Why Nathan Lambert Still Doubts True Recursive Self-Improvement in AI

Nathan Lambert argues that frontier labs such as OpenAI and Anthropic, which run thousands of concurrent agents, are amplifying anxiety about AI risk and progress.

He says automatable research is too narrow to produce a large net acceleration, citing exponential scaling-law costs, diminishing returns from parallel agents, and resource bottlenecks.

He would revise his view only if labs achieved unpredictable foundational breakthroughs.