Skip to content
TrackPodcasts
technologyMay 1, 202637:52failed

Beyond Bigger Models: Recursion As The Next Scaling Law In AI

About this episode

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.

Get every episode summarized

Each time Y Combinator Startup Podcast publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.

Email me new episodes

Free for 3 shows. No card needed.

Hosts & guests

No transcript yet

This episode has not been transcribed. Request it and it moves to the front of the queue.

Beyond Bigger Models: Recursion As The Next Scaling Law In AI

Y Combinator Startup Podcast

0:00
37:52

More episodes

More from Y Combinator Startup Podcast

View all episodes →