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Rich Sutton on AI creativity and discovery

twitter.com

June 10, 2026

1 min read

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58/100

Summary

A new and possibly controversial perspective: In this video, I explain the sense in which generative AI trained by supervised learning is incapable of making novel discoveries. https://t.co/LhAU6AyDkh The text of the speech: AI Creativity and Discovery Good day ladies and

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Community Sentiment

Mixed

Positives

Rich Sutton emphasizes the importance of evaluation in AI creativity, suggesting that generative AI needs a structured approach to retain valuable outputs, which could enhance its utility in science and engineering.
The discussion around AlphaGo and Claude Code illustrates the potential of AI systems to autonomously evaluate and iterate, highlighting their capabilities in discovery and problem-solving.
The idea that AI can generate novel outputs while being grounded in training data opens avenues for innovative applications, merging randomness with learned knowledge.

Concerns

There is skepticism regarding the claim that AI can only produce either random or good outputs, as many believe that AI can achieve both through advanced training techniques.
Concerns are raised about the limitations of current AI models in discerning valuable outputs, suggesting that without proper evaluation mechanisms, creative potential may be wasted.