It is with great excitement that we announce NVIDIA AI Computing by HPE to accelerate the generative AI industrial revolution. And here to tell us more, I am very pleased to welcome out a man and a friend who needs no introduction: the Founder and CEO of NVIDIA, a driving force of innovation that's changing the world, Jensen Huang.
Did somebody say partner?
Yes. Look at this.
Hey, everybody.
It is amazing.
Go HPE.
Go NVIDIA.
Isn't this amazing, Jensen?
Yeah, it's great.
Yeah.
Nice living room. Did you say living room?
It's a living room. It's my personal living room.
Okay. I like it.
Yeah. We may play something later.
Okay.
Something more interesting. But listen, Jensen.
All day long, you got all these people staring at you. That's a good way to live.
I couldn't believe, I mean, listen, we have people, you know, kind of stuck in the bridge, at the bridge, right? And they were telling me, you know, we need to wait another 5 minutes or so. I said, okay, let's wait. We want the house full. Look, it's full. In fact, there were supposed to be not a lot of people on the side because that kind of is not the best view. But boy, we have every seat pretty much taken. It's amazing.
Well, they're here to see you.
Yeah.
Yeah, you guys are doing a great job.
Yeah, thank you. Thank you for being here. It means a lot to us, but honestly, it means a lot to them, our customers and partners. You know, listen, we just announced the NVIDIA Computing by HPE. And obviously, our focus is to capitalize this amazing opportunity, which is AI. But let's talk a little bit about what it means for enterprises. What is for them at the end of the day?
Well, when you take a step back, AI, generative AI, what's going on in the industry today hasn't happened in 60 years. This is the greatest fundamental computing platform transformation in 60 years. From general-purpose computing to accelerated computing, from processing on CPUs to processing on CPUs plus GPUs, from instructions, engineered instructions to now large language models that are trained on data, from instruction-driven computing to now intention-driven computing. Every single layer of the computing stack has been transformed, as we both know very deeply well. And the type of applications that are now possible to write and develop are completely new. And the way you develop the application is completely new. And so every single layer of the computing stack is going through a transition. And that's why, from an industrial perspective, it's such a big deal.
On the other hand, what's really amazing is a whole new industry has emerged. What used to be the IT industry, and we've seen the creation of a $3 trillion industry, which is really driven by the last industrial revolution where we invented the idea as an industry of mass-producing software. Software is invisible. You can copy as many versions as you like. And yet, we've created a $3 trillion industry on that idea. Now we have a new idea. And this new idea is quite extraordinary in the sense that what is being manufactured is still invisible, but it's embedded with intelligence. We call it tokens. And so what is really extraordinary is the IT industry and the work that we're doing together, on the one hand, can address enterprise computing, GPU clouds, sovereign AI. But now we also have this new industry that's emerged called AI factories.
Exactly.
Where we're producing intelligence in high volume. And so our industry has been transformed really, really profoundly. And we're at the beginning of that.
But Jensen, I mean, two years ago, we were not talking about this. But you and I have many conversations over the years, and you have this amazing conviction that there is a better way. And it's not just about technology. It's about transforming the business. And I think, I think the power of this AI revolution, that's why we call it the generative AI industrial revolution, as you just talked about it, is transforming the business. It's transforming society. So when you put yourself in their shoes as a customer, what do they need to think through to be successful as an enterprise? What are the key ingredients they need to think about it?
Well, theoretically, what AI needs are three components. Of course, the model, the revolutionary large language model and generative AI models. Second, computing to go process that. But very importantly, something that all of the enterprises in the world possess, and I heard you say it earlier, and it's completely true, their most important asset. For companies, it's your most important asset. For countries and different regions, it's your natural resource. You need these three things. You need model technology, you need data, and you need compute. However, that's on a theoretical basis. What you need on a practical basis is you need a model stack, you need a data stack, and you need a computing stack. Each one of those stacks are incredibly complicated.
And so the work that we've done together is really about productizing and on a really massive and comprehensive way that our partnership is working together so that we could productize the model. We call them NVIDIA NIMs and the model stack. The data stack, which comes from NVIDIA AI Enterprise and the data processing, the vectorizing of your data, semantic embeddings, the retrieval and the deployment, we call that NVIDIA AI Enterprise, and the entire computing stack, which has all of the software that goes along with supercomputing technology. One of the reasons why this is built in the clouds today is because the stack is so complicated. Between our two companies, we've really turned these three stacks into deployable solutions that you can engage right away.
