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Embeddings

Lists of numbers that represent meaning — texts about similar things end up close together.

An embedding model turns a sentence, document or image into a vector (a long list of numbers). Similar meanings land near each other in that space: "How do I reset my password?" sits right next to "I forgot my login."

Embeddings power semantic search, recommendations, duplicate detection and — most importantly — RAG.

💡 Think of it like

A map where every idea has coordinates, and related ideas are neighbors.

🧠 Test yourself

Which of these describes Embeddings?

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