A machine learning technique where models learn to align with human preferences by using feedback as a guide. It refines AI behavior through trial-and-error rewards based on human ratings, improving tasks like content generation and chatbot responses. Developers and users benefit from safer, more relevant outputs that better match desired outcomes.
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