Evals are systematic processes used to test and measure the performance, safety, or reliability of AI models and systems. Developers use them to identify weaknesses, while organizations rely on them for compliance and trust. Researchers, product teams, and regulators benefit most, ensuring models behave as intended before real-world deployment.
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