← Y Combinator Startup Podcast
Listen to this episodeAll Y Combinator Startup Podcast episodes →
Beyond Bigger Models: Recursion As The Next Scaling Law In AI
Y Combinator Startup Podcast · 2026-05-01 · 38 min
Episode notes
A 7-million parameter model outperforming models a thousand times its size on tasks like ARC Prize. That's what recursive reasoning unlocks.In this episode of Decoded, YC's Ankit Gupta and Francois Chaubard break down two recent papers on recursive AI models, HRMs and TRMs, that are achieving state-of-the-art results with a fraction of the parameters of today's largest models.They explain why standard LLMs hit a fundamental ceiling on certain reasoning tasks, how recursion at inference time gives small models the compute depth to break through it, and what happens when you combine these ideas with the power of large-scale foundation models.
More from Y Combinator Startup Podcast
All episodes →- Why Domain Experts Are Winning In The Age Of AI43 / 100
- How To Pick A Startup Idea41 / 100
- "The CEO Must Be the Chief AI Officer"65 / 100
- How to Build an AI-Native Services Company
- How To Build Superintelligence Inside Your Company