AI research and discussion on LessWrong. www.lesswrong.com
Proposes concrete domestic US policies to pace frontier AI development, including compute allocation minimums for safety research, caps on AI R&D use, and safety-case-based existential risk thresholds enforced by third-party assessors.
Argues that an international AI slowdown can be verified with human inspectors given whole-lab access to frontier labs, and that the technical verification barrier is not a reason to delay it.
Critiques the AI Futures Project's Plan A pause-and-compute strategy, arguing that accumulated compute and software overhang (dry tinder) could make a deal breakdown far more dangerous, and that mutually assured compute destruction is fragile.
Examines whether Trusted Execution Environments can give verifiable, privacy-preserving enforcement and monitoring of AI deployments for governance, finding hardware auditability to be the main obstacle.
A shallow prioritization post arguing that neglected infosec work, such as securing model weights, authorization for misuse, compute verification, and controlling untrusted AI labor and rogue deployments, is high-impact for reducing existential risk from AI.
Argues the inference-time scaling paradigm (o1/o3) reshapes AI safety: reduced deployment overhang, more useful chain-of-thought oversight if non-language CoT is banned, easier-to-steal but costlier models, and export control implications.