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 don’t just store your data. They find the most meaningful connections within it, driving insights and decisions at scale. A vector database is just like any other database in that it ...

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 ...

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, ...

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...

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 ...

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.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Ludi Akue discusses how the tech sector’s ...

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 ...

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 ...