Vector databases are specialized storage systems designed to efficiently store, index, and retrieve high-dimensional vector data. They are commonly used in machine learning and AI applications, such as image and voice recognition, to facilitate fast and accurate similarity searches among large datasets. By converting complex data into vectors and leveraging indexing techniques, vector databases can quickly find items similar to a query vector, making them essential for recommendation systems, search engines, and other AI-driven services.
Tips, Tech and AI to grow