Making benchmarks outputs directly useful for AI safety and security

As AI systems improve, benchmarks are saturating quickly, losing their ability to measure progress. LessWrong contributor Pierre Peigné proposes repurposing this capability: use benchmark evaluation to directly solve problems in AI safety and security, such as hardening the sandboxes where AI runs or optimizing the code that powers safety experiments. He's calling for others to take on this work, noting that the window to get ahead on AI safety is narrowing.

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