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.

The emergence of vector databases and vector search for handling massive quantities of complex data have radically transformed the way AI is implemented and managed. As a specialized approach for ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Data platform vendor DataStax is entering the vector database space, ...

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 ...

Vector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie. The proliferation of large language models (LLMs) and 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 ...

Vector databases are blowing up with massive funding rounds from Weaviate, Pinecone, and Chroma—but what exactly are they? At their core, vectors are just arrays of numbers that represent things like ...

Timescale is looking to further advance its namesake open-source database platform with new AI capabilities announced today. Timescale was founded in 2017 as a time series database (TSDB) technology ...

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 ...