FY 2021 4Q Earnings Call Transcript Excerpts
John Pitzer
Yes, guys. Thanks for letting me to ask questions. I want to go back to data center. You've been very kind over the last couple of quarters to call out Mellanox both when it was a positive driver and when it was a headwind. I'm kind of curious as you do – when you look into the fiscal first quarter, is there anything of distinction to mention around Mellanox versus core data center? And I guess as a follow on, the key metric that a lot of investors were looking at is when does the core data center business year-over-year growth starts to reaccelerate? And some of that is just simple math where you're just comping very hard compares from last year. But Jensen how would you think about data center year-over-year growth in the context of a reopening trade or any sort of new applications out there? I mean, what happened – what helped last time around was the move to natural language AI. Is there another big sort of AI application we should be thinking about as we think about data center growth reaccelerating?
Jensen Huang
We're expecting – Mellanox was down this last quarter. And our compute business grew double digit and offset – more than offsets the decline in Mellanox. We expect Q1 to be a growth quarter to Mellanox and we expect this coming year to be quite an exciting year of growth for Mellanox. The business is growing and ethernet is growing for CSPs is growing in InfiniBand for high performance computing and the Switch – the Switches have grown. Switch business grew 50% year-over-year. And so, we're seeing really terrific growth there. One of the new initiatives and we're going to see success towards the second half because the number of adoptions, the number of engagements has grown as our BlueField DPUs. It's used for virtualization for hyperscalers.
It's also used for security. As you know quite well the future of computing and cloud and it's multi-tenant cloud and there's no VPN front door to the cloud. You've got millions of people who are using every aspect of computing. So you need to have distributed firewalls and you can't have it just in one place. The intense focus of security across all of the data centers around the world is really creating a great condition for BlueField, which is really perfect then. And so, I expect our Mellanox networking business to grow very nicely this year. And we expect Q1 to be a great growth quarter for compute as well as Mellanox.
The Killer, great driving application for AI are several – last year you're absolutely right that it with natural language understanding and the transformer model and what is the – what was the core of – and other versions like that really, really made it possible for us to enable all kinds of new applications. So you're going to see a natural language understanding do text completion, and it's going to be integrated – I think it was just announced today that it was going to be integrated into Microsoft Word, and we've been working with them on that for some time.
And so there are some really exciting applications out there, but the new ones that came – that emerged recently are deep learning based conversational AI, where the ASR, the speech recognition as well as the speech synthesis are now based on deep learning, it wasn't before. And they were based on models that ran on CPUs, but now with these deep learning models, the accuracy is much, much higher and it has the ability to also mimic your voice and be a lot more natural. And so, the ability – these models are much more complex and much larger.
The other big huge driver is the recommenders. This is something really worthwhile to take a look at is called deep learning recommender models, and recommenders have historically – whether it's for shopping and or personalizing websites are personalizing your store, recommending your basket, recommending your music. Historically, it's been – and use the traditional machine learning algorithms, but because of the accuracy and – just the extraordinary economic impact that comes from an incremental 1% in accuracy for most of the – mostly the world's large internet businesses people are moving very rapidly to deep learning based models. And these models are gigantic. They're utterly gigantic.
And this is an area that is really driving high-performance computers. And – so we – I expect us to see a lot of momentum there. And the last one is the one that I just spoken out, which has to do with industrial 5G and edge, IoT type of applications for all of the different industries whether it's retail or logistics or transportation, agriculture or warehouses to factories. And so, we're going to see AI and robotics in a very large number of applications in industries and we're just seeing so much excitement there.
Mark Lipacis
Hi, thanks for taking my question. A question for Jensen, I think. Jensen, if you look at the past computing eras, typically it's one ecosystem that that captures 80% of the value of that computing era and mainframes as IBM and many computers with stack PCs, Wintel, cell phones, Nokia and then Apple. So, if you don't get the ecosystem right then you're splitting 20% of the market with a handful of players. So in this next era of computing parallel processing or AI, I think you've articulated the most compelling architectural vision of the data center of the future with data center scale computing devices with CPUs, GPUs, DPUs integrating to the same box serving all workloads in machine virtualized environment. Can you help us understand where is the market in embracing that vision and where is NVIDIA in building out that the ecosystem for that data center scale competing vision. And then maybe as part of that to what extent is CUDA of the kernel for that ecosystem? Thank you.
Jensen Huang
Yes, we're – I think we've done a great job on building out the platforms for several ecosystems around the world. And the domain that we do incredibly well out on – the domains that I have to do with accelerated computing, we pioneered this approach. And we brought it to high-performance computing at first and we accelerated scientific computing and we democratized supercomputing for all researchers, anybody who wants to have a supercomputer now can. And computing, it will simply not be the obstacle that somebody's discovery. We did the same for artificial intelligence. We did the same for visualization. We brought – we expanded the nature of gaining tremendously. Our GeForce today is the largest gaming platform. It’s the largest single largest body of computers that are used for gaming.
And in each case, we expanded the market tremendously. We would like to do the same for data center scale computing, as it applies to virtualizing these applications, these applications are also in the process. They've historically required dedicated systems, but they're moving into a virtualized data center environment.
And we are best at doing that. They run on our platform today. We have the ability to virtualize it and put it into the data center and make it remotely available. And so these applications, these domains are some of the most important domains in the world. And so we're in the process of getting them. By doing so and making our architecture available to CSPs and OEMs, we could create this accelerated computing platform available to everybody.
And so that's we're seeing our journey doing them. First, creating an architecting this platform, and then putting it literally into every single data center in the world. But we would also like to the next step of our journey is there's the Phase 3 of AI and has to do about – it has to do with turning every end point into a data center, whether it's a 5G tower, a warehouse or retail store, a self-driving car, a self-driving truck, these are going to be – they're all going to be essentially autonomous data centers and/or they're going to run AI, but they're going to run a lot more. They're going to do security in real time. Its networking is going to be incredible. It's going to run software to 5G and GPO accelerating 5G, we call areal.
And so these platforms are going to become data centers. There'll be secure. The software is protected and we can't tamper with. It if you tamper with it, of course won't run. And so the capability of these clouds will move all the way out to the edge. And we're in the best position to be able to do that. So I did the – in this new world of post close to Moore's law post in arts gaming in this new world where AI and software that writes software in this new world, where data centers are going to be literally everywhere and they're unprotected. There's no giant building with a whole bunch of people that secured. And in this new world where a software is going to enable this autonomous feature, I think we are a perfectly positioned for it. |
