Nvidia CEO Jensen Huang delivers a keynote address through the Nvidia GTC Conference on the SAP Center in San Jose, California, on March 18, 2024.
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Last week, Nvidia announced deals with Johnson & Johnson to be used of generative AI in surgery, and with GE Healthcare to enhance medical imaging. The health care developments at its 2024 GTC AI conference, — which also included the launch of roughly two dozen latest AI-powered, healthcare-focused tools — reveal just how vital medicine is to Nvidia’s non-tech sector revenue opportunities in the long run.
“The explanation why Nvidia is so popular today is since it mainly provided the plumbing and the technology for something that you can not do simply before or if you happen to needed to do something like this you would want probably several times more time, money and value,” said Raj Joshi, a technology analyst and senior vp at Moody’s Rankings. “Health care, whether it’s biotechnology, chemicals, or drug discovery is a really powerful area.”
Nvidia shares are up near 100% year-to-date, and the biotech industry is an example of the untapped potential that investors are proceed to bet on. AI can speed up the means of drug discovery and even find uses for drugs which will have failed to provide results for the initial disease they were developed to focus on.
“During the last 18 months or so, we are likely to consider it’s more hope than hype due to tangible outcomes after which the very compelling use cases how AI helped with the pharmaceutical industry, medtech industry or biotech industry,” said Arda Ural, EY Americas health and life sciences industry market leader.
Drug development is a dangerous process that may take at the least a decade from concept to clinical studies, Ural said. It is also a process that may cost billions, with a high likelihood of failure.
About 41 percent of biotech CEOs surveyed by EY in late 2023 said they were “concrete” ways generative AI could possibly be used for his or her firms. “This could be very high for my experience, having been 30 years on this industry,” Ural said. “It is a really unusual feature we’re seeing with AI that is being picked up much faster than other technologies.”
The health care focus from Nvidia at its conference was a doubling down on an ambition it’s had for a very long time. During an earnings call with investors in February, Nvidia mentioned several ways its technology was being adapted for the medical field. Firms like Recursion Pharmaceuticals and Generate: Biomedicines have been expanding their biomedical research with the assistance of hyperscale or GPU specialized cloud providers, they usually need Nvidia AI infrastructure to facilitate the method.
“In healthcare, digital biology and generative AI are helping to reinvent drug discovery, surgery, medical imaging and wearable devices,” said Colette Kress, Nvidia chief financial officer. “We’ve built deep domain expertise in healthcare over the past decade, creating the NVIDIA Clara healthcare platform and NVIDIA BioNeMo, a generative AI service to develop, customize and deploy AI foundation models for computer-aided drug discovery.”
Last yr, NVIDIA invested $50 million in Recursion for its drug discovery projects. Recursion is inputting its biological and chemical data to coach NVIDIA’s AI models on its cloud platform. The corporate has also worked with Roche’s Genentech to develop latest medications and higher treatment protocols. It also partnered in 2021 with Schrödinger for drug discovery.
Considered one of NVIDIA’s best health-care strengths up to now is the BioNeMo platform, a generative AI cloud service specifically made for drug development.
“It’s one thing to design semiconductors and computing platforms for others to do something. However it’s one other thing altogether when you may construct full-fledged packages of technology that you could sell to a customer,” Joshi said. “For instance if you happen to are a biotech firm, you’re taking the complete technology from Nvidia, and you simply start working on it versus determining ‘how do I take advantage of this information technology?'”
Biotech-focused generative AI platforms have the flexibility to cut back costs for pharmaceutical firms beyond the drug development process. Many firms offshored their back office processes for supply chain, finance and administrative functions, in addition to manufacturing, to lower your expenses. But with the rise in geopolitical tensions and the emphasis on bringing jobs back to the U.S., moving jobs overseas has grow to be an increasing cost.
“Now you may try this at home with AI with a much lower cost because you may have now robotic process automation, powered by AI,” Ural said. “So it isn’t only helping speed up the drug development, but additionally it helps with lowering the fee of running an organization. Meaning you may deploy more of the capital towards drug development and find more cures faster.”
The health-care space is an example of how far an organization that was designing gaming graphics cards a decade ago has come. “You’ve got to offer credit to them that Jensen had the foresight way back in 2012 when he saw some people actually use his graphics card at Stanford University to unravel some sorts of mathematical problem,” Joshi said. “He said, ‘You recognize what, this could actually be used to do what is named general computing, you already know, the things that all of us do on a regular basis on a traditional basis.'”
But to totally realize the advantages of AI which can be just becoming clear within the health-care sector, leaders might want to get more support from considered one of the nation’s largest workforces. In response to EY’s AI Anxiety in Business survey, greater than two-thirds of health science and wellness employees have concerns concerning the use of AI, and seven out of 10 are anxious about AI adoption within the workplace.