All of that has come together in one unified operating model where the intelligence has been built at the core and that's why we believe as a company we are ahead of the game when it comes down to providing these solutions to enterprises of that unification.
The 65 is live here at HPE Discover 2026 in Las Vegas. What an event it's been so far. We've had a few great keynotes. We've had a number of announcements. And of course, we are in the middle of a boom across AI, networking, security, compute, and so much more. And I couldn't think of a better person to have here with me today than Antonio Neri. Antonio, great to have you. Welcome back to the show.
Thank you. Thank you for having me. And thank you for joining us at HPE Discover this very, very critical week. I would say a fun week.
It's been a fun week. It's been a good week. I know you're a World Cup fan. So you even got a little reward. I heard you got to watch the great Lionel Messi score a hat-trick right in between probably your three or four dinners last night. But what a start that's been by the way.
Well, it was a great day. Obviously, we had the keynote early in the morning and we had record attendance. It was unbelievable to see that room. It was almost two football fields. Think about how wide that room was. More than 9,000 people came to see it. But, you know, wrapping the day with my fellow compatriots, which I know because I met him a couple of times. It's remarkable to see what he's doing. It's just the best ever.
It's the best in the world. I remember four years ago sitting there watching that final. Do you think they could do it again?
Look, it's hard to be back to back. But if there is one that can do something that nobody ever imagined, it's Leo Messi. But I believe it's going to be hard because this World Cup has one more extra game to play.
But look, the Argentinian team look good. They sure did.
And if he's on form, it's going to be hard to beat him.
All right, we got to talk some tech. I could ramble on about, you know, I'm a passionate fan myself, so it's just like I knew you'd be excited, so I just want to dwell on that a little bit. But, it's been a, first of all, you had to one up a pretty big keynote last year because you guys did the Spear experience last time. And so, but I agree with you, the room, the energy. I mean, it's been just a tremendous year for HPE. I track you both as an industry side and I track you very closely on the securities and equity side, and it's been, you know, just want to congratulate you. The market's catching up.
We're still undervalued so we're clear, but it's slowly catching up to our vision and strategy and strong execution we had in the last four quarters and honestly I think the thesis of the Juniper acquisition is playing out now and people are recognizing that. I think being able to pull forward a couple years was very well received. The, I call it the god candle that you got in response, you know, and well deserved because it's been a long time that I think it's been underappreciated. So, but more to go as you said. So, let's talk a little bit about the customer side. You're here at an event. The customers are all around you, customers, partners. AI is in this, it's I always say it's still really early. I see these interviews on CNBC where they're like, "Oh, we're in the third inning." I got on CNBC and I said, "I think we're still in the parking lot and we're still cooking a hot dog and having a beer in the pregame." Like, I think it's extremely early.
We're tailgating. That's what we're doing.
Yeah, we're tailgating. That's actually what I said. I said, "We're tailgating." And people think you're crazy. I'm like, "I don't think people realize how big this actually is." But you have the front row seat to customers that are turning AI into productivity and efficiencies. I mean, what are you seeing in those companies right now that are getting there early and that are getting results at the very beginning of this AI boom?
And you have a lot of that here on the show floor. I mean, we have seven acres of technology on display and the story is being told by customers which is what I love. One thing is you standing up there and sharing your point of view. One thing is a customer telling how they're using this technology for their advantage. And look, I spent more than 50% of my time talking to customers and partners. And when I think about the adoption of AI, it really hit an inflection point six months ago with the advancement we see with Agentic AI. And that's why we spend a lot of time around the Agentic Enterprise. And look, we see it ourselves. We have 200 use cases under a lifecycle process and 250 already in deployment. The value of the agentic AI is really bringing together AI in a process-oriented approach where you hyper automate using AI that workflow and we see it across all the functions: finance, HR, legal, supply chain services, and then of course in engineering you see the value of this technology to assist coding and application development. So clearly enterprises are seeing the value and then there is one metric I watch all the time: the growth in inferencing. Because the moment that inflection point continues to grow, inferencing is going to be the largest part of what we're going to see by the end of the decade and that's why I'm very encouraged about the adoption but most importantly I'm encouraged about what we have to offer. That's why our AI factory for enterprise is so critical.
