As supercomputers take on the mighty challenge of accelerating research in the complexities of life sciences, Artificial Intelligence (AI) is not far behind. Researchers are testing a system based on AI to detect neurological disorders like dementia in just one brain scan. As researchers begin the trial of the system, currently it takes several scans and tests to diagnose dementia. An earlier diagnosis of the disorder could be life-saving and enhance treatment strategies. The team of researchers from the University of Cambridge are hopeful that the AI system will be tested in a "real-world" clinical setting on about 500 patients, in its first year of trial.

Nvidia is launching the $100 million Cambridge-1, the most powerful supercomputer in the United Kingdom, and it is making it available to external researchers in the U.K. health care industry. The machine will be used for AI research in health care, and it's one of the world's fastest supercomputers. Nvidia will make it available to accelerate research in digital biology, genomics, and quantum computing. Nvidia is collaborating with AstraZeneca, maker of one of the COVID-19 vaccines, to fuel faster drug discoveries and creating a transformer-based generative AI model for chemical structures. Transformer-based neural network architectures, which have become available only in the last several years, allow researchers to leverage massive datasets using self-supervised training methods, avoiding the need for manually labeled examples during pre-training.

Artificial intelligence (AI) stocks appear to be gaining traction among tech investors in the stock market today. Whether you are familiar with the concept of AI or not, it remains an increasingly relevant area of research now. Simply put, AI is defined as the simulation of human intelligence processes by machines, hence the name. Notably, AI tech has and continues to evolve to carry out complex tasks like natural language processing and speech recognition. If that wasn't enough, the tech also does this much more efficiently than humans today.

He said the system will enable research breakthroughs at a scale and speed previously impossible with global impact potentially benefiting millions. Its first projects with AstraZeneca, GSK, Guy's and St Thomas' NHS Foundation Trust, King's College London and Oxford Nanopore Technologies include developing a deeper understanding of brain diseases like dementia, using AI to design new drugs and improving the accuracy of finding disease-causing variations in human genomes. Cambridge-1 is the first NVIDIA supercomputer designed and built for external research access. The company will collaborate with researchers to make much of this work available to the greater scientific community. The system is located at a facility operated by NVIDIA partner Kao Data. Cambridge-1 is the first supercomputer NVIDIA has dedicated to advancing industry-specific research in the U.K. The company also intends to build an AI Center for Excellence in Cambridge featuring a new Arm-based supercomputer, which will support more industries across the country.

The UK's most powerful supercomputer, which its creators hope will make the process of preventing, diagnosing and treating disease better, faster and cheaper, is operational. Christened Cambridge-1, the supercomputer represents a $100m investment by US-based computing company Nvidia. The idea capitalises on artificial intelligence (AI) – which combines big data with computer science to facilitate problem-solving – in healthcare. "If you could imagine ganging up 10 refrigerators in a row and then having several rows of those refrigerators – that is the size and shape of this computer," said Kimberly Powell, vice-president of healthcare at Nvidia. The UK has already made strides with massive datasets such as the UK Biobank, which encompasses anonymised of medical and lifestyle records from half a million middle-aged Britons.

THERE'S AN APOCRYPHAL story about how NVIDIA pivoted from games and graphics hardware to dominate AI chips – and it involves cats. Back in 2010, Bill Dally, now chief scientist at NVIDIA, was having breakfast with a former colleague from Stanford University, the computer scientist Andrew Ng, who was working on a project with Google. "He was trying to find cats on the internet – he didn't put it that way, but that's what he was doing," Dally says. Ng was working at the Google X lab on a project to build a neural network that could learn on its own. The neural network was shown ten million YouTube videos and learned how to pick out human faces, bodies and cats – but to do so accurately, the system required thousands of CPUs (central processing units), the workhorse processors that power computers. "I said, 'I bet we could do it with just a few GPUs,'" Dally says. GPUs (graphics processing units) are specialised for more intense workloads such as 3D rendering – and that makes them better than CPUs at powering AI. Dally turned to Bryan Catanzaro, who now leads deep learning research at NVIDIA, to make it happen.

We Fools may not all hold the same opinions, but we all believe that considering a diverse range of insights makes us better investors. Follow Anders on Twitter, LinkedIn, and Google . Semiconductor designer NVIDIA (NASDAQ:NVDA) today announced that it is building the United Kingdom's most powerful supercomputer ever. Dubbed Cambridge-1, the system will give healthcare researchers access to impressive artificial intelligence (AI) tools. The $52 million Cambridge-1 will be installed at the university it's named after, and is scheduled to come online by the end of 2020.

Through a new partnership with GlaxoSmithKline, AstraZeneca and the U.K.'s National Health Service, the chip maker Nvidia plans to build Great Britain's most powerful supercomputer--and dedicate its use to artificial intelligence research in healthcare. Dubbed Cambridge-1, the machine is designed to deliver 400 petaflops of performance, or 400 quadrillion floating-point calculations per second. When presented with dense systems of linear equations used in AI--such as simulations of molecular models and chemical interactions among potential drug compounds--it is expected to provide 8 petaflops of supercomputing power, ranking it number 29 on the list of the world's fastest. It is slated to come online before the end of the year, with GSK and AstraZeneca among the first drugmakers to use the system. Researchers from King's College London, Oxford Nanopore and the Guy's and St. Thomas' NHS Foundation Trust will also have access.

Most of you are probably familiar with the chip giants like Intel & AMD which command a bigger share of the computing processor market, but this entrant to the chip market in 1993 has solidified its reputation as a big name in the arena. Although most well-known for its graphical processing units (GPUs) -- GeForce is its primary & most popular product line, the company also provides system-on-a-chip units (SoCs) for the mobile computing and automotive market. Since 2014, Nvidia has begun to diversify its business from the niche markets of gaming, automotive electronics, and mobile devices. It is now venturing into the futuristic AI, along with providing parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. Let's review of some these endeavors.

Jensen Huang, CEO of NVIDIA, has kicked off the company's annual GTC conference with a series of AI announcements--including a doubling-down of its UK investments. NVIDIA is investing heavily in the UK's accelerating AI sector. The company announced its acquisition of legendary semiconductor giant Arm for $40 billion back in September along with the promise to open a new AI centre in Cambridge. "We will create an open centre of excellence in the area once home to giants like Isaac Newton and Alan Turing, for whom key NVIDIA technologies are named," Huang said at the time. "We want to propel Arm – and the UK – to global AI leadership."