AI Definitions: RAGs

Retrieval augmented generation (RAG) – A RAG combines a retriever (used to collect relevant information from a document) and a generator (which compares the query vector to other known vectors, selecting the most similar ones, and then generating an answer to the user’s query). Rather than generating answers from a set of parameters, the RAG collects relevant information from the document. In effect, this coding technique instructs the bot to cross-check its answer with what is published elsewhere, essentially helping the AI to self-fact-check. RAG lets companies “ground” AI models in their own data, ensuring that results come from documents within the company, minimizing hallucinations.

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