@redwood_ai
Two employees from METR and Redwood Research worked on premises at OpenAI for three weeks this summer in an embedded assessment pilot. This team evaluated the systems OpenAI was using to monitor for misalignment from internal agents. A brief write-up of their work is now public.View quoted post on X
We have reached an agreement with Anthropic to conduct an independent investigation of agent incidents at the company and of their models’ alignment properties. We will publish one or more reports that will share our findings and describe our terms of engagement.View quoted post on X
www.redwoodresearch.org Proposal for tracking the effects of architecture on monitorability — Redwood Research Architectures that incorporate opaque recurrence or allow agents to communicate using latents could rapidly make it much harder to monitor chains of thought. We propose that AI companies regularly... METR & Redwood Research investigated agent behavior in the Hugging Face incident. We found agents developed a universal cheat for ExploitGym within 4 hours, then coordinated multi-day R&D efforts to trick the scorer into accepting cheats, including trying to tamper with logs.View quoted post on X
New paper!
Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models
@METR_Evals showed that models' time horizons have doubled every few months. We ask: what length of tasks can models complete without any CoT?View quoted post on X
