Vector embeddings are numerical representations that capture the relationships and meaning of words, phrases and other data types. Through vector embeddings, essential characteristics or features of ...

A vector database is a type of database technology that's used to store, manage and search vector embeddings, numerical representations of unstructured data that are also referred to simply as vectors ...

Artificial intelligence (AI) processing rests on the use of vectorised data. In other words, AI turns real-world information into data that can be used to gain insight, searched for and manipulated.

Vector databases power RAG, semantic search, recommendations, and memory. Learn how indexing, filtering, and hybrid retrieval ...

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...

Enterprise adoption of retrieval-augmented generation has moved sensitive corporate content into a new storage format that existing security tools cannot inspect. Companies deploying internal AI ...

PostgreSQL with the pgvector extension allows tables to be used as storage for vectors, each of which is saved as a row. It also allows any number of metadata columns to be added. In an enterprise ...

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...