Yeah. So, you know, the NVIDIA AI Computing by HPE offerings and services, you know, one of the key elements, it will be available through our joint go-to-market strategy that really spans the sales, the channels. So here you have 1,500 of the most important channels and partner ecosystems as well. And we will provide training them, obviously. But also today, so you know, we're making an announcement that Deloitte, HCL, Infosys, TCS, and Wipro are coming along our journey. And that's really significant because at the core of this, they also need to transform the business. And obviously, there is a variety of workloads. And so when I think about that, you know, first is training and certification. So together with Jensen and and and his team, we are going to train the entire HPE sales force. We're going to show up in front of you as one company.
And when I think about that, there's thousands and thousands of people, thousands and thousands of people just on the specialization side, as well as on the presale side, which is a huge important role. And listen, when you engage HPE, you're going to be working with, you know, AI experts that have the skill to help you design together with our partner ecosystem, deploy and operate these amazing generative AI solutions. Together, we are making significant investments to train you as well and the services that you need across the lifecycle to turn this NVIDIA computing initiative a reality. So where do you have skill gaps? We have the experts to help you, ready to support. Second, we're also working with Jensen and his team to develop multi-levels of comprehensive and optimized solutions to deliver that amazing innovation.
And obviously, Jensen, you are on the forefront to keep announcing these amazing, you know, architectures. Obviously, we are now into, you know, the H family, but the Grace Hopper and now soon Blackwell and and the other ones, you know, Rubin and the like. So that's super important. But also at the same time, we also need to think about managing the lifecycle of these solutions. And that's why HPE has unique differentiation with HPE Financial Services, because ultimately, as these systems come to end of life, we can find the right, smarter IT lifecycle solutions so that we can help you create the capacity to invest in this amazing innovation, but also make sure we find the right use when that asset comes out of your environment. So Jensen, this is amazing because I'm super excited about this joint go-to-market.
But can you please elaborate, you know, these three elements we talk about, right? Because ultimately, this ends up on an integrated co-engineering solution we're going to announce today.
Yeah, these three stacks are incredibly complicated. First of all, you're sitting on a mountain of really valuable data. You want to fine-tune your proprietary model. We have a large collection of public, proprietary, and partnership models that we've created. And we take this entire complicated stack and we turn them into NVIDIA Inference Microservices, basically a model stack. This model stack is essentially an API. It's kind of like a chatbot, except we've integrated everything and made everything work. And it's now in essentially a giant container of hundreds of dependencies, incredible amounts of technology, but easy for you to use. You download it, you could fine-tune it, guardrail it, you can deploy it. And that microservice is now one of the stacks. The second stack that you have is your data stack. This data stack, you want to vectorize, bring semantic meaning to it.
So we have technologies for helping you do that. We call NIM. You could then take this data stack and connect it to your model stack. This way, your model stack becomes an intelligent AI that can interact with, chat with, retrieve information from your company's private data. Then the third thing is, of course, the entire computing stack. Between us and HPE, we will turn you into a world-class AI cloud, a world-class AI company. Then, of course, those three ingredients are fundamental to AI. But ultimately, you also need the expertise, the domain expertise. And this is where this network of partners connecting with all of this technology with a giant go-to-market, we can now bring AI to the world's enterprises for the very first time. This is a massive partnership and a really comprehensive solution that we can take to the market.
So it's a very big deal today.
And we appreciate the vote of trust and confidence in us because for us, obviously, partnering with the best has always been one of our key objectives. But you talk about these three major elements, I call it. While others have talked about integrating these AI solutions, at HPE, we wanted to create something truly unique with you. And so we did not just bring together the pieces. I always like to talk about widgets or doorknobs in a bag. You know, that's very complex for you. That's not how it works. If you want to accelerate this generative AI solution, we have to deliver you an experience. And so that's why, together with NVIDIA and their amazing portfolio of software and obviously silicon, the networking components, we are bringing all this together with the HPE systems, HPE services, the ability to manufacture and service this.
I think people forget that because once we go to direct liquid cooling, and Jensen and I were talking early on, you need to have a water-cooled manufacturing capability. And HPE has one of the largest water-cooled manufacturing capabilities on the planet. On the planet. Why? Because we have to do it for supercomputers, right? And so now we bring it all together. We democratize with all the things you talk about. And that's why today it is a pleasure to introduce what we call the first-of-a-kind turnkey private cloud AI solution developed with NVIDIA. We call it HPE Private Cloud AI. And this solution provides the deepest integration. And this is very important.
