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.

Did you know that over 80% of the data generated today is unstructured? Traditional databases often fall short in managing this type of data efficiently. That’s where vector databases come into play.

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now In 2014, a breakthrough at Google ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Vector databases, a relatively new type of database that can store and ...

With ChatGPT dominating the space of conversational AI and rapid, helpful response turnout, as well as OpenAI’s open source retrieval plugins for the revolutionary tool, ChatGPT will begin to permeate ...

For most enterprise applications, vector support is a feature that should be woven into the existing data estate, not a ...