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An embedding is a numerical representation of a text or an object as a vector, capturing its meaning.
An embedding turns a word, a sentence or a document into a vector of numbers. Content with similar meaning ends up close together in this vector space.
This property makes semantic search possible: instead of comparing exact words, you compare meanings. It is the basic building block of RAG systems.
Embeddings are produced by specialised models, then stored in a vector database to be queried quickly.
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