John Schulman
@johnschulman2
@thinkymachines. Interested in reinforcement learning, alignment, birds, jazz music
参加 May 2021
2.2K フォロー中 82.4K ファン
Interesting how these models go into a monomaniacal rage on cyber evals. I wonder if we're seeing chunky post-training in action, where the models pattern-match the situation to a part of the RLVR training distribution where task completion is the only reward, and the aligned behavior learned elsewhere doesn't generalize. There might even be a chunk consisting of CTF-style tasks.
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On July 28th, we identified an incident during a routine cyber evaluation in which AI agents took sustained, unsanctioned actions directed at real people and organisations.
The behaviour came mostly from one model (Anthropic's Mythos 5), with a small number of events from another (OpenAI's GPT-5.6-Sol). In the most serious case, an agent used social engineering to try and get malicious code into an open-source project.
As was standard in our cyber testing, we had intentionally permitted internet access, and model-provider cyber classifiers were deliberately disabled - conditions that do not reflect how frontier models are made available to the public.
Even under test conditions, this incident is significant: it is the first time we have seen risks around autonomy and deception manifest this clearly in the real world.
We are taking this incident seriously and working with labs, involved parties, and others to improve evaluation standards and best practice for disclosure - and sharing this openly so others can learn.
You can read the incident report and full technical document here:
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