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What is RAG Detailed about?

Retrieval-Augmented Generation (RAG) integrates retrieval systems with generative models to enhance accuracy by grounding outputs in external data, making it useful in enterprise AI, chatbots, and search engines. It helps reduce hallucinations and improve factual consistency, although it faces challenges like retrieval latency and maintaining updated knowledge bases. Future developments aim for real-time retrieval and better contextual understanding.

Author

oneplustab072

Language

EN