00:00 Speaker A
Bob, want to get you in here as well. You know, I bet there are some viewers and investors, Bob. They see when Nvidia hits a milestone like this, maybe they sort of think of it the same way as when they see a headline, you know, the market hits new record, they think, ah, you know, missed my shot. What do you think about that? What do you see ahead in Nvidia? What are the catalysts ahead for Jensen’s one company?
00:27 Bob
Uh, well, look, it’s I there’s I still think there’s a lot of opportunity, Josh. And you know, it is easy to think, oh, all right, that’s it, they’re over and done. But there are so many things that are really just starting to happen. And again, this is where you just you have to give Jensen a lot of credit because he was thinking way in advance on a bunch of these things. Um, and so I mentioned earlier at at the top of the show, we talked a little bit about this notion of enterprise AI factories. Um, uh sovereign uh AI factories, where you’ve got countries and companies making the investments. Again, that’s just starting. So that’s opportunity. Let’s not forget also, right now, we’ve been talking about AI is kind of this general purpose blade that can cut through anything. But as you start to refine the AI capabilities, you start to think, okay, now how do I apply it? First thing, of course, that he’s been talking about is robotics. And that’s a huge upside opportunity. And again, you know, they had robotics platforms years ago that, you know, were very basic, quite honestly, but he set the stage, built the software, built the tools, and now he’s seeing how some of the other pieces that he’s had can be combined with that robotic side, and all of a sudden, open up a whole new set of opportunities. The other thing that I think doesn’t get much attention and I bring it up every time I I’m, you know, I’m here and talking with you guys, but there’s a software story. There is a software story that he’s starting to build up as well. If you want to get access to the latest, you know, Blackwell chips and what have you, when he sells it to companies like Dell and HPE and Lenovo and these guys that are selling the infrastructure to enterprises and and to other governments, you know, it’s comes with Nvidia’s software platforms and those have licenses, if you know, license fees if you choose to use them. And he’s got a bunch of other tools that are part of it too. Now, you know, right now, that’s small, but again, if we’re thinking longer term, uh, then you certainly see that opportunity on the software side, again, robotics, of course, you know, arguably automotive is a different form of robotics when we think about autonomy. Uh, so there’s that still, that possibility. Uh, so I I think there’s plenty of upside still there. Um, I do, again, think that we’re going to see much more competition from them. Everybody wants to have somebody who can compete against, you know, the king of the hill. Uh, so that’s going to be a a part of the story. But again, I think another big barrier that they overcame that, again, the market is kind of getting their heads around, as I mentioned earlier, is this, hey, China, maybe, no, maybe, yes, but it’s all gravy. And that, I do think, is a is a big factor that helps keep this thing moving.
05:02 Speaker A
Dan, I want to bring you back here as well. Bob mentions competition. How do you see the the competitive landscape, Dan, for Nvidia now and ahead? Where’s the competition going to come from? Is it, you know, is it the AMDs, Dan? Is it is it the tech giants in Nvidia’s own customers?
05:24 Dan
Uh, a little bit of column A, a little bit of column B, eventually. Uh, right? We have uh AMD has their their latest chips that uh, you know, they’re marketing as comparable to what Nvidia has right now with the Blackwell. Um, but you know, I think the the fact that so many customers have already built on Cuda, which is the software that allows you to access uh Nvidia’s chips, you know, kind of go in there and turn a uh graphic accelerator into a general purpose kind of computing chip uh for AI acceleration. That has a lot of people locked in and you know, AMD offers a competing uh piece of software that’s that’s more open source, but you know, I think at this point a lot of people are in that kind of Nvidia camp for the time being. Now, look, if the if they just built out a data center for Blackwell, they’re probably going to get Blackwell Ultra if they’re looking to upgrade. Um, it just slots in. That’s a big selling point uh for Nvidia. If a company is looking to upgrade in the future though, uh and AMD is offering something that’s as powerful and as compelling at a lower price, because that’s their kind of go-to, then maybe that’ll be uh a good uh a good opportunity for them. Intel, I I don’t, I mean, they’re not even really part of the conversation at this point when it comes to these AI chips. And then, you know, as you said, the the the actual customers themselves, the Microsofts, the Amazons, the Googles, yeah, they’re building their own chips. That’s good for them, but their customers may not want to use their chips. They may want to use Nvidia’s. So they still have to buy those Nvidia chips in their data center, so that if you say, look, I want to put this AI model together, I want to run this AI model on an Nvidia platform, not your platform, the customers can still do that. So, regardless of whether or not they’re they’re using their chips for for training or things like that, when it comes to inferencing, these people may still want to use Nvidia chips and they have to put those in the data center as well.
