Enterprise

Nvidia wants to solve 'hard problems' for health care companies with AI. At stake? $10 trillion.

Nvidia is chasing the health care market for AI with a medical-grade version of its data center server and software platform, and Kimberly Powell is leading the charge.

Kimberly Powell, Nvidia's vice president and general manager of Health Care

Nvidia’s top executive heading up its health care efforts is Kimberly Powell, vice president and general manager of Health Care and a 14-year veteran at the company.

Photo courtesy of Nvidia

For most of its early life, tech industry insiders thought of Nvidia as a business focused on video game graphics technology; first graphics cards, and then the specialized chips that power them.

But Nvidia has come a long way after it realized that the parallel processing tech that was so good at rendering graphics could also be put to work on machine-learning problems for enterprise tech. It has expanded its chip offerings into the data center, developed a software business and recently pursued the $10 trillion health care market en route to surpassing Intel as the most valuable chip company in the U.S.

That $10 trillion target is no secret among other big enterprise tech companies that have an AI business either. Cloud titans such as Oracle and Microsoft have also begun to chase the lucrative industry, each announcing big acquisitions in recent months that revolve around the evolution of health care and AI.

Nvidia’s top executive heading up those efforts is Kimberly Powell, vice president and general manager of Health Care and a 14-year veteran at the company. Powell recently spoke with Protocol to discuss Nvidia's recent health care initiatives, and how it plans to approach the sector in the future.

This interview has been edited and condensed.

Can you outline Nvidia’s current effort in health care?

We think we can make a significant contribution in the area of medical imaging and medical devices. One of the largest workloads in supercomputing, and accelerated computing, is in the area of life sciences. To be able to do simulation of diseases, and chemical compounds interacting and trying to stop the behavior — [it’s] to do drug discovery, essentially in silico, in a computer.

Our charter, which we put out back in 2018, is that with the accelerated computing platform [and] the new modern AI era, how do we take these computing approaches, and help the health care industry benefit from it. We called the platform Nvidia Clara, after Clara Barton who invented the Red Cross. Our Clara is a platform that helps the industry take advantage of the most advanced computing approaches — everything from hardware solutions, through accelerations layers, libraries, full-on applications. And we target domains we think we can make a unique contribution to.

We solve really hard problems. One of our most successful bodies of work is Monai, which is where we’ve taken PyTorch and essentially wrapped it and domain-specified it for health care.

What is the market opportunity Nvidia is chasing in health care?

You can think of the [total addressable market] in a lot of interesting ways in health care, and where it’s going to go. But it's approaching a $10 trillion industry. For example, if you look at the radiology practice itself, it’s a half-trillion dollar market, where you’re doing a combination of the devices themselves, but then also the skills needed to interpret these images. You could imagine that whole thing as the TAM.

The expansion will continue too. If you know a bit about health care, only a third of the population of the world has access to things like radiology, or even surgical procedures. And it’s growing. We’re living longer; our population is growing. We don’t have enough medical professionals to serve the existing population. And so we need to have ways of automating and augmenting the medical professionals that we do have. Being able to create competing platforms that could take someone who has studied medicine for a few years and make them a trained surgeon rather than the 30 years it usually takes for them to be a trained surgeon.

So that’s where the market analysis you could take all the way through if you’d like. We think about it in a way that without a doubt every single one of our medical professionals will be augmented with these platforms with these capabilities.

How large is the team and how does it fit into Nvidia?

It’s in the hundreds, because at this point we are building full-on products and platforms. We have everything from applied research, engineering, product marketing, technical marketing, developer marketing, campaign marketing, business development.

I essentially report to [Nvidia CEO] Jensen [Huang]. Our report structure generally doesn’t really signify anything. In general, I’m working with Jensen on efforts in health care and he is very, very passionate about this area, which is why [it's] 14 years in the making.

How do you decide where and how to allocate resources, R&D budget?

We have three fundamental questions that get us set straight on this. One, that we have identified an important problem. [Second], is it super hard to do? Because if it’s not hard to do, I’d love for somebody else to go do it. Truly. Because we attract the world’s most fantastic talent and you want them to work on something that is just hard to do. And the third thing is: Do we have a unique capability to do it? If all three of those don’t check out, then it’s not really something we would deploy resources on.