And it's interesting because that inflection that you were watching created a boom for a number of parts of the infrastructure stack that I think a lot of people somewhat, you know, we talked about what was underappreciated. This entire CPU boom which you were well positioned to benefit from. I mean a year ago people, you know, there was a story it's all GPU, XPU, there is no more future, CPUs are this diminishing thing and now we're finding that people are buying 2-year-old CPUs just to get as much capacity as possible. Memory, I mean we knew memory was a big thing for training but what inferencing has done and now agents have done for the need of memory and then of course you being a full infrastructure stack all the way down the supply, you got storage, you got to get things close to memory because you can't put enough memory. And so what I'm saying is it's really created this grab.
Well, I mean look, I understand the hype around accelerated computing which of course was the GPU progress we saw tremendous progress in the last two years but everything else in the stack has to catch up. And the next layer of that stack is memory. And to me, storage is an extension of memory. That's why you see now things like KV cache and other things growing very rapidly. But ultimately, the biggest bottleneck is networking.
I was going to ask you, but you went first. So go ahead.
Yeah. Well, I mean, look, the networking is the core bottleneck to get the maximum amount of productivity for this accelerated computing. And so whether it's CPU now for inferencing and we made a number of announcements together with Nvidia or whether it's alternative training stacks like AMD Helios, and the need to really drive the maximum productivity for this amount of capex because we believe by the end of the decade we're going to basically have 250 gigawatts of compute power. You don't want any GPU or CPU to be idle. And that's why our thesis on networking is growing up very, very rapidly because networks for AI have to catch up to the other demands. And I believe with Juniper we have the best products to compete in that market.
And it's worth putting an exclamation point on first of all Juniper being designed inside Helios. We have AMD potentially seeing double digit market share. So for a long time and you have a great partnership with Nvidia, but that size when you're talking about 250 gigawatts and you talk about 50 maybe even 80 billion per gigawatt you look at what that opportunity means.
And then networking represents between 15 and 20% of that.
So every gigawatt let's say 60 billion just take a middle of the road.
That's a 10 billion networking opportunity per gigawatt.
And so Juniper brings all the key elements to build this data center. Scale up...
Which you talked about being inside the Helio stack. Scale out because you now need to connect massive amount of GPUs across hundreds if not thousands of racks and then scale across because you have to drive the data center interconnect. Juniper brings all elements of that thesis to bear with the latest time-to-market technology, fully automated solutions with AI.
Yeah. And then obviously we have the on-ramp solutions as well which is core to how we use these models. But as part of your story, you were very thoughtful about leading with network security and of course you have always had a big compute business, right? But you know, we talked a little offline about how it sort of took the market a while to catch up, but the fact that you're in the scale up product that Helios product that AMD is building, it does give you now a much bigger entree because you've been very margin sensitive. You've focused very much and said we're going to grow enterprise. We're going to grow sovereign. We're going to work where we can deliver compute and make the kind of margins that we have promised to our investors and that allow us to run the business the way you want to run the business. But some people thought maybe that meant you weren't getting exposure to that 250 gigawatts.
No, we have exposure. It's just intentionally we select what to play because look, in any customer segments the one thing I try to reinforce all the time is you need to think about the use case: training versus inferencing. And then you need to think about customer segmentation underneath. Obviously hyperscalers, service providers and model builders is one segment. Sovereign is another segment and enterprise is another segment. In any case, in any of these whether it's training or inference or whether it's segment one, two or three, we lead with networking. We have it all. That's where we can get tremendous value for our shareholders and we bring the right solution to our customers. Then for compute we prioritize the full stack integration with Nvidia for enterprise our AI factory including software because there the value proposition is time to value.
