Retrieval-Augmented Generation (RAG) equips AI systems with real-time data access, enhancing response accuracy and relevance, but requires personalized approaches for effective implementation.
RAG is like giving a smartphone with the latest info to someone relying on outdated knowledge; it transforms generative AI by reducing errors and enhancing responses through real-time data integration.
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