RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
Retrieval-Augmented Generation (RAG) combines large language models (LLMs) with information retrieval techniques. The key objective is to connect a model’s built-in knowledge with the vast and ...
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They developed LLMs applications using Retrieval-Augmented Generation (RAG), a technique that tapped internal datasets to ensure models provide answers with relevant business context and reduced ...