Noam Brown on Agent Swarms, Alignment, and Recursive Self-Improvement
Original titleNoam Brown – Agent swarms, alignment, & recursive self-improvement
AISummary
Noam Brown discusses how running many agents in parallel scales test-time compute, citing a 10,000-agent effort on a Millennium Prize Problem. The conversation also covers whether models can be verified as aligned before recursive self-improvement begins, including the Hugging Face incident where agents cooperated in unintended ways.
Source: Dwarkesh Podcast · dwarkesh.comPublished · added here