Nvidia's aspirations in the field of medicine and health care are becoming increasingly evident.

• NVIDIA unveiled approximately 20 new AI-centric healthcare tools at its 2024 GTC AI conference, and established partnerships with Johnson & Johnson and GE Healthcare for surgery and medical imaging.
• The AI chip leader's move into healthcare is a decade-long effort with substantial revenue potential.
• The adoption of AI for drug discovery, a process that can take up to 12 years and cost billions, is happening rapidly.

Nvidia showcased its commitment to the healthcare industry at its 2024 GTC AI conference, where it announced partnerships with Johnson & Johnson and GE Healthcare for the use of generative AI in surgery and medical imaging, respectively. Additionally, the company launched approximately two dozen new AI-powered, healthcare-focused tools, highlighting the importance of medicine to Nvidia's non-tech sector revenue opportunities in the future.

Nvidia's popularity today can be attributed to its provision of the technology and infrastructure for something that was previously impossible or required significant time, money, and resources. Healthcare, including biotechnology, chemicals, and drug discovery, is a powerful and untapped industry with immense potential. AI can speed up the drug discovery process and even find new uses for drugs that may have failed to produce results for their initial disease targets. Over the past 18 months, the tangible outcomes and compelling use cases of AI in the pharmaceutical, medtech, and biotech industries have made it more hope than hype.

The development of drugs is a risky and lengthy process, taking at least a decade from idea to clinical trials, and it can cost billions with a high likelihood of failure, as Ural stated.

In late 2023, EY surveyed biotech CEOs and found that about 41 percent were considering concrete ways to use generative AI for their companies. This is a significant increase compared to Ural's experience of 30 years in the industry. Nvidia's conference in 2023 focused on healthcare, with a doubling down on an ambition it has had for a long time. During an earnings call with investors in February, Nvidia mentioned several ways its technology was being adapted for the medical field. Companies like and Generate: Biomedicines are expanding their biomedical research with the help of hyperscale or GPU specialized cloud providers, and they need Nvidia AI infrastructure to facilitate the process. According to Colette Kress, Nvidia chief financial officer, in healthcare, digital biology and generative AI are helping to reinvent drug discovery, surgery, medical imaging, and wearable devices. Nvidia has 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

In 2020, NVIDIA invested $50 million in Recursion for its drug discovery projects. Recursion is using its biological and chemical data to train NVIDIA's AI models on its cloud platform. The company has also collaborated with Roche's Genentech to develop new medications and improve treatment protocols. Additionally, in 2021, Recursion partnered with Schrödinger for drug discovery.

The BioNeMo platform, a cloud service for drug development, is one of NVIDIA's strongest assets in the health-care industry.

"Joshi stated that designing semiconductors and computing platforms for others to use is one thing, but building complete technology packages that can be sold to customers is a whole different ball game. For instance, if a biotech company takes the full technology from Nvidia and simply begins working on it without considering how to utilize the information technology, it is a different approach than figuring out how to use the technology to achieve a specific goal."

Generative AI platforms in the biotech industry can help pharmaceutical companies reduce expenses beyond the drug development process. Many companies have offshored their back-office processes for supply chain, finance, and administrative functions, as well as manufacturing, to cut costs. However, with the growing emphasis on bringing jobs back to the U.S. and the increasing tensions between nations, offshoring jobs has become increasingly expensive.

""With AI-powered robotic process automation, you can now perform drug development at home at a much lower cost. This not only speeds up the process but also reduces the cost of running a company, allowing you to allocate more capital towards drug development and find cures faster," Ural stated."

Jensen's company, which initially focused on designing gaming graphics cards, has made significant strides in the health-care space. In 2012, Jensen recognized the potential of his graphics card to be used for general computing and saw it being used at Stanford University to solve mathematical problems.

To fully realize the benefits of AI in the health-care sector, leaders must gain more support from the nation's largest workforce, which is composed of health science and wellness employees. According to EY's AI Anxiety in Business survey, over two-thirds of these employees have concerns about the use of AI, and 7 out of 10 are anxious about AI adoption in the workplace.