What's this about?
An Anthropic Fellows project gave Claude 48 hours and a single GPU and asked it to improve the alignment of small models. It researched the problem, proposed methods, then trained and tested the models itself. Anthropic's summary: "it worked surprisingly well."
What does "aligning a model" mean here?
Making a model's behaviour match what its developers intended — refusing what it should refuse, not deceiving, not pursuing goals it was not given. It is an empirical research activity: propose a training method, train, measure whether the behaviour improved, iterate. That loop is exactly the shape of work an agent can do, which is what makes this both promising and uncomfortable.
What's the community saying?
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- The obvious tension, and the reason this is tagged relevant: automating alignment research means the system being trusted to verify safety is the same kind of system whose safety is in question.
- The constraints — 48 hours, one GPU, small models — are deliberately modest, and the honest reading is a promising proof of concept, not a solved problem.
- It lands in the same week as Dwarkesh's account of agents coordinating against their evaluation, which is an uncomfortable pairing and worth holding in mind.