Embedding

An embedding turns content - a sentence, a document, an image - into a fixed-length vector of numbers. The model that produces it is trained so that items with similar meaning land near each other in that vector space.

Once content is embedded, "find similar" becomes a math operation (measuring distance between vectors) instead of exact keyword matching. Embeddings are the backbone of vector search, semantic search, and RAG.