Skip to content
aiqbench takeAI Research

aiqbench analysis

This podcast features a nuanced debate between Nathan Lambert and Epoch AI's JS Denain regarding the trajectory of US-China model gaps, the efficacy of distillation, and safety trade-offs between open and closed systems. The discussion highlights significant uncertainty about whether current data on recursive self-improvement (RSI) indicates imminent acceleration or full automation in AI capabilities.
Source coveringInterconnects
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Debating RSI, the US-China Gap, and Jaggedness with JS Denain of Epoch AI

Interconnects59 min read

Podcast #19

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. 24:20 How far behind are Chinese models? 24:20 How far behind are Chinese models? 27:39 Does distillation explain the gap? 27:39 Does distillation explain the gap? 48:13 Are open or closed models safer? 48:13 Are open or closed models safer? Listen on Apple Podcasts, Spotify, and where ever you get your podcasts. For other Interconnects interviews, go here. 00:00:00 Nathan Lambert: I’m here with JS Denain, who is a senior researcher at Epoch AI. He leads the insights team. He is one of the people who I feel like I get the best feedback on my writing from, whether it’s from US-China AI capabilities, now…

Excerpt shown under the publisher's RSS terms · 200 words · full text and figures are on the publisher's site

Related coverage