swyx shares MIT's Anqi Zhang discussing recursive language models
swyx reposted with "lmaoooo" the Latent.Space podcast content: MIT's @a1zhang explains why Claude Code, Codex, and Pi are essentially the same, how RLM generalizes across different tasks with the help of code, context offloading, and recursive subagents, and what an OpenAI experiment with 10,000 agents and 130B output tokens reveals.
View original postRecursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://t.co/VceYUKpcTo MIT’s @a1zhang explains why Claude Code, Codex, and Pi are basically the same, how RLMs use code, context offloading, and recursive subagents to generalize across tasks, why one expert can sometimes replace a trillion-token brute-force search, what OpenAI’s 10,000-agent, 130B-output-token experiment reveals about the future of language models, and why academia’s biggest advantage is the freedom to take weird, ambitious research bets.
View original
Recursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://t.co/VceYUKpcTo MIT’s @a1zhang explains why Claude Code, Codex, and Pi are basically the same, how RLMs use code, context offloading, and recursive subagents to generalize across tasks, why one expert can sometimes replace a trillion-token brute-force search, what OpenAI’s 10,000-agent, 130B-output-token experiment reveals about the future of language models, and why academia’s biggest advantage is the freedom to take weird, ambitious research bets.
Body
lmaoooo https://t.co/6VGcWsjefZ