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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Antonio Niir of HPE

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Speaker 1: their CEO, and I'm going to put up here for

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Speaker 1: those of you on YouTube you can see one of

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Speaker 1: my most beloved Hewlett and Packard artifacts. This is the

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Speaker 1: twelve ce that got me into this chair with the

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Speaker 1: obligatory CFA stick around it. And Sweeney's got their killer app.

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Speaker 1: Antonio Naeri HP twelve c app on his Apple iPhone.

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Speaker 1: Mister Nay, honored to have you with us today. I

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Speaker 1: want to carry on from Chris Miller's wonderful Chip Wars,

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Speaker 1: the battle of say Silicon Graphics coming into HPE, and

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Speaker 1: all of this hot air about AI. You've got HPE,

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Speaker 1: Green Lake. How are you going to join in video?

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Speaker 1: In Microsoft? You're good competitors in the excitement of AI.

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Speaker 1: What's the path over the next two years?

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Speaker 2: Well, good one and Tom and Paul, thanks for having

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Speaker 2: me today. And obviously we are living an massive inflection

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Speaker 2: point where the AI, where I think you know, is

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Speaker 2: the most revolution of technology or lifetime, is going to

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Speaker 2: change everything the way we work with where we live.

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Speaker 2: And when you think about that opportunity, I think about

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Speaker 2: the opportunity to change everything from a technology standpoint, but

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Speaker 2: also from the business standpoint, and so US with HP

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Speaker 2: green Lake, we have a unique opportunity to democratize these

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Speaker 2: AI technology to everyone because today AI has been only

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Speaker 2: used for the large institution of the government and academia.

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Speaker 2: But going forward, enterprise have to adosg those technology.

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Speaker 1: I like said, I get the AI idea within computer science,

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Speaker 1: like what you've done in your leadership over the years

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Speaker 1: at Hewlett Packard. But what I don't understand, and I

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Speaker 1: think there's a lot of doubters when you say, HPE

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Speaker 1: Greenlake you're going to unleash the potential of your people.

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Speaker 1: What does it actually mean two years.

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Speaker 2: Out, Well, it means you know a significant amount of

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Speaker 2: automation and business inside you can gather through the data

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Speaker 2: and the application on these technologies. We see that across

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Speaker 2: multiple vectors or industries, the robotics in manufacturing, through finding

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Speaker 2: cures for major diseases. We have some amazing use cases

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Speaker 2: we're working today with AI finding an accelerating a queue

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Speaker 2: for Alzheimer's and dementia. You know, one of the things

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Speaker 2: we're doing is trying to model entirely neural neurological brain

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Speaker 2: to find what the protein is that causing those issues,

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Speaker 2: but also better climate research and forecasting. But when you

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Speaker 2: bring it to enterprise, it's all about productivity, you know,

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Speaker 2: in the legal space and the finance space, in the

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Speaker 2: operation space, and this large language model accelerates that set

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Speaker 2: of capabilities, Antonio.

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Speaker 3: What I think a lot of investors are trying to

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Speaker 3: figure out here in these earls of AI is how

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Speaker 3: much of this AI spending in terms of capital expenditures

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Speaker 3: is incremental or how much of it is taken away

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Speaker 3: from other tech budgets. Maybe it budgets for example. What's

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Speaker 3: your experience so far?

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Speaker 2: Yeah, Paula, I will say AI has a life cycle

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Speaker 2: from training to fine tune into infanancy. Most of the

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Speaker 2: action in the last five quarters or so since we

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Speaker 2: have going through this hype has been on the training side.

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Speaker 2: These are companies, unique companies that are building large language

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Speaker 2: models now exceeding a trillion parameters, if you will, and

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Speaker 2: they need a lot of compute power right to keep

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Speaker 2: training and retraining the model to reduce the cost of

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Speaker 2: those models, but also to make it more accurate so

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Speaker 2: you can trust it. Enterprises are in the early stages,

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Speaker 2: and I don't think they're going to build the models itself.

