Retrieval Augmented Generation (RAG) in Generative AI

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Retrieval Augmented Generation (RAG) in Generative AI

A strategy for 'grounding' AI tools in accurate facts by combining generative and retrieval models. RAG uses a pre-trained model to retrieve relevant information from vetted and verified documents (a knowledge graph) and then uses a generative model to output content based in fact.

"Our chatbot was confidently giving incorrect answers to our patients. Since we're in medicine, that's not acceptable, even for casual use, so we used a RAG strategy so that the chatbot retrieve facts from medical texts but then makes them easier to read for lay users."


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