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This tweet explores the relationship between statistical mechanics and artificial intelligence, citing a paper that proposes a thermodynamic theory for machine learning systems, introducing concepts like temperature, entropy, and energy, and treating the training process as a phase transition.
This article explores the four layers of physics' role in AI, from the bottom computational skeleton to the methodological layer, arguing that physics' methodology is migrating from the natural world to the AI domain.