Glossary · AI & ML

Embedding

A numerical vector representation of text, data, or objects that captures semantic meaning for AI processing.

An embedding is a dense vector representation of data (text, images, or other objects) in a continuous, low-dimensional space where semantically similar items are positioned closer together. Text embeddings convert words, sentences, or documents into fixed-size numerical vectors that capture semantic meaning. For example, the embeddings for "revenue" and "sales" would be closer together than "revenue" and "temperature." Embeddings are fundamental to many AI applications: semantic search, recommendation systems, clustering, and RAG (Retrieval-Augmented Generation). Popular embedding models include OpenAI's text-embedding-3, Cohere Embed, and sentence-transformers.

Fig — every answer ships with the tables, rows and SQL behind it.