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Speaker 2: They're going to take a model, They're going to give

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Speaker 2: context to the model with their data in a location

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Speaker 2: where they can afford. Honestly, I think that's the why

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Speaker 2: reason why greleg is important. In a small you only

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Speaker 2: pay for what you consume versus all laying tens of

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Speaker 2: millions of dollars of capex upfront, and then the value

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Speaker 2: comes from the infancy where you deploy the model, where

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Speaker 2: the data is generated so you can actually deliver the outcome,

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Speaker 2: whether it is in all processing video surveillance, or whether

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Speaker 2: it is you know, in the manufacturing floor to automate processes.

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Speaker 2: This is where we are in the early stages, and

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Speaker 2: I think you know that's gonna you know, it's going

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Speaker 2: to be one of the biggest growth in twenty four

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Speaker 2: and twenty five.

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Speaker 3: Antonio, you just reported earnings. You took your four year

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Speaker 3: guidance down. That was in part due to the networking

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Speaker 3: business leading to that miss, and that was one of

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Speaker 3: your better performing businesses last year. What's changed for you

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Speaker 3: in that business?

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Speaker 2: You know, it's a little bit the success we have had,

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Speaker 2: right so, in the last two years, we we raised

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Speaker 2: our revenues in the networking business by two billion dollars.

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Speaker 2: We took share from Cisco and we have an amazing

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Speaker 2: portfolio and just came back from Moral Congress. You can

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Speaker 2: see the use cases of inferencing at the edge of

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Speaker 2: the network, for example the monetization of five G and

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Speaker 2: private five G. But what's going on now? Customers are

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Speaker 2: digesting the last two years purchases were very significant. We

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Speaker 2: grew over forty percent a year over year, and so

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Speaker 2: this goes back. But this is why the merger with

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Speaker 2: Juniper in the networking space is going to be a

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Speaker 2: terrific addition to our portfolio and the creation for us

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Speaker 2: going forward.

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Speaker 1: We have time, sir for one more question. I've just

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Speaker 1: got to go back and folks, full disclosures. I'm going

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Speaker 1: to redo it as a book of the summer chip Wars.

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Speaker 1: Chris Miller's fabulous book. Antonio Seymour Kray was with controlled

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Speaker 1: data and all that, and he made a wonder computer

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Speaker 1: of my childhood out of Wisconsin and Minnesota. After three mergers,

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Speaker 1: Silicon Graphics and all, Hewlett Packard Enterprise, which people think

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Speaker 1: is stodgy, picks up one of the magic names. In

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Speaker 1: twenty nineteen in computers, what are you going to do

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Speaker 1: with Cray excess scale.

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Speaker 2: Well, I mean amazing company, Amazing companies that changed the

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Speaker 2: landscaping computing. Both now Cray and SGI Silicon Graphic are

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Speaker 2: part of our server business delivering these amazing systems. We

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Speaker 2: call it supercomputing. Yeah, to give a sense. Those systems

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Speaker 2: today are deploying Department of Energy and have many coming online.

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Speaker 2: And so our goal is to use the system to

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Speaker 2: solve some of the biggest challenges, to design better engines,

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Speaker 2: more sustainable solutions in the life science and climate research, sustainability.

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Speaker 2: So this is why we made the investment. I think

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Speaker 2: I would say, Tom, what people misunderstood when we bought Cray.

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Speaker 2: We bought a company that had silicon and software, and

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Speaker 2: we're able to turn that into a capability that solved

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Speaker 2: these charges. That's why we are excited about it.

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Speaker 1: We're at a time and Tony and are you got

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Speaker 1: to come to New York. You got to come in

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Speaker 1: our studio. I need to show you my HP twelve

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Speaker 1: C mister Neary with HPE, the wonderful follow on of

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Speaker 1: all the work at Hewlett Packard