In this episode, we unpack legible AI—systems that not only answer questions but show their reasoning in a way humans can verify. We break down OpenAI's prover-verifier training (including the sneaky prover twist) and discuss how a smaller verifier helps teach bigger AIs to be clear. We also explore the 45-second human evaluation experiment and what legible AI could mean for medicine, law, and AI safety, with references to the OpenAI blog post and the underlying research paper.

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