Retrieval-Augmented Generation (RAG) is a method for improving the output of large language models (LLMs). While LLMs are trained on vast amounts of data, they may lack access to proprietary or enterprise-specific information behind paywalls, or other custom data needed to generate accurate results. RAG supplements the LLM’s knowledge by retrieving relevant external information, making […]