Does Nvidia make hardware that is designed specifically for health care applications? Or does Nvidia build something like its DGX data center AI server systems for the health care industry?

If you think of what medical devices are, what they are becoming — they are being redefined by AI and robotics. And they need a specific platform that is medical grade. Is that down to the silicon? No, it's built with the three chips Nvidia offers: smart networking interconnection that [can] stream in all of the data that’s coming off the sensors, whether it’s ultrasound or an endoscope. You need to stream that data in and then you need to start operating its data pipeline to do more and more sophisticated things to assist the surgeons or the radiologist, or whoever is reading the result.

We use our network interconnect to stream in to do a direct memory access right into the [graphics processing unit] to start all of the AI processing. If you think of what happens with ultrasound, the first thing you want to do is increase the image quality, or you want to de-noise it. These are all now AI applications that can be done in software. And as soon as you get the image quality where you want it, you want to start providing real-time information. This is the heart, this is the ventricle, how much blood flow is going through this particular area. Cut here, don’t cut there. It’s guiding, so they’re essentially becoming robots themselves.

So Clara Holoscan is a platform for medical devices, and Clara Holoscan MGX hardware is the compute platform that will essentially create that architecture: streaming in massive AI computing, and in a complete real-time sensor to display, because you need that when you’re in a surgical environment.

When you talk about Nvidia’s health care products being “medical grade” what do you mean by that exactly? How can a chip or a piece of software achieve that?

There are two pieces of it. Because we’re a platform, there’s a hardware layer and a software lawyer. And those two pieces need to be medical grade. You can’t put any old computer next to a patient; liquids might spill on it, for example. Or it might interfere with other signaling that’s going inside the health care environment. There are certifications that the market has to go through, so we architect the system for that at the hardware layer. At the software layer, there are similar safety certifications for medical devices. It exists for the automotive industry, all the redundancy things that you need, and similar things exist in the health care industry.

Think of a startup company engineering a system, getting it medically certified, building the entire compute stack so they can run their application on top. They’ll go out of business before they can even dream about doing it. We’re really just trying to create that platform for them to accelerate innovation and go to market.

Picking up on what you said about training a surgeon in three years vs. 30, what will we have to achieve in computing technology, chip design and software in order to enable that?

If you’ve watched Jensen describe what he means by “million-x” — it’s a paradigm, not just for medical but we absolutely apply it. The first thing you need to do is make something accelerated. The next thing you need to do is scale it in parallel, and then the next thing we’ve done is introduce artificial intelligence.

Let me give you the example of drug discovery. We are able to take what would otherwise be an intractable problem, where you have to accurately simulate how drugs interact with diseases. It’s intractable in its current form but it can be refactored by using AI, physics-informed neural networks, to essentially augment that simulation and approach. So these AI models that are essentially able to predict physics behavior applied throughout, so that’s going to be what is absolutely transformational in the area of drug discovery and simulation. And simulation is present in everything that we do, and what we are going to do in the future. So without that, it will be very hard to get where we want to go, and that’s the next five to 10 years — AI being able to do these physical world calculations, physics predictions.

Policy

Google is wooing a coalition of civil rights allies. It’s working.

The tech giant is adept at winning friends even when it’s not trying to immediately influence people.

A map display of Washington lines the floor next to the elevators at the Google office in Washington, D.C.

Photo: Andrew Harrer/Bloomberg via Getty Images

As Google has faced intensifying pressure from policymakers in recent years, it’s founded trade associations, hired a roster of former top government officials and sometimes spent more than $20 million annually on federal lobbying.

But the company has also become famous in Washington for nurturing less clearly mercenary ties. It has long funded the work of laissez-faire economists who now defend it against antitrust charges, for instance. It’s making inroads with traditional business associations that once pummeled it on policy, and also supports think tanks and advocacy groups.

Keep Reading Show less
Ben Brody

Ben Brody (@ BenBrodyDC) is a senior reporter at Protocol focusing on how Congress, courts and agencies affect the online world we live in. He formerly covered tech policy and lobbying (including antitrust, Section 230 and privacy) at Bloomberg News, where he previously reported on the influence industry, government ethics and the 2016 presidential election. Before that, Ben covered business news at CNNMoney and AdAge, and all manner of stories in and around New York. He still loves appearing on the New York news radio he grew up with.

