<ul><li>Retrieval-Augmented Generation (RAG) is a transformative approach in AI that enhances the performance of large language models.</li><li>RAG connects language models to dynamic knowledge bases, enabling real-time, domain-specific responses.</li><li>RAG mitigates issues such as hallucination and outdated responses, ensuring accurate and relevant information retrieval.</li><li>The RAG framework operates through indexing, retrieval, and generation phases to integrate knowledge with language model outputs.</li></ul>

Understanding Retrieval-Augmented Generation (RAG) in AI

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