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Embedded AI evaluators won’t be an easy solution, Hugging Face’s policy chief says
AI labs have staked their reputations on model benchmarking — the supposedly neutral and accurate system of evaluations that are designed to measure whether one AI product is better than another.
AI Summary
AI labs rely on model benchmarking to claim one product outperforms another, but the evaluation methods are still complex and evolving. Irene Solaiman, Hugging Face’s chief policy officer, said this during a discussion at TechCrunch Disrupt last week. She argued that testing must become a more consistent science for the industry to trust benchmarks in the future.
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