Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 491 Agentic and Physical AI in Medtech How NVIDIA is Changing the Space EDAI.

Episode Date: March 27, 2025

Agentic AI is AI that does your work, right? ⚙️And Physical AI is just robots and stuff, right? 🦾Not exactly. When those technologies are applied to the medtech space, though, the meanings change. Agentic AI can get you into the doctor faster. Phyiscal AI can (literally) save your life. Agentic and Physical AI in Medtech: How NVIDIA is Changing the SpacePrerna Dogra knows this all too well. She's the Senior Manager for Healthcare AI Products at NVIDIA, and she joined the Everyday AI show to show us how new GenAI advancements in the medtech space are doing more than spitting out quarterly reports. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the conversation and ask Jordan and Prerna questionsUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:Augmented AI vs. Physical AI in HealthcareIntroduction of Prerna Dogra and NVIDIA's Role in Healthcare AINVIDIA’s Technology Stack and Impact on MedTechImage Reconstruction and Diagnostic Applications with NVIDIA GPUsRobotic Surgery and Personal Impact on Prerna DograCurrent State of AI and GenAI in MedTechAgentic AI and its Current Use Cases in MedTechAgentic AI Systems and Human Expert InvolvementExplanation of Three Computer System in AI by NVIDIAEthical Considerations and Safeguards in Agentic AIPotential Risks of Agentic AI in MedTechExciting Advancements in Agentic AI and Physical AI in HealthcareFocus on Real-Time AI Processing and Simulation ComputersFuture Challenges and Opportunities in Robotics and AI in HealthcareTimestamps:00:00 NVIDIA's AI Impact in Healthcare05:56 AI's Impact on MedTech Progress06:52 GenAI's Impact on Healthcare Transformation10:20 "Agentic AI Revolutionizes Healthcare Navigation"13:43 Digital Agents Enhancing Healthcare Delivery18:13 Agentic AI Progress in Healthcare21:22 Empowering Communication Through RoboticsKeywords:augmented AI, physical AI, healthcare, medicine, medtech, generative AI, NVIDIA GTC, agentic AI, host, Everyday AI, livestream, podcast, newsletter, company growth, Prerna Dogra, NVIDIA, product management, algorithm ecosystems, computing appliance, accelerated computing, artificial intelligence, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. When we think about agented AI,

sometimes I think people think of sitting behind the computer screen and maybe helping you get that quarterly KPI report out quicker. When we talk about physical AI, maybe we just think about humanoids in a warehouse. But both of those things are actually so much more than that. And especially when we talk about, I think highly specialized and very important sectors like healthcare and medicine and meta tech. You know, I think that generative AI, you know, is maybe always not talked about as much as it should in those fields because it impacts all of us, right? Not everyone here is in marketing.

Not everyone here deals with legal, but, you know, we all benefit from what generative AI can do in the mettech space. So that's why I'm extremely excited for today's conversation and back at Nvidia GTC to talk about egentic AI and physical AI in MetTech and how Nvidia is changing that space. All right, I'm excited for today's conversation. I hope you are too. What's going on, y'all? My name's Jordan Wilson.

I'm the host of Everyday AI, and this is your daily live free podcast and free daily newsletter, helping us all not just keep up with AI, but how we can use all of the latest news and advancements to get ahead to grow our company and career. That's you. You're on the right clicks. So make sure you do go to our website at Your EverydayAI.com. Because if you miss some of the great insights from today's episode,

we're going to be recapping it all in the newsletter. So make sure you check that out. All right. So like I said, if you're listening on the podcast, you don't see this. You're on the live stream. You see we're here at GDC and there's been a ton going on. So I'm excited for today's conversation. So please help me.

Welcome to the show, Praeradadadadad, the Director of Product Management for Healthcare. I at NVIDIA, Furnat, thank you so much for joining the everyday a.m. Thank you, Jordan, for having me. All right. I'm excited for today's conversation, but before we get started, tell everyone a little bit of what you do in your role at NVIDIA. Sure. So, at NVIDIA, I had our product between the developer ecosystem's team.

