AI-native vector database startup Weaviate B.V. is expanding into artificial intelligence development with the launch of a new “workbench” that consists of various cloud-based applications and tools ...
IBM worked with Nvidia and Samsung to demonstrate a content-aware storage (CAS) system that can hold a 100-billion-vector database on a single server, work targeted at making retrieval-augmented ...
Amazon Web Services (AWS) has announced vector storage for its S3 cloud object storage – S3 Vectors – in a move it claims will reduce the cost of uploading, storing and querying vectorised data in AI ...
A Scalable Vector Database, a cutting-edge solution, is meticulously designed to efficiently manage high-dimensional vector data. Unlike traditional databases that handle data types such as strings ...
Artificial intelligence (AI) processing rests on the use of vectorised data. In other words, AI turns real-world information into data that can be used to gain insight, searched for and manipulated.
Vector databases emerged as a must-have technology foundation at the beginning of the modern gen AI era. What has changed over the last year, however, is that vectors, the numerical representations of ...
For most enterprise applications, vector support is a feature that should be woven into the existing data estate, not a reason to add a second source of truth.
Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.
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