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Home/Glossary/Embedding Model
AI Glossary Term

What does “Embedding Model” mean?

Definition

A model specialized for converting data into vectors used for semantic search, clustering, and retrieval.

Related terms

Embedding
A numeric vector representation that captures semantic meaning of text, images, or other data.
Feature Extraction
Converting raw data into informative features that a model can use.
Hybrid Search
A retrieval approach that combines keyword (lexical) search with vector (semantic) search for better recall and precision.
Knowledge Graph
A graph structure of entities and relationships used for reasoning or retrieval.
RAG (Retrieval-Augmented Generation)
A method that retrieves external knowledge and feeds it into generation at inference time.
Semantic Search
Search that matches meaning rather than exact keyword overlap, often using embeddings.

Learn more in our free guides

AI Models ExplainedModel CollapseModel LifecycleModel Context Protocol

See also

Distilled ModelEval HarnessDifferential PrivacyFeature StoreData ProvenanceGroundednessData LineageGuarded Decoding
PreviousDistilled ModelNextEval Harness
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