And essentially, our mission is to translate the amazing technology stack that we've built with our computing appliance and our accelerated computing, artificial intelligence into the most impactful industry, the healthcare industry. So we are really solving for like what are the domain specific problems, right? Healthcare is very main specific. So as an example, in computer vision things like cats and dogs videos are to reflect to these MRI and CT1 vector images. So how do we turn that domain problem into a computer science problem and really bring

accelerated compared to that. Similarly, when we're thinking about agents and the big ban of LLM's conversation layer. How do these AI models start about the medical job, the medical job? We said at that translation layer or in Bilea's amazing technology staff or the industry of healthcare and life sciences and my focus is specifically in nettec. And for that we may create new software capabilities because we found something very unique to solve. Or sometimes we adapt our existing staff and really build very intentional good markets with our partners and our customers. But essentially bringing GQ community too. Yeah, and it's extremely exciting. But maybe how it explains where it's a little bit,

how does this ultimately play out in their lives, right? Because no one goes to the doctor and sees, you know, an NVIDIA logo on there, right? But I'm guessing, you know, that many of the major, you know, names in health are using, you know, something along the line, whether it's, you know, GEOs from VDIA or your software, you know, in the health space. But, you know, tell us a little bit who are those, you know, partners and customers that are, you know,

using the METEC kind of offerings from or through NVIDIA. Absolutely. So our journey in METTEC really started 12 years ago. And the first application that we identified for accelerated computing was this thing called image re-instruction. But what that essentially is that when you go to get your MRI or your CT scan, it's actually a GPU that can take all of that sensor information and convert it into an image. And so in diagnostics, generally if you talk to these clinicians, they'll say what you can see, you can cure. Right. And all these breakthroughs like with best scanning and so on, like how with low dosage,

can you get these really high quality, high-fidelity imagery? So that is one area where it's almost like Nvidia and site all of these devices. Robotic surgery, right? It became so real. It really came home for me. I always spoke to this, right? Not all the past customers, but we're all consumers of health care.

And I thought two years ago I had to go through a prostate surgery. and that it was the da Vinci system of buying via and it's a minimally invasive surgery. So really again, bringing this ability of keeping care of cancer and solving with technology, what couldn't have been possible in the past. Super, super touching story, yeah, like the word that you and your colleagues are doing, you know, being able to see it help firsthand, you know, in your father's, you know, surgery. That's really, really cool story. So, you know, one thing I do want to talk about is, you know, before we get into, you know, the announcements and what's new and what's changing, can you maybe just bring our audience to like, where are we at today? Because as an example, I didn't know that, you know, image reconstruction was essentially just powered by GDVUs, right? So like, where are we at if you had to give a, you know, the state of the state address for, you know, AI in MetTac. Like, where are we? Our most, you know, large healthcare or. organizations, you know, using, you know, Gen AI and AI and GVUs, you know, around their entire structure

or is it still like, you know, some companies and some larger organizations are still, you know, kind of quote-unquote old school and still figuring out this new Gen AI wave. Yeah, so what I would say is because healthcare is so fragmented, like, unlike any other industries, you know, like we have like one big layer and if they take Gen. I just become like good. But I would say that Gen AI and the problem, and the problem is, like, promise is really come to last. The journey very started with a lot of the perception AI pieces, which have been there for like eight, seven, eight years now and you can see the growing number of FDA algorithm that

are proved with the learning. But this power of Gen.i and Gen. Z is now really coming through. So as an example of epic, I don't know if everybody knows about it, but if you've used your my chart. And it is the number one EMR system. It is getting forward by all thoughts of these co-pilots and really streamline the patient experience.

We also announced the integration of Nvidia's technology stack and our models into Epic on their AI phone gig. Like that is one direction where, right? Once someone like Epic integrates Gen. I is going to touch everyone's life. And it's as simple as when I open my MyChart app. Today I look at this summary and it's a bunch of jargon. I'm not following.

Can I have a patient summary that's in English? Yeah. In the future, can I make a call and not be an awaiting life? And even talk with a digital agent. Like, so these capabilities are sort of really bringing that access to care. We're totally seeing that done through. I think it's a great example. A bridge is, again, a wonderful example.

when they have really they have stale of the art technology for their automatic speech recognition and death to speech and this really alien intelligence system where they are bringing back that conversation between the doctor and the patient right like the last so many other like it's been you talking to the patient and the doctor is constantly at the screen and administrative work the nerve is putting in the course so that's that's a great example and a bridge is installed. And it's having a great to get a great.

