At the Microsoft Build conference held this week in the US, Microsoft announced Azure Machine Learning Hardware Accelerated Models powered by Project Brainwave integrated with the Microsoft Azure Machine Learning SDK
GIGABYTE a provider of server hardware for high performance computing has released two new 4U GPU servers: the 8 x SXM2 GPU G481-S80, and the 10 x GPU G481-HA0
Robert Roe looks at recent developments in processor and accelerator technology
The University of Cambridge is set to receive a new AI supercomputer as part of a £10 million partnership between the Engineering and Physical Sciences Research Council (EPSRC), the Science and Technology Facilities Council (STFC) and the University
The best research needs ideas from a wider range of people and publications, writes Anita Schjøll Brede
A team of academic researchers and industrial experts are concluding a successful three-year research collaboration which has tackled the challenges of producing new software for high-performance AI and other data-intensive applications
UK-based driving simulation company, rFpro, has launched a commercial platform to train and develop autonomous vehicles using simulation
At last week’s Nvidia GTC conference the company announced three new products aimed squarely at the datacentre and AI markets
Iris.ai, an artificial intelligence tool which helps researchers find relevant scientific papers and journals, today announced the launch of version 4.0
Some 44 per cent of life science professionals are using or experimenting with AI and deep learning, while 94 per cent expect an increase in use of machine learning within two years
Robert Roe interviews MathWorks Loren Dean, on the use of AI in modelling and simulation
Every device needs to work seamlessly in its operating environment. But when that environment is a human body, things get complicated.
Christian Marcazzo, general manager at IDBS, highlights trends in life sciences research and development.
Data is a company’s biggest asset, yet for any organisation, keeping a handle on the potentially vast volumes and diversity of data that are generated can represent a considerable issue.
Rob Lalonde, Univa’s cloud VP general manager, considers the unique challenges posed by HPC
Deep learning has seen a huge rise in popularity over the last five years in both enterprise and scientific applications.
HPC users are increasingly turning to cloud technologies due to their flexibility and scalability, allowing them to quickly change the size of their workloads, adopt new technologies in a small testing environment and to help to increase the agility of a company working across multiple sites, or
