A vector store is a specialized database designed to efficiently store, index, and retrieve high-dimensional vectors. These vectors typically represent data points such as text, images, or other forms of unstructured data that have been transformed into numerical representations through processes like embedding. Vector stores are crucial for tasks involving similarity search, clustering, and nearest neighbor search, as they enable rapid querying and comparison of vectors based on their geometric properties. They are often used in applications like recommendation systems, semantic search, and Natural Language Processing (NLP) to enhance the performance and scalability of Large Language Models (LLMs).
See also Vector Embedding and Vector Search.
The LLM Knowledge Base is a collection of bite-sized explanations for commonly used terms and abbreviations related to Large Language Models and Generative AI.
It's an educational resource that helps you stay up-to-date with the latest developments in AI research and its applications.