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Nvidia’s ‘Cambridge-1’ utilizes AI to advance research in healthcare

Nvidia’s ‘Cambridge-1’ utilizes AI to advance research in healthcare

Nvidia’s ‘Cambridge-1’ is now operational and utilising AI and simulation to advance research in healthcare.

The UK’s most powerful supercomputer and among the world’s top fifty, Cambridge-1 was announced by the technology company in October last year and cost $100 million (£72m) to build.

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 will empower world-leading researchers in business and academia with the ability to perform their life’s work on the U.K.’s most powerful supercomputer, unlocking clues to disease and treatments at a scale and speed previously impossible in the U.K.,” said Jensen Huang, founder and CEO of NVIDIA.

“The discoveries developed on Cambridge-1 will take shape in the U.K., but the impact will be global, driving groundbreaking research that has the potential to benefit millions around the world,” he added.

AI for healthcare is growing rapidly in the UK, with a range of start-ups and larger pharmaceutical companies turning to mining the vast quantities of data available to discover potential drugs, further understand certain diseases, and improve and personalise patient care.

“It’s great to see it in the UK ecosystem,” said Roel Bulthuis, head of the healthcare team at Inkef Capital. “Many European healthcare systems are not as advanced in their thinking about using data and integrating that into the healthcare system.”

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According to Frontier Economics, an economics consulting firm, Cambridge-1 has the potential to create an estimated value of £600 million over the next 10 years.

(Except for the headline, this story has not been edited by The Technology Express staff and is published from a syndicated feed)

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