NVIDIA 4Q16 Earnings Call Notes

Jen-Hsun Huang

Enterprise is waking up to the power of AI

“And so I think the hyperscalers are going to continue to adopt GPU both for internal consumption, and cloud hosting for some time to come. And we’re just in the beginning of that cycle, and that’s one of the reasons why we have quite a fair amount of enthusiasm around the growth here. You mentioned Enterprise, and enterprise, it has all woken to the power of AI, and everybody understands that they have a treasure trove of data that they would like to find a way to discover insight from. In the case of real applications that we’re engaging now, you could just imagine that in the transportation industry, car companies creating self-driving cars, one car company after another needs to take all of their row data and start to train their neural networks for their future self-driving cars. And so they use our DGX or Tesla GPUs to train the networks, which is then used to run their cars running on DRIVE PX.”

We have to make VR headsets easier to use with fewer cables

“The early VR is really targeted at early adopters. And I think the focus of ensuring an excellent experience that surprises people, that delight people, by Oculus and by Valve and by Epic and by Vive, by ourselves, by the industry, has really been a good focus. And I think that we’ve delivered on the promise of a great experience. The thing that we have to do now is that we have to make the headsets easier-to-use, with fewer cables. We have to make it lighter, we have to make it cheaper. And so those are all things that the industry is working on, and as the applications continue to come online, you’re going to see that they’re going to meet themselves and find success. I think the experience is very, very clear that VR is exciting. ”

Deep learning is a breakthrough in the category of machine learning

“deep learning is a breakthrough technique in the category of machine learning, and machine learning is an essential tool to enable AI, to achieve AI. If a computer can’t learn, and if it can’t learn continuously and adapt with the environment, there’s no way to ever achieve artificial intelligence. Learning, as you know, is a foundational part of intelligence, and deep learning is a breakthrough technique where the software can write software by itself by learning from a large quantity of data. Prior to deep learning, other techniques like expert systems and rule-based systems and hand-engineered features, where engineers would write algorithms to figure out how to detect a cat, and then they would figure out how to write another algorithm to detect a car. You could imagine how difficult that is and how imperfect that is. It basically kind of works, but it doesn’t work good enough, well enough to be useful. And then deep learning came along. The reason why deep learning took a long time to come along is because its singular handicap is that it requires an enormous amount of data to train the network, and it requires an enormous amount of computation. And that’s why a lot of people credit the work that we’ve done with our programmable GPUs and our GPU computing platform and the early collaboration with deep learning.”

We haven’t found boundaries of problems that deep learning can solve

“Now, the reason why deep learning has just swept the world, it started with a convolution of neural networks, but reinforcement networks and time sequence networks and all kinds of interesting adversarial networks. And the list of types of networks, I mean, there are 100 networks being created a week, and papers are coming out of everywhere. The reason why is because deep learning has proven to be quite robust. It is incredibly useful, and this tool has at the moment found no boundaries of problems that it’s figured out how to solve. ”

You could achieve level 5 autonomous today with more chips

“DRIVE PX today is a one-chip solution for Level 3. And with two chips, two processors, you can achieve Level 4. And with many processors, you could achieve Level 5 today. And some people are using many processors to develop their Level 5, and some people are using a couple of processors to develop their Level 4. Our next generation, so that’s all based on the Pascal generation. That’s all based on the Pascal generation. Our next generation, the processor is called Xavier. We announced that recently. Xavier basically takes four processors and shrink it into one. And so we’ll be able to achieve Level 4 with one processor. That’s the easiest way to think about it. So we’ll achieve Level 3 with one processor today. Next year, we’ll achieve Level 4 with one processor, and with several processors, you could achieve Level 5.”

Colette Kress

Level 4 autonomy in Audi by 2020

“Jen-Hsun was joined on the CES stage by Audi of America’s President, Scott Keogh. They announced the extension of our decade-long partnership to deliver cars with Level 4 autonomy starting in 2020, powered by DRIVE PX technology. Audi will deliver Level 3 autonomy in its A8 luxury sedan later this year through its zFAS system powered by NVIDIA. We also shared news at CES of our partnership with Mercedes-Benz to collaborate on a car that will be available by year’s end. During the quarter, Tesla began delivering a new autopilot system powered by the NVIDIA DRIVE PX 2 platform in every new Model S and Model X, to be followed by the Model 3.”