FY 2021 Q4 Selected Earnings Call Transcript Excerpts - Part 1
C.J. Muse
Good afternoon. Thank you for taking the question. I guess Jensen, higher level question for you on the enterprise side; you're now a couple of quarters into the ramp of A100. I am curious if you could speak to whether you've seen any surprises here, any areas of specific strength worth calling out? And any changes to how you're thinking about the size of this opportunity?
Jensen Huang
Yes. Thanks a lot. It's Jensen. As you know A100 is a very different type of GPU. This is our first universal computing GPU. It's great at high-performance computing. It's great at data analytics, it's great at training and also for our highest GPU is also the first time that is incredible for inference. It's some 20 times faster than previous generation. We may introduce this some really exciting new computational formats like TF32, TensorFloat-32 for training. And with a multi-instance GPU, turning our GPU 1, GPU to a whole bunch of smaller GPUs – autonomous GPU to improve performances and reducing latency.
And so the capability is really quite exciting. We're seeing straight in hyperscalers as they continue to accelerate their adoption of AI. Some of the new applications we've spoken about a couple of times before, the transition to deep learning, the conversational AI, speech recognition to natural language understanding all the way to speech synthesis, which is now based on AI – based on deep learning. The other area that's growing incredibly fast is the deep learning recommender models. That's just about everything that you do on the Internet is based on recommenders. There are hundreds of different recommenders out there, whether you're shopping or recommending music or recommending news or recommending search and so all of the recommending ads, and so all of these different types of applications are driving down.
For the first time we saw our industrial application or industrial data center growing to be larger than hyperscale. And we're seeing industrial applications across scientific computing where simulation based approaches are now being fused with AI approaches for weather simulation, genomics, molecular dynamics simulation, quantum chemistry, even simulating quantum computing, which is one of the really exciting areas.
We're seeing AI being deployed for big data analytics rapid, which is Nvidia has created open source platform for data analytics of Spark 3.0, which Nvidia really led and as now GPU accelerated. So now you could have big data in the cloud, while doing big data analytics in the cloud on all of the CFT platforms. And you could – we're seeing a lot of excitement around financial services and consumer internet services are all really growing nicely. And so A100 is the adoption is just starting, I mean, we're going to see several – couple of years of continued growth ahead of us, while as AI gets adopted in clouds and industries.
Vivek Arya
Thanks for taking my question. Just a clarification and then a question for Jensen. On the clarification, Colette, I was hoping if you could give a little more color around Q1? Do you still expect data center to grow sequentially in Q1? I know you said that most of the growth will come from gaming, but any color on the data center would be useful?
And then Jensen the question for you, in your press release you use the phrase AI driving the smartphone moment for every industry. Could you help us quantify what that means and where I'm going with that is, is there a number in terms of what percentage of servers are shipping today with your accelerators, and where can that ratio go overtime? Is that a fair way of looking at the adoption of your technology and AI?
Colette Kress
So thank you, Vivek. Your question regarding the guidance as we beat into Q1. We had indicated that yes, a good percentage of our growth between Q4 and Q1 those come from gaming, but we also do expect data center to grow. Most of our sequential growth coming from gaming, but keep in mind we also expect all of our markets platforms will likely be able to grow quarter-over-quarter.
Jensen Huang
Vivek Arya, we are entering the third phase of AI. The first phase of AI was when we invented the computing platforms, the new chips, the new systems, the new system software, the new middleware, the new way of working, the new way of developing software, which the industry, the world is now starting to call MLOps. The way that software is developed and the way that is deployed is completely different in the past. In fact I heard a great term Software 2.0, and it makes a lot of sense. It's a computer that is writing software. The way that you develop software is completely different; the way you compute is different. And that was our first phase, and that that started in a journey that was some eight, nine years ago now.
The second phase was the adoption of using this in an industrial way for clouds. And we call it revolutionized services; whether it's speech oriented services or searching oriented services, recommended services, the way you shop, the way you use the internet is completely different today. And so that's really the second phase and those two phases are still continuing to grow, and you're still seeing the growth associated with that.
The third phase is the industrialization of AI and some of the great examples when I say in terms of smartphone moment, I meant that it's a device with AI, its autonomous and it's connected to a cloud service, and it's continuously learning. So some of the exciting example that I saw, that I've seen and we're working with companies all over the world, we have some 7,000 AI startups we're working with, and almost all of them are developing something like this. And large industrial companies whether it's John Deere or Walmart, they're all developing application [indiscernible].
And basically it's an autonomous system, autonomous machine. In our case it's called Jetson, it's a robotics machine. That robotics machine is a car, then its call DRIVE and it's running an autonomous, an AI application on top and AI's skills on top. And it could be – it could be moving things around, it can be picking and placing. It could be just watching a warehouse and monitoring traffic and keeping traffic flow going. It could be connected to a car. And whenever the car – whenever the fleet of cars needs to be retrained because of the new circumstance was discovered the cloud service will do the relearning and then was deployed into all of the autonomous devices.
And so in the future, we're seeing these industries, whether you're in retail or in logistics or transportation, or farming, ag tech to lawnmowers – consumer lawnmowers. They're not going to just be products that you buy and use from that point forward, but it likely be a connected device with an AI service that runs on top of it. And so these industries I'm so excited about because it gives an opportunity to change the way that they interact with their customers. Rather than selling something once, they sell something and provide service that's on top of it. And they can stay engaged with the customers. The customers could get a product that's improving all of the time, just like your smartphone. And that's kind of like – that's kind of the reason – that's the reason why I've been calling it a smartphone moment for all these industry.
And we saw what happened to the smartphone revolution. And then we saw what happened to the smart microphone, the smart speaker revolution, and you're going to see smart lawnmowers, smart tractors, smart air conditioners, smart elevators, smart building, smart warehouses, robotic retail storage and entire store – the entire retail store is like a robot. And they will all have autonomous capability that are being driven by AI. And so what’s new for the industry therefore. Is that all if the enterprises in the world use to have computers for IT to facilitate our employees and their supply chain. But in the future, all of these industries whether in medical imaging or lawnmowers, you're going to have data centers that are hosting your products just like the CSP.
And so that's a brand new industry and we have a platform that we call EGX, which is the 5G Edge AI systems. And we have the autonomous systems we call AGX, which is what goes into adjusting and drives. And between those two systems and the software stack that we have on top of it we're in a great position to help these industries one at a time transformed their business model from a object oriented business model, a thing based business model to a connected device. |
