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 ...

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...

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, ...

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 ...

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 ...

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.

About two years ago, popular cache database Redis was among a wave of vendors that added vector search capabilities to their platforms, driven by the surge of interest in generative AI.… Vector ...

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.

VCs are hungry to back vector database startups and other behind-the-scenes tech that improves AI. Vector databases store and structure data that LLMs can then pull from. Business Insider has ...