Retrieval augmented generation (RAG): grounding a model in your own data with Azure AI Search

A language model knows only what was in its training data, which is out of date and does not include your company's private documents. Asked about them, it may invent a plausible answer. Retrieval augmented generation (RAG) fixes this by retrieving relevant passages from your own data at question time and adding them to the prompt, with instructions to answer only from those passages. The model's job changes from remembering facts to reading and summarizing the facts you hand it.