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.

Storage optimization technologies like compression and deduplication have reduced the capacity requirements of many processes within the data center, most noticeably backup. When these data sets need ...

The computing industry has reached a significant milestone with the ratification of the 1.0 RISC-V Vector Specification. This development marks the beginning of a new era in computing efficiency, as ...

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 ...

Vector database offers on-prem, cloud-native, or SaaS deployment, leading performance, a rich set of integrations and language drivers, and a dizzying array of optimization options. Efficient ...

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 ...