Choosing the Right Embedding Dimension for Semantic Search
Executive Summary: Embedding dimension — the length of the vector used to represent text, images or other data — is a critical hyperparameter for semantic search. Higher dimensions let embeddings capture finer-grained semantics, often boosting recall a…