NOAM BROWN – AGENT SWARMS, ALIGNMENT, & RECURSIVE SELF-IMPROVEMENT

Summary from the TLDR AI newsletter

This post features a transcript of an interview with Noam Brown, a research scientist at OpenAI who works on reasoning, reinforcement learning, self-play, and multi-agent AI. Brown was a foundational contributor to the development of reasoning models. In this interview, Brown talks about multi-agent, Navier-Stokes, the current explosion of maths progress, automating AI research, and how we will know whether models are actually aligned before recursive self-improvement kicks off. A video of the interview is available.