Retrieval Augmented Generation
Also known as RAG
Retrieval augmented generation is a method in which a model is given relevant documents fetched from a data source at the moment of the question, and answers from them rather than from memory alone.
Why It Matters
It is how companies put their own documents behind an AI system without retraining a model, and it is the mechanism by which published articles can end up inside an AI answer.
Related Terms
- Semantic SearchSemantic search matches the meaning of a query against the meaning of documents, using numerical representations of text, rather than matching the words themselves.
- Vector DatabaseA vector database stores text, images or other content as numerical vectors and retrieves the items whose vectors are closest to a query, which is how meaning-based search is served at speed.
- EmbeddingsEmbeddings are numerical representations of text, images or other data, arranged so that items with similar meaning sit close together, which lets software compare meaning mathematically.
- AI SearchAI search describes search products that answer a question in prose, drawing on retrieved sources, instead of returning only a list of links.
VANTAGE52 Coverage
Published reporting filed under the topics behind this concept.
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