It's the deepest integration to date of NVIDIA AI computing networking and software with HPE storage and obviously our servers and the HPE GreenLake cloud because ultimately you have to deliver that experience as a cloud experience, right? Unlike any other AI solution out there who are services led, you know, meet in front of the customer, bring it together, we deliver this as a one integrated product and is ready to run out of the box because that's the key. When I say turnkey, I mean the simplest experience today for deploying and operating the NVIDIA software stack in the industry. So how does this work, Jensen, because you and I went through it, right? It's a plug it in, a few clicks.
3 clicks, I understand.
Three clicks.
Three clicks.
All it takes is three clicks.
Well, the thing that's really amazing is you say it works right out of the box. Inside that box are CPUs, NVIDIA Grace CPUs, NVIDIA GPUs, networking, NVLink switches, either InfiniBand or Ethernet for AI switches. And all of that technology with all of that software all integrated, number 1. Number 2, we've made it so that you could have small, medium, large.
Extra large.
Yeah, extra large. And as you know, the more you buy, the more you save. And so everybody.
Buy more.
Yeah.
In fact, you need fewer of them.
The more you buy, the more you save. And so, so you want the extra large version, but you can start anywhere. And this is really, this is really the big deal that we've integrated everything into a really easy-to-use private cloud AI solution. And all of the complexity that goes into all the technology has been provided to you, hidden from you, and it's helping you operate it over time. Remember, you're not buying a computer that you're using. You're buying a service, and you can own a service that you can operate. And so that's a very, very big deal.
Yeah. I'm excited because obviously he is a million times better engineer as I am. But when I think about technology, it's always about the experience, right? So that's why the HPE Private Cloud includes comprehensive multi-layer control from both HPE and NVIDIA, right? Because we have to deliver this through a cloud experience. And also the most secure sensitive data models, which includes, by the way, built-in AI data compliance and explainability. That's very important. You want to know from where these models are coming from. Automated AI pipelines with complete lineage, traceability, and auditability for the entire AI lifecycle. This is one of the things enterprises are worried about. How this thing works, where the models are coming from, how to track the data. A single dashboard. Think about that. A single dashboard to monitor all your AI applications and services.
By the way, it supports multi-tenant collaboration with unified role-based access control to isolate data and purchase across different teams. It is, as Jensen said, all built in. And at the launch, as we just kind of hinted to you, HPE Private Cloud AI will be available in 4 configurations. We are in the United States, so we need to have 4, not small, medium. We need to go a little bit large, but 4, small, medium, large, and extra large. And you can see here, each one of them is flexible, is modular, has the ability to expand our capacity over time, but maintain that consistent cloud managed experience with the HPE GreenLake cloud. Many of you are already HPE GreenLake customers here where they're using it for deploying an access point or a storage array or a server or, you know, a switch.
Now you can do the same with this private cloud solution. And now, listen, some customers are going to start small, maybe to try, but also do some inferencing. But also, as the use cases multiply, you need all the things like RAG and to fine-tune into one solution. I think we are going to offer the most comprehensive solution on the planet because also we can offer it as a self-managed or as a managed services as a part of HPE GreenLake. And at the same time, you know, you maintain the consistent operating model, which, you know, by the way, is ready to adopt whatever you come up with, which I know you have a lot coming up with, which means it's ready to adopt the latest technologies that Jensen and the team are coming through. So this is, in my mind, is a big deal.
So when you think about that, Jensen, you know, and think about the next generation, which obviously will support Grace Hopper 200 as well as the network, what do you think the enterprises will be looking next once they have the simplicity? It's all about understanding the use cases and getting it that factory mold to deploy. I think that's what we're trying to do here.
Yeah, it's a really big deal for for enterprise today. The fact of the matter is we're sitting on a mountain of data. All of us are sitting on a mountain of data. We've been collecting it in our businesses for a long time. But until now, we really haven't had the ability to refine that data, discover insight, and codify it automatically into our company's digital experience, our digital intelligence. Every company is going to be an intelligence manufacturer. Every company is built fundamentally on domain-specific intelligence. For the very first time, we can now digitize that intelligence and turn it into our AI, the corporate AI. The thing that's really profound here is that you could start anywhere: small, medium, large, extra large. They're architecturally completely compatible.
