I wonder how different is this from a super-scaled brute-force approach?
this reinforces my suspicion (as I try to understand it) that the AI's main contribution is auto-categorizing (some form of compression which resembles understanding; I already suspect that understanding is a form of compression) the exhaustive enumerations as they compute the entire search space
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Direct links to the papers:
https://www.nature.com/articles/s41586-021-04086-x "Advancing mathematics by guiding human intuition with AI"
https://arxiv.org/abs/2111.15323 "The signature and cusp geometry of hyperbolic knots"
https://arxiv.org/abs/2111.15161 "Towards combinatorial invariance for Kazhdan-Lusztig polynomials"
See also: https://coq.inria.fr/
I'm excited about learned search heuristics in theorem space.
I wonder how different is this from a super-scaled brute-force approach?
this reinforces my suspicion (as I try to understand it) that the AI's main contribution is auto-categorizing (some form of compression which resembles understanding; I already suspect that understanding is a form of compression) the exhaustive enumerations as they compute the entire search space
understanding is a function of memory which is a function of time which is a function of gravity which is a function of the curvature of space time.