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OpenAI explores how to optimize AI models without sacrificing true objectives

OpenAI has published research on how to mitigate Goodhart's Law, a phenomenon where a measure becomes a target and ceases to be a good measure. The paper explores mathematical approaches to optimize AI models for complex human preferences, which are difficult to measure directly. OpenAI uses proxy objectives, like a reward model, and investigates techniques such as best-of-sampling to ensure that optimizing the proxy still aligns with the true underlying objective. AI

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RANK_REASON The cluster contains an academic paper from a major AI lab discussing research into AI alignment and optimization techniques.

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OpenAI explores how to optimize AI models without sacrificing true objectives

COVERAGE [1]

  1. OpenAI News TIER_1 ·

    Measuring Goodhart’s law

    Goodhart’s law famously says: “When a measure becomes a target, it ceases to be a good measure.” Although originally from economics, it’s something we have to grapple with at OpenAI when figuring out how to optimize objectives that are difficult or costly to measure.