Sustainability. It can be a charged word in the context of blockchain and crypto – whether from outsiders with a limited view of the technology or from insiders using it for competitive advantage. But as a CEO in the industry, I don’t think either of those approaches helps us move forward. We should all be able to agree that using less energy to get a task done is a good thing and that there is room for improvement in the amount of energy that is consumed to power different blockchain technologies.

So, what if we put the enormous industry talent and minds that have created and developed blockchain to the task of building in a more energy-efficient manner? Can we not just solve the issues but also set the standard for other industries to develop technology in a future-proof way?

Keep Reading Show less
Denelle Dixon, CEO of SDF

Denelle Dixon is CEO and Executive Director of the Stellar Development Foundation, a non-profit using blockchain to unlock economic potential by making money more fluid, markets more open, and people more empowered. Previously, Dixon served as COO of Mozilla. Leading the business, revenue and policy teams, she fought for Net Neutrality and consumer privacy protections and was responsible for commercial partnerships. Denelle also served as general counsel and legal advisor in private equity and technology.

Workplace

Everything you need to know about tech layoffs and hiring slowdowns

Will tech companies and startups continue to have layoffs?

It’s not just early-stage startups that are feeling the burn.

Photo: Kirsty O'Connor/PA Images via Getty Images

What goes up must come down.

High-flying startups with record valuations, huge hiring goals and ambitious expansion plans are now announcing hiring slowdowns, freezes and in some cases widespread layoffs. It’s the dot-com bust all over again — this time, without the cute sock puppet and in the midst of a global pandemic we just can’t seem to shake.

Keep Reading Show less
Nat Rubio-Licht

Nat Rubio-Licht is a Los Angeles-based news writer at Protocol. They graduated from Syracuse University with a degree in newspaper and online journalism in May 2020. Prior to joining the team, they worked at the Los Angeles Business Journal as a technology and aerospace reporter.

Entertainment

Sink into ‘Love, Death & Robots’ and more weekend recs

Don’t know what to do this weekend? We’ve got you covered.

Our favorite picks for your weekend pleasure.

Image: A24; 11 bit studios; Getty Images

We could all use a bit of a break. This weekend we’re diving into Netflix’s beautifully animated sci-fi “Love, Death & Robots,” losing ourselves in surreal “Men” and loving Zelda-like Moonlighter.

Keep Reading Show less
Nick Statt

Nick Statt is Protocol's video game reporter. Prior to joining Protocol, he was news editor at The Verge covering the gaming industry, mobile apps and antitrust out of San Francisco, in addition to managing coverage of Silicon Valley tech giants and startups. He now resides in Rochester, New York, home of the garbage plate and, completely coincidentally, the World Video Game Hall of Fame. He can be reached at nstatt@protocol.com.

Workplace

This machine would like to interview you for a job

Companies are embracing automated video interviews to filter through floods of job applicants. But interviews with a computer screen raise big ethical questions and might scare off candidates.

Although automated interview companies claim to reduce bias in hiring, the researchers and advocates who study AI bias are these companies’ most frequent critics.

Photo: Johner Images via Getty Images

Applying for a job these days is starting to feel a lot like online dating. Job-seekers send their resume into portal after portal and a silent abyss waits on the other side.

That abyss is silent for a reason and it has little to do with the still-tight job market or the quality of your particular resume. On the other side of the portal, hiring managers watch the hundreds and even thousands of resumes pile up. It’s an infinite mountain of digital profiles, most of them from people completely unqualified. Going through them all would be a virtually fruitless task.

Keep Reading Show less
Anna Kramer

Anna Kramer is a reporter at Protocol (Twitter: @ anna_c_kramer, email: akramer@protocol.com), where she writes about labor and workplace issues. Prior to joining the team, she covered tech and small business for the San Francisco Chronicle and privacy for Bloomberg Law. She is a recent graduate of Brown University, where she studied International Relations and Arabic and wrote her senior thesis about surveillance tools and technological development in the Middle East.

Latest Stories
Bulletins