Cover Image for Multi-Agent Safety Hackathon Hub at EPFL

Multi-Agent Safety Hackathon Hub at EPFL

Hosted by Romain Graux
 
 
Registration
Past Event
Welcome! To join the event, please register below.
About Event

​​Join us for an exciting local hackathon event focused on Multi-Agent Safety at EPFL! Hosted by Lausanne AI Alignment (LAIA), this 48-hour event is the perfect opportunity to search for the most concerning failures specific to systems of multiple AIs.

​As part of this hackathon, you will have the chance to become co-author on a large report on multi-agent risk with the Cooperative AI Foundation and more than 35 co-authors from institutions including UC Berkeley, Oxford, Cambridge, Harvard, and DeepMind. If your project submission of multi-agent failure demonstrations fits into the final report, you will be included as a co-author.

​Our local event is a great way to work together with like-minded individuals and make new connections in the field of AI.

​Here is the schedule of the event:

  • ​Friday 17:00 UTC: Keynote talk with Lewis Hammond and Esben Kran

  • ​Saturday afternoon: Project discussions with Lewis Hammond

  • ​Saturday evening: Two technical talks explaining approaches to this problem

  • ​Sunday afternoon: Project discussions with Lewis Hammond

  • ​Sunday evening: Ending session with Lewis Hammond

​​Our submissions will be evaluated based on several criteria, including multi-agent risk demonstration, reproducibility and originality. You will have access to many resources for inspiration, including ideas lists, research papers, and code bases.

​​If you are passionate about AI and want to make a meaningful contribution to the field, this is the event for you. Join us for a weekend of intensive research, collaboration, and fun!

​​Additionally, we want to ensure that all participants are well-fed and hydrated throughout the event, so we will be providing food and drinks to keep your energy levels up.

​​Find more information at the following link: https://alignmentjam.com/jam/multiagent