Vector database

A vector database is a type of database designed to store and process large volumes of vector data, which are mathematical objects representing multi-dimensional numerical values. These databases are optimized for efficient search, retrieval, and analysis of vector data, making them ideal for applications like machine learning, natural language processing and recommendation systems. They are particularly useful for AI-related tasks that involve large amounts of numerical data and require fast query processing. 

This definition was generated by AI, using our BigNoodle model.

Vector databases can be used to contain specific information, not available to the model itself. When interacting with the model one or more vector databases can be added to the interaction, thus expanding the "knowledge" of the model.