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 ...

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 ...

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 ...

Vast Data Inc. today announced enhancements to its Vast Data Platform, enabling it to support structured and unstructured data in a single DataSpace with linear and secure scaling.The enhancement ...

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.

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.

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 ...

Startup Zilliz Inc., best known as the creator of the Milvus vector database, announced today it has raised $60 million through an extension to its earlier $43 million Series B round of funding.Pr ...

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.