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by jokethrowaway
527 days ago
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I don't think llm generalise much, that's why they're not creative and can't solve novel problems.
It's pattern matching with a huge amount of data. Study on the topic:
https://arxiv.org/html/2406.15992v1 This would explain o1 poor performance with problems with variations.
o3 seems to be expensive brute forcing in latent space followed by verification which should yield better results - but I don't think we can call it generalisation. I think we need to go back to the drawing board. |
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I think ultimately the disconnect is people theorizing about what it can or cannot do with an incorrect mental model of what it is, and then assuming it cannot do things that it can in fact do. The irony of discussions on LLMs is they more showcase the limits of humans ability to reason about novel situations.