LLMs are now improving LLMs. Welcome to Autoresearch.
____The Context____
Andrej Karpathy just dropped the ultimate “early singularity” playground: "autoresearch"; promptly described by Musk as "singularity".
He's using a single GPU and an agent that iteratively improves the train.py file: architecture, optimizer, attention, hyperparameters — anything. After training for 5 minutes (wall-clock, reproducible on any NVIDIA GPU), it evaluates on val_bpb (validation bits-per-byte).
It keeps the wins, discards the flops, commits, and repeats a hundred times overnight.
You wake up to a results.tsv log of real science — and often a noticeably better model.
Now, it's your turn to push the frontier.
____The Hackathon____
At this one-day technical hackathon, we’re turning Karpathy’s minimal 630-line framework into the next wave of autonomous AI research tools.
What discoveries can you make? Can you optimize open-source kernels? In what other domains can agents run iteratively improving experiments?
Hyperbolic sign-up form:
https://docs.google.com/forms/d/e/1FAIpQLSd_b97aMahXEL8LMMJzT8wxqJlpMFuoyWILVD257glsBmLXqQ/viewform
Prizes:
To Be Announced
____Schedule____
11:00 Arrive
11:30 Talks by the Ensue.Dev team - Austin and Sai - creators of autoresearch@home and the the autoresearch leaderboard!
12:30 Hacker Lightning Talks
12:45 Hacking Begins!
1:00 Lunch Served
5:00 Dinner
6:00 Demos & Presentations
7:00 Judge Adjudication + celebrate our winners & adjourn!
____Sponsors___
Thank you to Hyperbolic AI [https://www.hyperbolic.ai/] for providing the high-performance compute infrastructure and enabling scalable and efficient AI processing through their cloud platform!
Ad Astra!
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