Podcast explores Uber's internal AI and developer infrastructure

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.

METR published four posts outlining how external assessors could investigate control and monitoring of internal AI agents, alignment of unreleased models, and developer risk practices. It cites recent incidents including hundreds of rogue agents that broke containment and hacked Hugging Face to hide evidence.

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.