On this episode of the Six Five On the Road, hosts Patrick Moorhead and Daniel Newman are joined by Dell Technologies‘ Jon Siegal and Jonathan Huang, MD/PhD Candidate at Northwestern University Feinberg School of Medicine, Northwestern Medicine for a conversation on how Dell Technologies and Northwestern Medicine are leading the charge in revolutionizing patient care through life-saving artificial intelligence innovations.
Their discussion covers:
- Exploring generative AI vision and use cases in patient care
- Why The Dell AI Factory is the best solution for Northwestern Medicine’s AI needs
- Outcomes and impacts of Northwestern Medicine’s AI Factory initiatives
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TRANSCRIPT
Patrick Moorhead: The Six Five is On The Road in Las Vegas, Nevada. It is Dell Technologies World 2024. Dan, what an event. It’s pretty much AI, AI, AI. We just got out of the keynote with Jensen Michael and ServiceNow CEO. It has been crazy action here.
Daniel Newman: Yeah. It’s a big event for Dell Technologies. We’ve seen the ascent that the company has been on in the AI opportunity has presented itself, and it seems they’ve really seized the market. And here we are back in Las Vegas, a decade after the first time that you and I sat in these chairs in the Dell Broadcast Village. Couldn’t be more excited to be here, Pat, and excited for the partnership that we have here between Dell Technologies and Six Five Media.
Patrick Moorhead: Yeah. Dan, in The Six Five, we always talk about the grand purifier, is when we sit with a tech vendor and a customer. And we just happen to have one of Dell Tech’s incredible customers from Northwestern Medicine to talk about how the two companies are working together. So Jon and Jon, welcome to The Six Five.
Jon Siegal: Thank you so much. It’s a pleasure to be here.
Patrick Moorhead: Absolutely.
Jonathan Huang: Great to be here.
Daniel Newman: It is great to have you both. Like Pat said, we always say it’s interesting as analysts what we prescribe as good technology and value often translates to buying decisions. Customers, those that procure, build and partner with companies like Northwestern Medicine, Jon, are often seen as the best example of what can help drive a peer or another in your industry to make a decision, because you take some of the risk out. But you have some really significant projects underway and some initiatives and some proof of concept over at Northwestern. I read up on it a little bit, Jon. Talk a little bit about the vision and the use cases that you’re developing around Northwestern and of course the partnership with Dell and how that’s evolving.
Jonathan Huang: Absolutely. So at Northwestern, we’re a large healthcare system based in Chicago. And being in healthcare we’re primarily focused on making healthcare better. Better for patients, better for physicians and clinicians of all kinds. And fundamentally, I’m part of the Research and Development Team at Northwestern. We focus on using technology in a way that’s innovative, yet clinically grounded. So, we focus on finding real clinical problems that clinicians face in their daily practice and developing new tools, using new technologies for clinicians to tackle these.
So, some of the examples of these are, for example, new visualizations for medical data, things like colonoscopy, transforming videos into 3D visualizations to better detect cancer. Things like predictive modeling in maternal health, seeing if a mother will need a C-section before that actually happens. And making documentation better using generative AI, using digital twin large language models trained on electronic health records to predict patient events in the future based on past medical care. As well as using multimodal models that can translate radiological imaging like X-rays into reports that radiologists can use to continue their care.
Patrick Moorhead: So, what were some of the joint challenges that you guys found in achieving these use cases? Maybe Jonathan, I’ll send that one over to you.
Jon Siegal: Yeah, sure. I’ll say, so first of all, Northwestern Medicine is a customer, but also a partner in many ways. Because we started this collaboration, I’ll call it, about a year ago, where we actually, Northwestern told us about these use cases. We brought them into our AI innovation lab, right near outside of Austin, Texas. And really that’s where we did a lot of the testing and the benchmarking to figure out, for example, how do we help right size the configurations before they actually deploy it at Northwestern.
And so, we went through a lot of different things in terms of looking at what’s HIPAA-compliant, trying to figure out, again, the right size of the configuration to make sure that it’s cost optimized for their needs, and also make sure that it really meets their privacy and security needs as well. Because that was a big thing as well that we found in this partnership was, patient data doesn’t get more important than that. We had to make sure that it was secure and we make sure that we lock that down before they actually implement it.
Patrick Moorhead: That’s good.
Daniel Newman: So, when you were in that selection process though, you ultimately landed, Jon, on the Dell AI factory.
Jon Siegal: Right.
Daniel Newman: Double-click a little bit about that. Because I imagine in this particular era, you had a large number of opportunities, lots of vendors. Northwestern is a prestigious, I grew up in the Chicago area, but anywhere in the world, Northwestern is known, it’s reputed. And of course healthcare is one of those applications that the whole world is excited to see how AI can shift and make a big difference. How did you land? Why did you pick?
Jonathan Huang: Yeah. Well, from the very beginning when we started fleshing out this collaboration, we had the privilege of meeting with the AI innovation team at Dell. And immediately we were just so impressed that we were talking with engineers wanting to solve real problems, and we have plenty of real problems to bring to the table as well. Yeah. We flushed out some collaborations. We came down to Austin to see the lab in person, see all the hardware in all its glory. And we really benchmarked the hardware that we ended up going with, finding out, through all the range of potential AI acceleration hardware out there, what might fit the healthcare use case best.
