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The article questions whether the simplified narrative of AI as just next-word prediction is intentionally promoted, and discusses the lack of public awareness about AI's complexity and unknown aspects like consciousness.
This paper reports that deep reinforcement learning agents using frozen, randomly initialized CNN feature extractors spontaneously develop extremely sparse fully-connected representations, compressing task-relevant information through very few neurons without any sparsity-inducing objective.