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

If you’re building generative AI applications, you need to control the data used to generate answers to user queries. Simply dropping ChatGPT into your platform isn’t going to work, especially if ...

A 'picker' gathers items at Amazon's Fulfilment Centre in Peterborough, central England, on November 28, 2013. 'Cyber Monday' which falls this year on Monday December 2, 2013, is expected to be the ...

In today’s data-driven world, the exponential growth of unstructured data is a phenomenon that demands our attention. The rise of generative AI and large language models (LLMs) has added even more ...

Zilliz, the company behind Milvus, the world’s most widely adopted open-source vector database, recently announced the ...

With vector search a key element of AI development, data platform vendor Actian on Tuesday launched its first vector database. Vectors are algorithmically generated numerical representations of data, ...

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...

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 ...

NEW YORK, NY - 2009: A Times Square hot dog street vendor cart is seen in this 2009 New York, NY, early evening cityscape photo. (Photo by George Rose/Getty Images) Cloud is a combo. It wasn’t long in ...

Vector search is nothing new. Its role as a critical data management capability, however, is a recent development due to the way it enables discovering data needed to inform generative AI models.