Jensen Huang: One of the things that, if I could add, Stacy, to say something about the wisdom of what Mercedes is doing. This is the only large luxury brand that has, across the board, from every — from the entry all the way to the highest end of their luxury cars, to install every single one of them with a rich sensor set, every single one of them with an AI supercomputer, so that every future car in the Mercedes fleet will contribute to an installed base that could be upgradable and forever renewed for customers going forward. If you could just imagine what it looks like if the entire Mercedes fleet that is on the road today were completely programmable, that you can OTA, it would represent tens of millions of Mercedeses that would represent revenue-generating opportunity.
And that’s the vision that Ola has. And what they’re building for, I think, it’s going to be extraordinary. The large installed base of luxury cars that will continue to renew with — for customers’ benefits and also for revenue-generating benefits.
Operator: Your next question comes from the line of Mark Lipacis with Jefferies.
Mark Lipacis: I think for you, Jensen, it seems like every year a new workload comes out and drives demand for your process or your ecosystem cycles. And if I think back facial recognition and then recommendation engines, natural language processing, Omniverse and now generative AI engines, can you share with us your view? Is this what we should expect going forward, like a brand-new workload that drives demand to the next level for your products? And the reason I ask is because I found it interesting your comments in your script where you mentioned that your kind of view about the demand that generative AI is going to drive for your products and now services is — seems to be a lot, better than what you thought just over the last 90 days.
So — and to the extent that there’s new workloads that you’re working on or new applications that can drive next levels of demand, would you care to share with us a little bit of what you think could drive it past what you’re seeing today?
Jensen Huang: Yes, Mark, I really appreciate the question. First of all, I have new applications that you don’t know about and new workloads that we’ve never shared that I would like to share with you at GTC. And so that’s my hook to come to GTC, and I think you’re going to be very surprised and quite delighted by the applications that we’re going to talk about. Now there’s a reason why it is the case that you’re constantly hearing about new applications. The reason for that is, number one, NVIDIA is a multi-domain accelerated computing platform. It is not completely general purpose like a CPU because a CPU is 95%, 98% control functions and only 2% mathematics, which makes it completely flexible. We’re not that way. We’re an accelerated computing platform that works with the CPU that offloads the really heavy computing units, things that could be highly, highly paralyzed to offload them.
But we’re multi-domain. We could do particle systems. We could do fluids. We could do neurons. And we can do computer graphics. We can do . There are all kinds of different applications that we can accelerate, number one. Number two, our installed base is so large. This is the only accelerated computing platform, the only platform. Literally, the only one that is architecturally compatible across every single cloud from PCs to workstations, gamers to cars to on-prem. Every single computer is architecturally compatible, which means that a developer who developed something special would seek out our platform because they like the reach. They like the universal reach. They like the acceleration, number one. They like the ecosystem of programming tools and the ease of using it and the fact that they have so many people they can reach out to, to help them.
