Vector Embedding
A vector embedding is a numeric representation of a word, sentence, or image as a list of numbers, where mathematical closeness reflects closeness in meaning.
A model converts a piece of text into a vector with several hundred dimensions. Two sentences with similar meaning produce close vectors, even if they share no common words.
This technique enables semantic search, finding relevant content by meaning rather than exact keyword match. It sits at the core of RAG and vector databases.