— Techniques
Embedding
A numeric representation of text (or image) that captures its meaning.
What is Embedding?
An embedding is a vector of numbers (typically 384-1536 dimensions) that represents the semantic meaning of a piece of text, image, or audio. Similar meanings produce similar vectors. Embeddings power RAG, semantic search, recommendation systems, and clustering. Generated by embedding models like OpenAI's text-embedding-3, Cohere Embed, or open-source alternatives.
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Terms connected to Embedding
Techniques
RAG (Retrieval-Augmented Generation)
Giving an AI access to your private documents so it can answer questions about them.
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Vector Database
A database optimised for storing and searching embeddings by similarity.
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Semantic Search
Search that understands meaning, not just keyword matches.
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