Vector databases for RAG
A vector database for Retrieval-Augmented Generation (RAG) is a specialised storage system designed to help AI retrieve information based on semantic meaning rather than relying solely on keyword matching. Vector databases have become increasingly important in AI applications because they store information as numerical vectors that capture semantic relationships, enabling machine learning models to efficiently perform similarity searches and retrieve relevant information.
[Read More]
