Vector embeddings convert tokens (or words, sentences, chunks, documents, graph nodes, and concepts) to a high-dimensional space that encodes the semantic meaning, such that similar tokens are near each other. Options include - Word2Vec (2013) - BERT (2018) - OpenAI Embeddings (2024) [[vector database]] [[Chroma]] [[FAISS]] [[t-stochastic neighborhood embeddings]]