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Hillery Hunter

CTO, IBM Infrastructure

IBM

Data-powered AI: How IBM and Nvidia are shaping the future of enterprise and healthcare

Since data is the fuel that powers artificial intelligence, data-powered AI has become critical in the enterprise world.As a result, the connection between data and AI is crucial, as it reshapes how businesses and industries function by driving smarter decision-making, automation, personalization and a stronger focus on the customer, according to Hillery Hunter (pictured), chief technology officer of IBM infrastructure at IBM Corp.IBM’s Hillery Hunter talks to theCUBE about the transorfamtive impact of data-powered AI.“This is one of my favorite topics, because when you think about what an enterprise does, one of the most important functions they have is to steward their data,” she said

play_circle_outline Medical applications of AI for faster outcomes

play_circle_outline Trust in AI for regulated industries and customer interactions

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Hillery Hunter, IBM

Hillery Hunter

CTO, IBM Infrastructure IBM

In this insightful video, Hillery Hunter, IBM's Chief Technology Officer, joins us to delve into the multifaceted relationship between AI and data. Broadcast live from Nvidia GTC '25 in San Jose, California, this discussion hosted on theCUBE, with insights from theCUBE Research, explores significant advancements and trends in technology.

Hillery Hunter brings extensive knowledge and experience in technology, focusing on how AI and data intersect within enterprise environments. Throughout the interview, Hunter explores key themes such as the importanc... Read more

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What are some of the medical applications that IBM is focusing on in collaboration with hospital organizations? add

What factors are important when leveraging AI in a regulated industry with a large customer base, such as NatWest? add

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Hillery Hunter, IBM

Savannah Peterson

>> Good afternoon, IBM fans, and welcome back to NVIDIA GTC here in San Jose, California. My name's Savannah Peterson. You're watching our exclusive coverage here on theCUBE. Very excited for our next segment because we're going to be talking about something that no one's been talking about at the show, AI and data. Please welcome Hillery from IBM. Hillery, thank you for coming on so last minute, also for bringing the awesome blazer vibes. I feel like we're having a blazer moment right now on theCUBE.

>> We are, absolutely. Absolutely. We need some

>> more blazers on the show.

Savannah Peterson

>> Some more classy quality, stylish blazers. It's not all Blue Brooks Brothers blazers, unlike most of the folks here are wearing. Anyway, speaking of fashion, let's talk about data and AI. A big relationship between data and AI. Obviously a huge conversation here. This is something that you sit at the epicenter of. What are some of the trends, conversations that you're having? Talk to us.

>> Yeah, this is one of my favorite topics because when you think about what an enterprise does, one of the most important functions they have is to steward their data. These are companies that are interfacing with us as consumers. It's companies like FISA that we had on stage with us yesterday. Very personal, important information that they're stewarding banks, retail stores, all of that kind of stuff.

>> So sensitive. - So when you think about the enterprise

>> data is the core asset that they have.

Savannah Peterson

>> It's the core responsibility that they have and regulators have opinions even on that data and where it should be sovereign and things like that. And so we like to say that AI and data, or AI and hybrid cloud are two sides of the same coin in the sense that if you acknowledge where your data is, where your IT is, where your customers are, that's across a pretty big landscape. It spans from public clouds to on-premises, traditional IT even like mainframe and out to the edge where a lot of times we interface with a company as a customer. And so that data conversation being multi- dimensional means your cloud conversation is multi- dimensional, means your AI conversation is multidimensional, multi-location. So that's I think a really important topic we don't talk enough about.

Savannah Peterson

>> No, I think you're bringing up a really good point. We got to bring the AI to the data. We got to make sure that we're both on-prem for that highly secure stuff that's going on. And we can be at the edge for use cases, even like Brianna's marathon situation where she's tracking her different shoes. It's not all just tech devices. It's all the little pieces of this that are going to integrate into our personal lives.

>> Absolutely. Well, and I think it's interesting because when you look at this conversation fundamentally, historically, we've understood analytics, big data and all of that. With the current generation of generative AI, there's the opportunity to create things a lot faster. I would say that's the most remarkable change that's happened, is the speed at which you can create a new tool, the speed at which you can create a new insight. It's just at a totally different pace. And so you can talk about the big data era, whether or not we fulfilled those promises or other things like that, but I think a lot more enterprises are actually seeing the fruition of the data analytics and those capabilities in that context of being able to not just make a which AI decision, but how are you going to do the AI, what's that platform that you're going to use to create the AI that can be deployed where all your IT is and where all your customers are?

Savannah Peterson

>> Are there any of those use cases, and this is maybe taken off your IBM hacks, I'm sure you see a lot of different things, are there any of those use cases that get you really personally excited?

>> Yeah, there's a lot here at the conference about medical applications. I think we're honestly from an IBM perspective as well, working with different hospital organizations that are trying to bring AI-based insights to their customers, get faster turnaround time in how they get even diagnostics and other things out to clients. I personally then on a personal level think that's really exciting when we're seeing technologies where the bringing the AI to the data, bringing the AI to the applications means that we can get faster outcomes for people even in medical kind of contexts. Right? That's an incredibly exciting application in the technology.

Savannah Peterson

>> I can't think of an application where real- time information could be more powerful than when you're in a triage situation or fighting cancer or whatever's going on.

>> Absolutely. There's a hospital we work with

>> that's been doing AI-based acceleration on our power platforms, and they've gone from a three- day turnaround on diagnostics to a one-day, which is basically overnight as a patient. That's a huge difference, waiting three days for results versus getting it overnight.

