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 ...

Generative AI is revolutionizing data and analytics, but its applications demand advanced data management capabilities to handle vast, diverse, and complex datasets that include images, video, audio, ...

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 ...

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 ...

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.

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

In a nutshell: Adobe has been steadily adding generative AI functionality to its content creation suite over the past year. The latest update features tools that help users automatically generate ...

With an emphasis on AI-first strategy and improving Google Cloud databases' capability to support GenAI applications, Google announced developments in the integration of generative AI with databases.

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 ...

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today introduced its platform-independent GPU-accelerated vector indexing. This new feature ...