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could you let us know, like, where are we at now? Maybe talk us through, you know, some of the, you know, the benefits or use cases that you're already seeing you know, because it seems like, you know, last year, you know, here at GDC, you know, it's like agentic was more of a whispered, but now it's everywhere. So like, where are we at and what are some of those use cases already in the MetTexam? You hit on it, Jordan. Like last year, it was so like Gen.

I, and like NetTIC was like, oh, we don't have our foundation models yet and so on and so forth. And that is actually the proof point of what a foundation model means, right? because all these companies and to take these models and attack them to our contacts and really give AI now agencies. So that means not just that the AI model has the knowledge, but it now has the context awareness and we now like this ability to reason through a problem, right? So if I'm a patient, I'd have to call them to the hospital and figure out, hey, what's my care plan? Or how do I get?

Where's the party? Or what's my insurance code and so on? You can have this agentic AI system that is then calling and knows like, I need to call a specialty model from the insurance place. I need to call the specialty model from a nutrition space. I need to pull this out in the EMR and so on. So what agentic AI has done is taken all this amazing technology of AI that's the research papers and a model here and model there, but we already brought together to deliver something of value.

And so where it is right now, I would say, is where we are certainly seeing like that is down a bridge. not the great one to be very hard. When they're seeing these companies that are set on this journey, really taking off exponentially because those systems are performing incredibly well in the real world. But even more importantly, it opens up the atom for so many more to now come. Because traditionally, NetTac has been like a very regulated industry, as it should be. But the part of bring real world in fact from all this technology has been very high.

We just see that this genii, a genetic AI, and now this ability of reasoning and chain of thought, which allows to bring a transparency into systems, the perfect time to really bring value into health care. So the benefits, you know, I think are fairly obvious, right? You know, better health care, you know, faster, you know, communication, hopefully improved outcomes, right? But I think a lot of the early talk about the agentic AI, this is based around more of like, okay, here's things that I myself would be doing on my computer, right? Researching this, updating this document, you know, sending it over to an internal or external stakeholder. You know, can we talk, you know, with the benefit or what of the potential benefit so high with agency AI in MetTech?

You know, what about the potential risk, right? Because I know people are always worried about, you know, agetic AI. And then when you get in the MetTech space, so can you talk about, you know, a little bit about kind of the work that you and your team or maybe your partners are doing, you know, to ensure kind of that agency doesn't go off the rail, so to speak. Yeah, no, that is an excellent point. And also to the kind of like I said, this is a regulated industry as it should be. So what we see would have played, even with these systems and these agents,

you are essentially with an expert in the right? So the value of actually is in the operational efficiency of. of these systems that they can bring. As an example, it helped contextualize, like hippogradic care, has built these digital agents

that can make a call post-operative to a patient and find out how you're doing off to yourself to me and have you been taking your medications where the patient can ask what kind of diet tree plans I should be in. Okay, one, these are areas that don't happen today. Right?

So these digital agents and systems can bring care, which where it's not available at all. But then also because they are working, these, like in case of Hi, they have like a whole body of nurses across different systems, really try around these agent, digital agents and things like that. That was and not work. And really giving that time back to the clinicians and the nurses. So in all of these cases, with a bridge, with hippoccurricular, credit AI, a whole suite of these startups, autophiles company. They're all very much with that human expert in the loop that's really trying to say,

like, are these agencies well-gariled and so on. From a technology standpoint, InBedia does that, right, we have in our own to make sure we have the right software and allow developers to build a very safe system with things like garrails and so on. So there's been a lot of talk of them, you know, so far here at GTC about kind of this, this three computer system, right? Can you explain that, you know, maybe to our audience that didn't get a chance to listen to Jensen's keynote, which you should all vote do, by the way. But can you explain what that is and how it's going to be impacting the work that you all do? Yes, this is truly an inflection point.

And in me, I've been an engineer and technology and so you can really see this convergence of three very key computers, right? The first one is your AI computer. This is where you are training and creating these world-class AI moms. The second computer that really comes to life is now the simulation computer, right? And if you think about the simulation computer was actually one huge missing. piece. So the AI computer had its breakthrough when we

when we craft this notion of like our supervisor. I don't need data that's constantly labeled. The stimulation computer now almost is the AI playground. All this intelligence that I created, right? If you think about any field

of robotics, there is no chance that you can have humanoid and all these robots. Imagine in our industry like several robots, the cost of doing, that thing and all of that in the real world is so hot. Right.

