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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The traditional way for a database to answer a query is with a list of ...

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 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 ...

I recently wrote a Finextra piece entitled 3 GenAI Use Cases for Capital Markets; The Power of the Vector. In it, I discussed the increasing importance of the so-called vector database and vectors ...

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 ...

Timescale Inc., the creator of a cloud time-series database that’s based on PostgreSQL, is looking to cater to artificial intelligence developers with the launch of its latest vector capabilities.

Rockset, the leading search and analytics database built for the cloud, is announcing native support for hybrid search, redefining the potential of search and AI applications. Now, users can benefit ...

Ontology-based algorithms provide a rigorous framework for organising and processing complex data by representing domain knowledge as structured concepts and their interrelationships. These methods ...