In Defense of AI Evals, for Everyone
Read OriginalThis article argues against the recent 'anti-evals' sentiment in the AI community. It defines 'evals' as the systematic measurement of application quality, explains their role in the AI model lifecycle (pretraining and posttraining), and contends that all successful teams perform evaluations, even informally. It emphasizes the importance of evals for building reliable AI applications, particularly in coding and other technical domains.
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