Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...

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 ...

Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI - SiliconANGLE ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

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 ...

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 ...

The AI boom has launched numerous conversations on what's possible as more people grasp AI’s ability to transform the workplace, the economy and society at large. However, as the buzz around this ...

Learn how to identify keyword cannibalization using OpenAI's text embeddings. Understand the differences between various models and make informed SEO decisions. This new series of articles focuses on ...