So now you almost have this playground. I can be generating synthetic cases. I can be generating synthetic worlds that are mimicking the real world is right. That is the second tribute of stimulation. You take something that you train, you pull that into stimulation where it goes into post-training and it's getting really refined. So a model that was trained for tasks. or foundation model is brought in and now put into simulation

to be actually contextualized in the muta, which is similar, but in a different domain, right? And that's part of the simulation system. It's not running on world clock time, right? So your AI can practice and practice that it really masters this gear. And then the third computer, as we like to call it, the brain of the robot.

That is really the real-time computer. So we have invested heavily into this platform called in Bidia Holoscan, which is all about this real-time process. And so these three computers, the AI computer to train models, the stimulation computer at the playgrounds, but this AI tool, and there are systems actually, because it's not just one again and one, but it's a combination of AI models

and agent-a-framed works to really bring this sort of intelligence, that's just not knowledge, can perceive and act in meaningful ways that the physical world. into that simulation computer and when you think it's a quiet escape, oh, I think this robot knows how to do a solution just perfectly. We could take that and bring it into a real, what we call, filled-to-reel transfer of a prototype. And the fact that you can go through all these three loops

in constant digital prototyping more is what that really means. for every industry and then for healthcare specifically in that. Yeah, I think that was a crucial explanation because I'm sure there's people out there that, you know, when they hear agetic AI and then they hear, you know, humanoid, you know, performing surgeries, it's probably helpful to understand that, you know, this is a very well-thought-out, you know, I'm sure there's trillions of data points that go into this and so many countless simulations. So thank you for, you know, taking us behind the curtains on that one a little bit. But, you know, so one question as we wrap up here, because we've talked about a lot in this conversation so far, but, you know, out of everything, you know, that was announced here at GTC, what would you say that, you know, at least, you know, under the umbrella of today's episode of Agentic AI and physical AI, and that's, well, see, the one advancement that you and your team maybe are most excited about.

and then what will, you know, that recent announcement here mean for your space in the future? Kind of like, hey, are you able to tackle the new problem? Are you able to offer, you know, a new type of service for different type of healthcare organizations? What's that one thing that you're most excited about? Yeah. I know it's hard.

I go to understand. I do. Yeah. It's like a two-hour keynote. How can you pick one thing? I want to pick something that wasn't in the heat out. It was in Kubei Power's special address. She's the VPN GM for our healthcare business unit.

And we launched what we call it Isaac for healthcare. It is this domain specialization of the three computers that just walked through. And personally, I am most excited and passionate about this space because Because the reality is we are millions of people shot of healthcare style. The reality is we have aging parents. We all want to be consumers of healthcare. And so this, this, it's not just about innovation. In healthcare, it is a necessity to really bring physical AI to help in ways it was not

possible. I was walking the floor. There's this company called Wondercraft, who goes like these eight skeletons for people who are allied. And to see that young woman stand up from her wheelchair and be able to walk,

that is life-seating as he can get. There's a company called Synchron. They designed these brain-computer interface implants and they have this whole way of potentially patients with ALF like how do you take that signal turn it into intent and allow someone who was not able to interact with the world because of the impairments of the so many give them the agency to be able to do so to be able to your wife, I love you, to be able to turn on the fan, to be able to tell your care

whenever I can breathe. So this is going to be a long journey. We are aware of that, but we are here because this is an incredibly hard problem to solve, and we are committed to Loventary to take this forward. So it is a necessity. And so that is a necessity. And so that's where where my mind, my heart and my entirety focus is going to be to really see how to bring these three leaders to life to see as there we take on the bigger challenge and robots. Love to hear it. It's just extremely, you know, exciting and inspiring to see what's next because, you know,

I think, you know, sometimes people think, you know, when, oh, GPUs and this, that, perhaps that headlines, but what that opens up in terms of, of capabilities and possibilities just for us as humans for our health, I think is extremely inspiring. So, Prairada, thank you so much for taking time out of your day to join the Everyday A Actually, we really appreciate it. Absolutely. It's a pleasure. Thank you, Jordan. All right. And there was a lot in there. So, you know, if you miss something,

or if you want to know more about something that prayer in a second, it's going to be in our newsletter, so make sure you go check that out. So if you haven't already, go to your everydaya.com. Signed up for that free daily newsletter. We're in recapping this as well as everything else you need to stay up to date, get ahead with Gen. AI. Thanks for tuning in. Hope to see back tomorrow.

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