Word of the Day
Embeddings
Embeddings turn text into numeric vectors so similar meanings sit close together, powering semantic search and RAG.
Get it freeAn embedding is a list of numbers (a vector) that represents the meaning of a piece of text. Texts with similar meaning produce vectors that are close together, so software can measure semantic similarity mathematically rather than matching exact words.
Embeddings are the engine behind semantic search, recommendations, clustering, and the retrieval step in RAG: to find the passages most relevant to a question, a system embeds the question and finds the stored passages whose embeddings are nearest.
Related: rag · token · fine tuning
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