Podcast: Epoch AI's JS Denain debates RSI, US-China gap, distillation, open vs closed safety
An Interconnects podcast episode features a debate with Jean-Stanislas 'JS' Denain of Epoch AI, covering predictions for recursive self-improvement (RSI), the role of robotics in AI acceleration, the US-China AI gap, whether distillation explains the gap, insights from Chinese job postings, and whether open or closed models are safer. Both participants express significant uncertainty about the trajectory of AI.
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InterconnectsNathan Lambert
This episode is with Jean-Stanislas “JS” Denain of Epoch AI, who leads their Insights Team and is one of the people I find myself debating the state and trajectory of AI with more and more. We’ve had follow-on discussions of many of my favorite recent posts online and/or in private, so I wanted to dig into the nuance in a public episode. A big takeaway of this podcast is how JS and I both have so much uncertainty with exactly where we are heading, and this was our best effort at stating our observations today. Chapters / topics include: 00:00 Predictions for RSI 18:15 The role of robotics in an AI acceleration 24:20 How far behind are Chinese models? 27:39 Does distillation explain the gap? 40:58 What Chinese job postings reveal about their labs 48:13 Are open or closed models safer? 58:10 How Epoch AI ticks 1:00:55 What a frontier post-training recipe looks like Enjoy! More from JS: Epoch AI profile and writing , X , LinkedIn Share Listen on Apple Podcasts , Spotify , and where ever y
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