Sophia Ktori highlights the role of the laboratory software in the use of medical diagnostics
Gemma Church explores the use of modelling and simulation to predict weather and climate patterns
Robert Roe reviews the latest in accelerator technology and finds that GPUs and coprocessors will be key fixtures in the future of deep learning
Robert Roe finds that commoditisation of flash and SSD technology and the uptake of machine learning and AI applications are driving new paradigms in storage technology.
The first in series of articles covering the Paperless Lab Academy conference – in this article Robert Roe looks at the importance of adopting digital technologies - the benefits and pitfalls that laboratories face when on the road to digital convergence.
In January 2020 the American Diabetes Association released a new set of clinical standards that, for the first time, included the use of an FDA-approved autonomous artificial intelligence (AI) platform for detecting diabetic retinopathy in people with diabetes.
At the end of February physIQ and the US Department of Veteran’s Affairs published data from a clinical trial demonstrating the use of physIQ’s machine-learning algorithm to predict when an individual patient with previously diagnosed heart failure will likely require a readmission to hospital.
Cloud research tools provide a platform for new avenues of scientific research by providing fast access to bare-metal resources.
New processors and GPU technology continue to demand more power than the previous generations, combining this with increasingly dense architectures requires cooling solutions such as liquid or immersion cooling.
Tate Cantrell, CTO, Verne Global, comments on the cost of the AI computing revolution
European researchers are working on a new programming environment for exascale computing that aims to make using these systems more efficient and programmers more productive.
