AI / ML
Embedding
A numerical representation of text in a high-dimensional vector space where semantically similar items are positioned close together. 'Running shoes for flat feet' and 'supportive athletic footwear for low arches' would have similar embeddings despite different words. AI agents use embeddings to match product data to user queries by semantic meaning, not just keyword overlap. This is why natural, descriptive product content outperforms keyword-stuffed titles in agent commerce.
Why it matters
It is what lets a system find things by meaning rather than by keyword, which is why a search for winter creative can return an ad tagged only cold weather.
In practice
Mostly infrastructure. It matters when semantic search returns near-misses: the embedding is grouping by a similarity you did not intend.
Related terms