Large language models mimic what people say to do rather than work out what to do, which is why they are not about understanding the world.

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• Process supervision by an LLM judge cannot be run for long, because a judge with billions of parameters is gameable and RL will find its cracks. AKAndrej Karpathy17 Oct 2025LLMsreinforcement learning
• Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. CFChelsea Finn12 Aug 2026LLMsreinforcement learning
• Without an execution environment, LLMs cannot properly act on their understanding of how to forward evolve a system. TLTobias Lütke21 Sept 2026LLMsreinforcement learning
• A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. AKAndrej Karpathy17 Nov 2025reinforcement learning
• Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. AKAndrej Karpathy20 Mar 2026reinforcement learning

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