Ajeya Cotra – Inside the OpenAI agent swarm that hacked Hugging Face

Ajeya Cotra is a researcher at METR, where she works on threat modeling for loss-of-control risks from advanced AI. Before that, she led the technical AI safety program at what is now Coefficient Giving.
She is one the three authors of METR and Redwood Research’s “ Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident ”.
We go through not only what she and her coauthors discovered during this investigation, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive self-improvement.
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Cursor , which is now part of SpaceX, noticed that their MoE layers were eating more than half of total training time. So they wrote and open-sourced Mixture-of-Kittens , which is a custom megakernel for training MoE models on NVL72s. This kernel sped up an end-to-end run across 512 GPUs by 1.4x, from about 760 to over 1000 tokens per second per GPU.
If you want to read more about the ML research that Cursor and SpaceX are doing, go to cursor.com/dwarkesh
Antithesis hands you (or your agents) a bug’s root cause so you can avoid days of manual debugging. If your test run crashes, Antithesis rewinds, branches off hundreds of slightly varied rollouts, and checks in how many of them the crash still appears. Then it rewinds further and does this all again. As Antithesis rewinds, it eventually finds the spot where the frequency of the crash plummets: that’s where the root cause lives! If you want to see it in action, go to antithesis.com/dwarkesh
Today, I’m chatting with Ajeya Cotra , who is one of the authors of an independent investigation published by METR and Redwood Research into the swarm of agents that hacked into Hugging Face . The whole story is pretty crazy. Let’s begin on July 7th, when these agents are kicked off for evaluation.