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Ian Buck On 5 Big Bets Nvidia Is Making In 2020

'We're reaching a point where supercomputers that are being built now are all going to be AI supercomputers,' Nvidia data center exec Ian Buck tells CRN of the chipmaker's AI ambitions.

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AI-Accelerated Healthcare

Another area of focus for Nvidia is healthcare, for which the chipmaker is building out its own software stack to enable GPU-accelerated AI processes for things like medical imaging.

It's a highly regulated and complicated industry, but the opportunity and frankly the importance of solving those problems is too important [for Nvidia] to not be investing," Buck told CRN.

Medical imaging is one such area that can benefit from AI processors, according to Buck, because the number of images being processed every day is far too much for the number of radiologists in the U.S.

"We have around 50,000 radiologists in hospitals, but a typical radiology department has to process about 8,000 images every day. So if you do the math — and 50,000 radiologist is a critical shortage — this actually works out about four seconds per image per radiologist, which is a frightening number in terms of you getting a scan," Buck said.

Nvidia is tackling AI for healthcare through Clara, a set of developer tools that allows developers to take advantage of the chipmaker's GPU-accelerated computing.

"In the imaging use case an Imaging workflow is actually relatively simple and familiar to many people in AI," Buck said at GTC. "You have unlabeled data, it has annotated data, and we can use the Clara SDK to train a system on the label data to learn how to recognize certain things inside of the images."

As part of Clara, Buck said, Nvidia has "13 world-class pre-trained models already designed to extract major organs from medical imaging data," and it includes a process called "transfer learning" that can take the work of existing training models and extrapolate it to new use cases.

"We want to look for specific kinds of tumors, for example, so we can start from a pre-trained model which already is recognizing organs and train it [to start] looking for cancers," he said.

 
 
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