HackOS 1 - A Research-Themed Hackathon @ McGill x Waterloo
HackOS 1 is sponsored by Rootly (YC S24)! Learn more about Rootly in the sponsor section below.
Update: we have reached event capacity at our in-person venue at McGill, though we'll host a virtual option - feel free to join the waitlist, we'll send the virtual option shortly afterward.
Welcome! What is HackOS!?
A student-run hackathon to collectively create models to beat benchmarks for open access research topics, hosted at Building 21 at McGill University.
Who can join?
This hackathon is geared towards students, researchers, and recent grads. We welcome participants of all skill levels, whether you're writing code for the first time or a seasoned developer. If you are a public member, please send us a message, we'll do our best to accommodate!
What is happening?
We'll be hacking together models to beat benchmarks for 3 different streams:
Natural language understanding for LLMs: tinyMMLU (or time permitting, all of tinyBenchmarks!)
Bioinformatics: running predictions on genomic data with Genomic Benchmarks
Vision in compute-limited settings: a subsample of COCO minitrain
WFB: Whatever floats your boat! Choose your own goal/benchmark and hack away! Show us at the end of the hackathon pls <3
How will we evaluate models?
We're planning to create a Python library that you can clone from GitHub to easily run the above benchmarks - still a work in progress, we'll keep you posted!
Tentative Schedule:
Friday, October 25: (6PM to 9PM)
6:00 PM: Doors open
6:30 PM: Openincg ceremony featuring Rootly
7:00 PM: Hacking starts
9:00 PM: Hacking off-site
Saturday, October 26: (10AM to 3PM)
10:00 AM: Start of in-person hacking
12:00 PM: Lunch
2:00 PM: Demos
3:00 PM: Wrap up!
Our friends at Waterloo will be hacking at the same time! We'll chat with them virtually throughout the hackathon.
About Rootly, our sponsor
Rootly (YC S24) is a fast-growing Canadian startup trusted by industry leaders like NVIDIA, LinkedIn, and Wealthsimple to supercharge their on-call and incident response. Our platform seamlessly integrates with your entire tech stack and leverages AI to help SREs and DevOps teams resolve issues faster, reduce downtime, and prevent repeat incidents. Our goal with AI is to fundamentally help companies tackle incidents more efficiently and ensure they don’t happen again.
Questions?
Feel free to reach out to Laurence! (email: laurence.liang [at] mail.mcgill.ca)