And in healthcare, that’s an extensive range of data we need to work with. So we’re working with unstructured text, we’re working with X-rays, we’re working with CTs, MRIs, huge amounts of imaging data. And this collaboration with the Dell AI lab helped us to flesh out the benefits of this increased GPU acceleration at scale, at the healthcare scale that we fundamentally work with every day. And we also worked a lot on fleshing out high-performance compute setups, which it’s so important to keep in mind the privacy concerns that surround our data usage, especially when we’re training AI models, whether it’s on the cloud or on-prem.
Patrick Moorhead: So, Jon, what were some of the nuts and bolts of this lab that you guys put together? Were we talking PowerEdge? The MACs here? I heard a lot of excitement. Jensen was pretty excited about 72 Blackwell GPUs in a rack-
Jonathan Huang: Yes.
Patrick Moorhead: All water cooled. You probably don’t need that much horsepower, but what are some of the nuts and the bolts of the lab?
Jon Siegal: So, this lab is literally, the AI innovation lab, is where we provide the latest access to the latest and greatest technologies that you heard on stage today. And so that’s why it was a great benefit at the time too. So, you’ve got our XC 9680s based on, of course, NVIDIA, and we have everything there. So we have our GPUs are pretty data-hungry, so we also have PowerScale in there. We have our high-speed networking. So, you literally have, this is state-of-the-art latest and greatest. And it’s not just the technologies individually, but as you know, it’s how do we integrate them and make them easier to deploy and easier to manage, and easier to secure.
Patrick Moorhead: Was Dell’s services a part this as well?
Jon Siegal: Services plays a huge role here as well, both in the front end, in terms of understanding the use cases, but then also in deploying the configuration as well.
Patrick Moorhead: That’s great.
Jon Siegal: Yeah.
Daniel Newman: So, Jon, as you evaluate and you continue to make decisions about investment strategy, about next-generation implementations and the future of what you want to build at Northwestern, how are you sort of evaluating the outcomes of this? How fast is it moving? How fast do you see it moving? What are going to be the things that you’re going to say, “Yes. Let’s put our foot on the gas and let’s keep going and keep investing”?
Jonathan Huang: So, the thing with technology in healthcare is there’s a track record of technology actually, making care more complicated or difficult. It means a doctor’s typing at a computer instead of talking to you as a patient. And that’s what we want to avoid. We want technology to augment clinician intelligence and make workflows easier so that patients can spend more time talking with their clinicians. And so, in terms of outcomes, one of our models that we’ve studied the most so far is this multimodal large language model for interpreting radiology images. So, we’ve had it live across our health system.
It reads every single x-ray. And we’ve seen that when radiologists use this tool as a draft report, the AI report is completely generated from scratch, they are able to document as much as 40% more efficiently, in the research studies we’ve undertaken. And that’s a huge benefit. It means radiologists are spending more time talking with colleagues. It means patients are waiting less long for imaging results and ultimately it’s bringing patients and doctors closer together at the table with AI and technology serving in the background to streamline these processes.
Patrick Moorhead: So, I have to ask, how are you dealing with all the regulatory issues that come with medicine and there’s this brilliance of AI and the potential, and then there’s things like HIPAA, and the new ways that data are being used. How are you thinking about that?
Jonathan Huang: Yeah. It’s an important question for healthcare systems to handle. And we’re always very careful to make sure that this clinician, AI collaboration is the model that we move forward with. We’re not replacing radiologists, we’re not fundamentally changing how care is delivered. We’re making that more efficient with AI. And so that means there’s always a clinician who is reviewing the results of the models and it’s always fitting into the workflows that patients, and doctors are used to. In terms of HIPAA, we are making sure that all of the software infrastructure from model training and development to inference, it’s all done HIPAA-compliant and within the standard healthcare ecosystem.
Daniel Newman: Right. Well, Jon and Jon, I want to thank you both so much for taking a little time. I know Dell Technologies world has a lot of events and sessions going on. It’s been a joy, Pat, just from the time we got here, listening to all of the progress. And of course as a couple of analysts, we’re pretty interested in what’s going on in AI and of course, Jon, how it’s being applied at places like Feinberg at Northwestern University. Thanks both for spending some time.
Jon Siegal: Thanks for having us.
Jonathan Huang: Thank you so much.
Jon Siegal: It’s fun to geek out on these actual use cases. We’ve come so far in one year. A year ago. We didn’t have all these real examples and now it’s so fun to dig in.
Daniel Newman: Just wait a year into the future.
Jon Siegal: Imagine what’s next.
Daniel Newman: All right, everyone. Thanks so much for joining us here. The Six Five is On the Road at Dell Technologies World 2024 in Las Vegas, Nevada. Subscribe. Join us for all of our sessions here. If you’re here with us live, we appreciate you tuning in. If you’re listening to us later, we appreciate that too. See you soon.
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