Machine learning is abstracted as producing P/poly distributions with bounded entropy, and any such model that minimizes error on a pseudorandom generator's output distribution must itself be close to uniform.
Chain-of-thought prompting elicits reasoning in large language models
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How Does Machine Learning Manage Complexity?
Machine learning is abstracted as producing P/poly distributions with bounded entropy, and any such model that minimizes error on a pseudorandom generator's output distribution must itself be close to uniform.