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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

As we have noted before, vector databases aren’t new even though people talk about them that way, and in fact can trace their origins back a few decades. Exactly when depends on who you ask, but their ...

In today’s data-driven world, the exponential growth of unstructured data is a phenomenon that demands our attention. The rise of generative AI and large language models (LLMs) has added even more ...

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 ...

Google wants Gemini, its family of generative AI models, to power your app’s databases — in a sense. At its annual Cloud Next conference in Las Vegas, Google announced the public preview of Gemini in ...

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.

Keyword search in graphs and relational databases constitutes a pivotal research domain that seeks to bridge the gap between natural language queries and complex data repositories. By enabling users ...

Several decades ago, scientists started to set up biological data collections for the centralized management of and easy access to experimental results, and to ensure long-term data availability (Fig.

As processor speeds increase, the need to reduce latency between the CPU and data becomes more pressing. The answer to that need has seen the rise of local flash storage and PCIe flash solutions. But ...