| | | Reading the conference call transcript, Jensen sees the future and is doing his damnest to create it
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Matthew Ramsay
Thank you very much. Good afternoon, everyone. Jensen, I've been in the data center industry my whole career. I've never seen the velocity that you guys are introducing new platforms at the same combination of the performance jumps that you're getting, I mean, 5x in training. Some of the stuff you talked about at GTC up to 30x in inference. And it's an amazing thing to watch but, it also creates an interesting juxtaposition where the current generation of product that your customers are spending billions of dollars on, it's going to be not as competitive with your new stuff, very, very much more quickly than the depreciation cycle of that product. So I'd like you to -- if you wouldn't mind speak a little bit about how you're seeing that situation evolve itself with customers. As you move to Blackwell, you're going to have very large installed bases, obviously software compatible, but large installed bases of product that's not nearly as performant as your new generation stuff. And it'd be interesting to hear what you see happening with customers along that path. Thank you.
Jensen Huang
Yes. I really appreciate it. Three points that I'd like to make. If you're 5% into the build-out versus if you're 95% into the build out, you're going to feel very differently. And because you're only 5% into the build-out anyhow, you build as fast as you can. And when Blackwell comes, it's going to be terrific. And then after Blackwell, as you mentioned, we have other Blackwells coming. And then there's a short -- we're in a one-year rhythm as we've explained to the world. And we want our customers to see our road map for as far as they like, but they're early in their build-out anyways and so they had to just keep on building, okay. And so there's going to be a whole bunch of chips coming at them, and they just got to keep on building and just, if you will, performance average your way into it. So that's the smart thing to do. They need to make money today. They want to save money today. And time is really, really valuable to them. Let me give you an example of time being really valuable, why this idea of standing up a data center instantaneously is so valuable and getting this thing called time to train is so valuable. The reason for that is because the next company who reaches the next major plateau gets to announce a groundbreaking AI. And the second one after that gets to announce something that's 0.3% better. And so the question is, do you want to be repeatedly the company delivering groundbreaking AI or the company delivering 0.3% better? And that's the reason why this race, as in all technology races, the race is so important. And you're seeing this race across multiple companies because this is so vital to have technology leadership, for companies to trust the leadership and want to build on your platform and know that the platform that they're building on is going to get better and better. And so leadership matters a great deal. Time to train matters a great deal. The difference between time to train that is three months earlier just to get it done, in order to get time to train on three-months project, getting started three months earlier is everything. And so it's the reason why we're standing up Hopper systems like mad right now because the next plateau is just around the corner. And so that's the second reason. The first comment that you made is really a great comment, which is how is it that we're doing -- we're moving so fast and advancing them quickly? Because we have all the stacks here. We literally build the entire data center and we can monitor everything, measure everything, optimize across everything. We know where all the bottlenecks are. We're not guessing about it. We're not putting up PowerPoint slides that look good. We're actually -- we also like our PowerPoint slides look good, but we're delivering systems that perform at scale. And the reason why we know they perform at scale is because we built it all here. Now one of the things that we do that's a bit of a miracle is that we build entire AI infrastructure here, but then we disaggregated and integrated into our customers' data centers however they liked. But we know how it's going to perform and we know where the bottlenecks are. We know where we need to optimize with them and we know where we have to help them improve their infrastructure to achieve the most performance. This deep intimate knowledge at the entire data center scale is fundamentally what sets us apart today. We build every single chip from the ground up. We know exactly how processing is done across the entire system. And so we understand exactly how it's going to perform and how to get the most out of it with every single generation. So I appreciate. Those are the three points.
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