METR proposes framework for assessing AI loss-of-control risk

METR outlines how an assessor would measure whether AI automation is speeding up AI R&D, using benchmarks, intermediate measures like pretraining loss, and researcher surveys. It also covers separating AI-driven acceleration from other factors and identifying near-term bottlenecks.

Databricks reports a 6x reduction in Qwen training time on its AI Runtime, targeting the compute cost of training or finetuning multi-billion parameter foundation models.

A r/ClaudeAI thread asks how users comfortably grant agents access to machines, emails, and personal data, with the poster calling the level of access a massive privacy and security risk. The poster says that risk is the main reason they hesitate to connect Claude or similar tools.

Reddit users on r/SunoAI report a pop-up that hard-locks Android Chrome and that most browser features were removed in favor of the app. A workaround is enabling desktop mode; users say the app lacks features available to premium tiers.

Torvalds submitted a 10-patch series drafted with Anthropic's Claude Code that delivered a 23-fold throughput improvement on a read()-heavy benchmark. Reviewers have already flagged a race condition in the code, so further work is needed.

Kokon lets users brush an area of a photo and describe the edit, with changes confined to the brushed region. It is a free, open-source desktop app for Windows with a Mac beta, and auto-downloads the model matching the user's GPU.