# Q&A with AI researchers John Schulman, Beren Millidge, and Charlie O'Neill on steelmanning the case against RSI, Chinese labs' progress, long-horizon RL, more (Dwarkesh Patel/Dwarkesh Podcast)

> Dwarkesh Patel sat down with researchers John Schulman, Beren Millidge, and Charlie O'Neill for a technical conversation that, unusually, tries to argue against the hype rather than for it. The through line is a careful steelman of the case against recursive self-improvement, the idea that an AI could rapidly bootstrap itself to vastly greater intelligence, which sits at the heart of the field's most dramatic forecasts. Schulman, a central figure in the reinforcement learning work behind modern chatbots, is well placed to poke at where that story might break down in practice. The discussion also weighs how quickly Chinese labs are closing the gap and the move toward long-horizon reinforcement learning, where models are trained to pursue goals over many steps rather than single answers. For readers tired of both doom and boosterism, the value here is the texture: practitioners disagreeing in detail about which capabilities are actually near and which remain stubbornly hard, which is where the real trajectory of AI is being decided.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Dwarkesh Podcast · Published Saturday, September 12, 2026_

## Wortins' read

Dwarkesh Patel sat down with researchers John Schulman, Beren Millidge, and Charlie O'Neill for a technical conversation that, unusually, tries to argue against the hype rather than for it. The through line is a careful steelman of the case against recursive self-improvement, the idea that an AI could rapidly bootstrap itself to vastly greater intelligence, which sits at the heart of the field's most dramatic forecasts. Schulman, a central figure in the reinforcement learning work behind modern chatbots, is well placed to poke at where that story might break down in practice. The discussion also weighs how quickly Chinese labs are closing the gap and the move toward long-horizon reinforcement learning, where models are trained to pursue goals over many steps rather than single answers. For readers tired of both doom and boosterism, the value here is the texture: practitioners disagreeing in detail about which capabilities are actually near and which remain stubbornly hard, which is where the real trajectory of AI is being decided.

## Source

[Read the full story at Dwarkesh Podcast](https://www.techmeme.com/260912/p3#a260912p3)

## Related coverage

- [The detrimental cost of scaling AI too fast](https://www.wortins.com/story/the-detrimental-cost-of-scaling-ai-too-fast-aeca9f03) — [The Next Web](https://thenextweb.com/news/detrimental-cost-scaling-too-fast-greg-keith)
- [Anthropic tells investors it will be profitable for a second straight quarter](https://www.wortins.com/story/anthropic-tells-investors-it-will-be-profitable-for-a-second-80048b84) — [Techmeme](https://www.techmeme.com/260913/p14#a260913p14)
- [AI bootcamps aim to tackle UK youth unemployment](https://www.wortins.com/story/ai-bootcamps-aim-to-tackle-uk-youth-unemployment-e9b48096) — [The Guardian](https://www.theguardian.com/technology/2026/sep/13/ai-bootcamps-uk-youth-unemployment-neets-preston)
- [AI Agents Are Thirsty for Power](https://www.wortins.com/story/ai-agents-are-thirsty-for-power-07e24890) — [Wired](https://www.wired.com/story/ai-agents-are-thirsty-for-power/)
- [Feeling sad about AI](https://www.wortins.com/story/feeling-sad-about-ai-61bc65ed) — [Simon Willison](https://simonwillison.net/2026/Sep/11/feeling-sad-about-ai/)
- [Y Combinator's Garry Tan wants US open-weight AI labs to 'distill' frontier models, too](https://www.wortins.com/story/y-combinator-s-garry-tan-wants-us-open-weight-ai-labs-to-dis-268f3036) — [TechCrunch](https://techcrunch.com/2026/09/11/y-combinators-garry-tan-wants-u-s-open-weight-ai-labs-to-distill-frontier-models-too/)

---

_Curated and written by [Wortins](https://www.wortins.com) — The daily AI briefing. Every story links to its original source; the "Wortins read" on each is our own original analysis. [About Wortins & our editorial approach](https://www.wortins.com/about)._