We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP) ...

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 ...

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 ...

First solution to combine dense, sparse, and image embeddings with vector search in one managed environment. Reduces latency, cuts network costs, and simplifies hybrid and multimodal search BERLIN & ...

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 ...

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 ...

Have you ever found yourself frustrated with AI systems that confidently provide answers, only to realize they’re riddled with inaccuracies? It’s a common pain point for anyone working with generative ...