Embeddings

Also known as vector embeddings

Embeddings are numeric vector representations of text (or images) positioned so semantically similar content sits close together in vector space. They're the substrate under vector search and RAG: an embedding model converts a query and a corpus into vectors, then similarity search finds the nearest matches. Embedding model choice and dimensionality directly bound retrieval quality — a mismatched or stale embedding model is a common silent RAG failure.

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