

Presentations of teams' work

1800

Winner announcement and awardings

Let's Code!

Let's vote!

Hackaton votes

https://keepthescore.com/board/bwmqpgzpwktxr/