DeepMind updated its Frontier Safety Framework (blogpost, framework, original framework). It associates "recommended security levels" to capability levels, but the security levels are low. It mentions deceptive alignment and control (both control evals as a safety case and monitoring as a mitigation); that's nice. The overall structure is like we'll do evals and make a safety case, with some capabilities mapped to recommended security levels in advance. It's not very commitment-y:

We intend to evaluate our most powerful frontier models regularly 

When a model reaches an alert threshold for a CCL, we will assess the proximity of the model to the CCL and analyze the risk posed, involving internal and external experts as needed. This will inform the formulation and application of a response plan.

These recommended security levels reflect our current thinking and may be adjusted if our empirical understanding of the risks changes.

If we assess that a model has reached a CCL that poses an unmitigated and material risk to overall public safety, we aim to share information with appropriate government authorities where it will facilitate the development of safe AI.

Possibly the "Deployment Mitigations" section is more commitment-y.

I expect many more such policies will come out in the next week; I'll probably write a post about them all at the end rather than writing about them one by one, unless xAI or OpenAI says something particularly notable.