Savannah Peterson

>> Oh yeah. The cognitive load and anxiety in that particular moment alone is enough.

>> Absolutely. It's a very palpable outcome,

>> so I personally find those kinds of things most exciting.

Savannah Peterson

>> I think it's really exciting, and I think a lot of times people talk about how certain technologies are going to change the world or save lives. To this exact use case I think AI will save lives, and I think that IBM is going to be one of the partners powering that for our future, so I'm grateful for all y'all do, quite frankly. I'm also curious, big week of announcements. I think just about every company we were joking had a press release that came out at one PM today the moment the world heard about AI this year. What can we expect coming out of IBM and out of your team looking forward now that we're here at GTC and all the announcements?

>> Just hit a couple of the highlights from the press release, I won't promise to cover every single word in it from memory here, but to hit a couple of-

>> I'm holding you accountable to every word.

>> Yes, exactly. You're going to go back and check, right?

Savannah Peterson

>> Just to kind of hit a couple of the highlights, content- aware storage is something that we're really excited about that we announced that coming availability today, the interaction that with the NVIDIA stack as well, but really that solves a key problem. You notice a lot of times when you use AI as a consumer, it's not the best place, for example, to get the news from what happened in the stock market the last hour or so. There tends to be a little bit of a lag in the freshness. What we're accomplishing with content-aware storage is to be able to make the AI fresh and fully up-to-date. That rag pattern, that vector index-

>> That's a really big deal. - ...

>> is re-tuned at the instant the storage is updated.

Savannah Peterson

>> So if the data's there, the AI is integrating that into the search and the semantic capabilities of the system. And so solving that problem is something I think is really, really key and that we're excited about. We also touched in the announcement about integration of some of the NVIDIA NIMS capability into our WatsonX family.

Savannah Peterson

>> Yeah. Super exciting. - And our consulting capabilities,

>> they're leveraging some of NVIDIA AI enterprise capabilities, which adds to some things that they've been doing, for example, in digital twins, within manufacturing, and other things that have been happening that omniverse space with NVIDIA. So yeah, really great announcements. Also, our H200 GPUs coming available in IBM Cloud. I think I've now managed to touch on most of the key aspects.

>> You've done a really good job. I'm running through my checklist in my brain and you can get a

Savannah Peterson

>> gold star today on your homework. You've really nailed it, Hillery.

>> So we had stuff, everything from consulting

Savannah Peterson

>> to our software, our infrastructure, storage cloud, etc. And so really a broad set of things that we're really excited to be announcing today.

Savannah Peterson

>> Yes. I had the pleasure of working with your team at MWC, one of the things that I noticed there is it feels like there's IBM magic fairy dust kind of throughout the whole building. I sense that a little bit here as well. If you could, say, wave a magic wand and all of a sudden your community all knew about the exciting innovation that's happening at IBM and with your partners, what do you wish you could tell them all at once?

Savannah Peterson

>> Yeah, I think that one of the major things for me is where I started in the sense of this notion that AI and hybrid cloud and data are really more of a combined conversation than folks often understand. And if you look at our partnerships across this show floor, it's been exciting to see some of our main and strategic partners in the generative AI space, companies like Dell, companies like Lenovo, and then our partners in the software and the SaaS space, Salesforce, all those other kind of things.

>> All your buddies are here.

>> All of that comes together from an IBM perspective

Savannah Peterson

>> because we have a platform that can deploy on the basis of the Red Hat capabilities. They're also here, but deploy the Red Hat capabilities, everyone understands that works from on premises out to the edge, etc. Use that as the basis for then building your AI and use IBM software capabilities to create trusted AI and continue to then be able to monitor those through WatsonX governance and such as you go out to the field. So having that unique situation that we can be talking about AI as a platform conversation, scalability of AI, affordability of AI from those dimensions with our granite models being on the smaller kind of enterprise customized side, I think it's just a perspective that's very unique on this floor here, so we're really excited to be here talking about it.

Savannah Peterson

>> I think that was beautifully summarized. You mentioned trust. Last question for you, trusted AI, how critical is that in the conversations that you're having right now with your customers?

>> Well, when you talk about being a regulated industry, I think there's probably a lot of stewardship and data, as we talked about at the beginning, and then there's the trust of your customers. You want to make sure that they're going to come along with you in that journey. We worked with companies like NatWest that have 18 million, I think is number of customers.

Savannah Peterson

>> Wow. - That's a very large trust base, right?

>> Yeah, jeez. - And so when leveraging AI to help

>> that many people in their customer interactions with you,

Savannah Peterson

>> you want to make sure that you trust it. And so for us, it's a journey that starts from hate, abuse and profanity scrubbing of input data that's used to train our models. And it extends out then into the governance, which is not just of our models, but of other models. And as we announced today, including models that are being consumed from NIMS, from NVIDIA. And so that whole span for us, trust is a systematic and systemic conversation because it's absolutely critical to the AI decisions that enterprises have to make when they're servicing millions and tens of millions of customers.

Savannah Peterson

>> Absolutely. Well, for what it's worth, I trust, y'all.

>> Thank you. - Hillery, thank you so much

Savannah Peterson

>> for taking the time and for bringing the blazer game here. We really appreciate it.

>> Thanks so much. - And thank all of you

Savannah Peterson

>> for tuning into our coverage here at NVIDIA GTC in San Jose, California. My name's Savannah Peterson. You're watching theCUBE, the leading source for enterprise tech news.