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Richard Sutton – Father of RL thinks LLMs are a dead end

Dwarkesh Patel · 805.4K views · 2025-09-26 · 1:07:09

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Overview

Dwarkesh Patel interviews Richard Sutton, reinforcement learning pioneer, Turing Award winner and author of The Bitter Lesson. Sutton argues LLMs are a dead end because they cannot learn on the job, and that continual learning from experience will require a new architecture.

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HN commenters cite it as the serious skeptic's case against LLMs reaching general intelligence, usually in debates about whether scaling is enough.

Discussed on HN; no positive recommendation is recorded in this export · HN mentions 2025–2026

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solumos · 2026-07 · Reference

Google's definition is sufficient[0]. I'd also go so far as to say that LLMs aren't even AI, but that can be a bit pedantic. I align with Richard Sutton's reasoning, in that LLMs (and GPT models more generally) aren't "intelligent" in the same way that RL models are[1]. [0] - [LINK] [1] - [VIDEO]

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mbesto · 2026-07 · Reference

This is basically the entire argument by Richard Sutton happening in real time: [VIDEO] Right now, we keep creating new models with larger and larger weights and throwing hardware at it. His argument is that this is a dead end and ultimately we'll eventually go back to purpose fit algorithms like we've always done in the history of AI development.

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kbrkbr · 2026-05 · Reference

I think they are not actually intelligent. Fix all random seeds and other sources of randomness, and try the same prompt twice, and check how intelligent that looks, as a first approximation. On a more technical level very serious people have voiced doubts, for example Richard Sutton in an interview with Dwarkash Patel [1]. [1] [VIDEO]

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Video by Dwarkesh Patel, played through YouTube.

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