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Andrej Karpathy argues that the way machines learn through reinforcement learning has almost nothing in common with how humans actually learn. In today’s RL systems, every tiny action in a successful sequence gets rewarded even the steps that were mistakes or irrelevant. He says this creates a noisy signal that forces models to “suck supervision through a straw,” struggling to isolate what truly mattered. His point is bigger than a critique of RL. It highlights why current AI still lacks the ric
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