And so if you change your mind and you want to do more, everything that you've built yesterday is going to run seamlessly across the larger systems. When we go to the next generation system, everything will be CUDA compatible. This is one of the great disciplines of our company. By putting everything on top of CUDA, this revolutionary invention that we made 20 years ago, and having the discipline to maintain CUDA compatibility over all these years, some 15 generations now, we can make it possible for all of our customers to invest at any point, at any scale, and carry that investment forward. Now, once you do so, remember what AI is, and you mentioned lifecycle. It's a lifecycle that lives forever. The thing that we are looking to do in all of our companies is to turn our corporate intelligence into digital intelligence.
And once we do that, we connect our data and our AI flywheel so that we collect more data, harvest more insight, create better intelligence, which allows us to provide better services or be more productive inside the company, run faster, do things more efficiently, do it at a larger scale, and very importantly, create new products. And so all of that is possible because of the things that we're doing today.
The net of all of this to me is that you got to embrace this technology. We understand people have been a little bit wait and see. It wasn't easy for them to embrace it. But with today's announcement, we're making it really easy for you. It's just a rack or maybe two racks that you can deploy with everything you need, fully integrated. And to me, that's super exciting because we give you the tools to accelerate your journey to transform your business. But you know, today it's not just that. We talk about NVIDIA computing by HPE. We talk about the announcement of HPE Private Cloud AI. But also today, HPE is committed that we will be time to market with NVIDIA Blackwell and Rubin GPU architectures, in addition to all the software that Jensen and team will continue to bring to market.
So as you adopt this one operating model inside GreenLake, it comes with it, right? Very simple. And we'll be the leading integrator of the most advanced AI systems at any scales in a sustainable way, which is something we both care about because I argue the sooner you adopt this accelerated computing, the more efficient and more sustainable you will because you eliminate all the waste.
Liquid cooling results in higher performance, but also lower infrastructure cost.
Right.
The overhead of all of the liquid to air, air to liquid, all of that is now gone, liquid to liquid. And so the future of liquid cooling is going to result in everything from better performance, lower infrastructure costs, and lower operating costs. Yeah, really interesting.
HPE is uniquely positioned to deliver direct liquid cooling. So that's why.
Nobody has plumbed more liquid than Antonio.
There you go. And by the way, you need to come see our factory so you see how good we are on that one. Listen, HPE delivers 100% liquid cooling, including the CPU and the GPUs and the fabric. I don't think people understand that the fabric today is also liquid- cooled.
Yeah.
You know, they think about a switch there with a bunch of Ethernet ports. Actually, it's not. You also run direct liquid cooling to the fabric. And listen, we hold numerous, numerous hundreds of patents in this particular part of the portfolio. And listen, we have the expertise to build these large systems at scale, as I show early on. But also, you know, we are really proud to bring this innovation for you together with Jensen. And I think our combined portfolio can achieve amazing results. And by the way, do it in a circular economy because we can actually capture 100% of the heat that gets wasted. And we have some amazing use cases. We take actually the heat, Jensen, in some areas, and we either power greenhouses in the winter or also power heating systems in buildings so they don't waste, you know, other things.
Listen, Jensen, I know we can spend here the whole day, but to wrap us up, you know, what is the key takeaway you want the audience here with an amazing living room of this partnership?
Well, one, the era of generative AI is here. You must engage the single most consequential technology in history. You must translate and codify your company's intelligence into digital intelligence. And you must find a way as quickly as possible to turn that flywheel of your company's experience into your company's AI as quickly as possible. That's number one. Number two, our partnership with HPE is about simplifying all of this incredibly complicated technology in three stacks: the data stack, the model stack, the computing stack, turn it into this private cloud so that you could operate it or you could get the benefit from it with all of that complexity being extracted from you so that we could help you apply all of this great technology in service of you. And then lastly, this giant go-to-market.
Exactly.
This giant go-to-market.
People.
Us.
People matter.
Yeah. This network of ecosystem of partners and service providers. We're going to, because of this, make it possible for the first time to bring generative AI to every single company in the world.
Thank you. Now, Jensen and I are going to be on the show floor later. Not demonstrated because we don't have time, but going through the demos, which are amazing. We have an amazing show floor. Please go there. But listen, what Jensen and I do is in service to you, our customers. When we connect the power of our joint innovation, the expertise, and the greatness of our partnership with NVIDIA to your enterprise, intelligence has no limits, right? So thank you, Jensen, for inspiring us. It's great to have him here, an amazing innovator, a force for change in the world. For me, it's a pleasure and honor always to learn from you. Thank you very much.
Thank you, Antonio.
Go HPE. Go NVIDIA.
All right, guys. We're on your team.