Embedding
vector embedding, vectors, semantic search, vector search
In one sentence
A list of numbers that represents the meaning of a piece of text, so that texts meaning similar things end up close together and can be found by distance.
Why it matters
A model turns the text into a long list of numbers, 1,536 for OpenAI's text-embedding-3-small and 3,072 for the large one, the same length for a word or a page, placed so that similar meanings land close together. Closeness measures meaning, not shared words: "invoice overdue" sits near "payment reminder" and far from "invoice template". No single number means anything on its own, and embeddings from different models cannot be compared. It is what makes search by meaning, and with it RAG, possible.
Sources
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