That same vector database could help query all the images of aluminum ladders and get a summary of the related text or descriptions for each. They are also gaining a lot of traction when LLMs need to ...

A vector database becomes essential when handling unstructured data requiring complex algorithmic work, such as high-dimensional data, similarity searches, real-time AI applications, or when ...

Vector graphics have many advantages. We show you how to create a vector graphic or convert an image into an SVG file quickly and free of charge.

Vector databases, on the other hand, store and process data in the form of vector embeddings, which convert text, documents, images, and other data into numerical representations that capture the ...

Unstructured data — such as images, video, audio, and user behaviors — generally don’t fit the relational database model; it can’t be easily sorted into row and column relationships.

Vector databases unlock the insights buried in complex data including documents, videos, images, audio files, workflows, and system-generated alerts. Here’s how.

Text, images, and videos are all examples of unstructured data. Vector databases capture and store the essence of a particular piece of data that a machine-learning program or LLM can then pull from.

Vector databases and search aren’t new, ... We built software to scan electrophoresis samples into a database, and my job was to convert each DNA pattern’s image into representable data.

On Tuesday, Adobe announced major updates to AI image synthesis features across several products, including Photoshop, Illustrator, and Adobe Express. The updates include three new generative AI ...