The development of LIMS will involve not only integrated data, but integration with enterprise applications, in Kevin Smith's view
We must move beyond software designed to solve single physics problems, according to Lars Langemyr
Clare Sansom talks to Janet Thornton, a pioneer of computing for the life sciences
Conrad Wolfram believes we should treat computers like cars: we should specify the problem and let the computer do the working out
Tom Wilkie looks at 10 years of scientific computing
Web services will offer a way for LIMS to integrate with enterprise resource planning systems, says Peter Rees
Rohit Khanna looks forward to the integration of instruments and software to master the mounds of data created in the lab
Dr John McAlister finds that scientific computing is not an end in itself but that success depends on it
Susie Stephens and Dennis Constantinou see Grid computing as the way to master the flood of information from the life sciences
Jack Little believes that model-based design is the best way to turn new ideas into real things
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.
