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 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 ...

Vector databases unlock the insights buried in complex data including documents, videos, images, audio files, workflows, and system-generated alerts. Here’s how. The world of data is rapidly changing ...

Vector databases manage the vast data sets needed to power generative AI tools. As generative AI embeds itself across all industries, the use cases for vector databases increase as well. A vector ...

Vector databases are making a resurgence as generative AI hype sweeps across every industry. Organizations with developed graph and relational databases may question if they need to add another ...

Companies across every industry increasingly understand that making data-driven decisions is a necessity to compete now, in the next five years, in the next 20 and beyond. Data growth — unstructured ...

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 ...

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...

Each step adds operational overhead as data volumes grow, with most pure-play vector databases adding unpredictable pricing on top. Elasticsearch Vector Database handles all of this automatically ...

When Aquant Inc. was looking to build its platform — an artificial intelligence service that supports field technicians and agents teams with an AI-powered copilot to provide personalized ...