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
Coverage & discussions
Hacker News · twitter.com
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Community Sentiment
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.
