What Is an Embedding in AI?
In AI, an embedding is a list of numbers (a vector) that represents a piece of content — such as a word, sentence, or image — so that items with similar meanings end up close together in that numerical space. Embeddings let computers compare meaning mathematically.
How They Are Used
Semantic search, recommendations, grouping similar documents, and retrieval-augmented generation all rely on measuring the distance between embeddings.
Example
The embeddings for “car” and “automobile” are close together, while “car” and “banana” are far apart.
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Last updated: September 29, 2026. This definition is for general educational purposes only. It is not financial, investment, tax, legal, or medical advice, and it does not recommend any product or course of action. For decisions about your own situation, consult a qualified professional.