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company and we take them very seriously and we just kind of have to keep running fast.
Let's talk about vendor financing, because that has been something that has raised a lot of questions on Wall Street since you cut this deal with OpenAI yesterday. Bloomberg is reporting that you have a $2 billion in financing that you're going to be involved with, with XAI to help them with these same stories. But this idea of circular financing your your customers can't afford to buy these chips yet, so you're going to help them out with money along the way. That leads some people to think back to what happened with a with companies during the big build up, like a Lucent or Nortel in the early days. Is this different and if so, how?
Well, first of all, Xai, I'm super excited about the financing opportunity that they're doing. You know, the only the only regret I have about XAI, we're an investor already. The only regret I have is I didn't give him more money. You know almost everything that Elon's part of. You really want to be part of this. Well, and and he gave us the opportunity to invest in Xai. I'm just delighted by that. And so that's not that's an investment into a really great future company. And I'm really excited about that. That's not venture venture. That's not venture financing per se.
But what's going on, what's going on in the world versus what happened in 2000 is just dramatically different. You know, back then, as you recall, there were Pets.com hospitals and all of the internet companies combined was, what, 30, $40 billion in size? If you look at the hyperscalers now, that's where the first tranche of AI infrastructure is building. If you look at the AI, the the hyperscalers have about $2.5 trillion of business that's already operating today. That business that $2.5 trillion business in the CapEx that goes underneath that is about call it $500 billion. That transition from a classical CPU based computing to now generative AI computing powered by GPUs. That transition is just starting. So we've got to build into half $1 trillion worth of capacity infrastructure that's already naturally growing by itself. And we're in the beginning phases of that, where if you just look at Nvidia's AI infrastructure business, you know, call it a couple of hundred billion dollars so far, there were a couple hundred billion dollars into a multi trillion dollar build out. So that's number one.
The second part of it that's really unique is that we have a new generation of AI companies. The new AI companies like OpenAI and anthropic and XAI and and companies that are that are well, you know thinking machine labs from Meera and Ilya Sutskever SSI and Misha's company reflection. And I mean, there's a whole bunch of amazing AI, AI model builders now, this generation of AI model builders, what's happened in the last several months, a transition happened that is really, really important. For the last several years, they've been generating tokens. You know, these AI tokens basically at a loss. And the reason for that is because the early AI models weren't they were super interesting, really captivated a lot of attention, but they weren't useful enough to pay for the last several months has been very clear that the new technology is now reasoning. It's doing research before it answers a question. It goes on the web and studies other PDFs and websites. It can now use tools, generate information for you, and it creates creates responses that are really useful. I use it every day to the point where now the tokens are profitable.
The question though, is who is going to continue to pay for that build out? Is it the big companies like Procter and Gamble? Is it a big? Is it consumers who are going to do this? I mean, my doctor showed me the AI that he's using and it's incredibly helpful, but there's still a question about whether he's going to pay for it or the company he works for is going to pay for it.
Well hopefully both. I think the there's the consumer part of it. You know, a lot of OpenAI customers are consumers and they're paying for it. But the thing that's really cool is that the enterprise AI build out that's happening now. My my favorite enterprise AI service is cursor. Cursor is an AI coder. And every one of our engineers, 100% is now assisted by AI coders. And our productivity has gone up incredibly. And so you're now seeing enterprise AI companies like cursor open evidence I love lovable. All of these companies are some of the fastest growing companies in the world, and they address enterprise. And so enterprise AI is here.
I wonder how you think about Jensen, the ultimate destination where all this is actually building toward? I don't know, there was a post from David Carney's a Sequoia partner this week saying, look, AGI is the only thing that can justify the volumes of capital spending right now. Artificial general intelligence. At the same time, many of the model builders and experts are pushing out the date where that maybe is going to be achievable. Meantime, you're talking about annual generations of chips. How fast do they depreciate? We're putting all this capital in these data centers that it's just not clear, like when we get to the end or is it just a treadmill?
We are going to have incredibly profitable and incredibly useful AI's long before AGI. And for example, right now, cursor AI, you know, cursor cursor is a AI software coder is incredibly useful. All of our engineers use it. We have some 40,000 engineers. Almost every one of them are going to use it. And they're they're loving it. And so.
They're using it instead of something else presumably. Right.
So these are.
Displacing things.
Yeah. They're not they're this is a brand new thing. Yeah. Remember AI unlike unlike previous technologies previous technologies are tools that humans use. Excel is a tool that humans use a web browser. It's a tool that humans use for the very first time. We have technology that can actually use tools by itself. And so cursor uses, you know, visual C++ and it. And now we have Gemini agents that are able to use the browser and browse browse for, for groceries or, you know, destinations or book travel for you. And and it can use it can use tools by itself. So so this is really quite an extraordinary thing. This tool users the tool industry is a few trillion dollars. Yeah. Tool user industries $100 trillion. Which is the reason why everybody's so excited about the future of technology. Because it could augment labor. It can increase the productivity of labor. And here at Nvidia, you know, it's increased our productivity productivity tremendously.
You've already said you wish you could have bought more open AI and maybe invested more in AI. At this point. That implies that you don't think that this is all redundant because a lot of the players I mean, if I read what Sam Altman says in the message he tries to convey, it's as if they're sprinting to try to stay ahead of everybody else because they think it's not going to be room for everybody necessarily, who's trying to do something similar.
I think there's general intelligence and I think there's specialized intelligence. Yeah, we love general. General. When I hire engineers, I like them to be generally intelligent. And that's that's a great thing. But once they come to Nvidia we make them highly specialized, intelligent so that they could build things that Nvidia needs. And so I think the idea of specialized intelligence versus generalized intelligence will continue to happen. And where the real value for enterprises and companies are is specialized intelligence and where the value for consumers general intelligence.
Okay. So let's talk a little bit about capital allocation. And how do you see that. Just back to those same points that you wish you had more invested in open AI. You wish you had more invested in in these other companies that you're kind of taking stakes in, like an AI, you can do things with your money. You can choose to put it back into R&D. You probably don't need a ton with that right now. You can choose to build the company. You can choose to make acquisitions. You can choose to give shareholders back big dividends, or you can invest it yourself in other companies. And lately, what we've seen is a lot of investing in other companies. Do you have other deals like that planned in the works?
We're always looking for great startups to invest in. One of my favorite ones was Core Weave, right? My only regret is I didn't invest enough. Yeah. And so in all of these, all of these investments that we've made recently, we've made some really terrific investments. And and largely my only regret is that we didn't invest more because a really special companies and they're building their part of our ecosystem, building out the AI infrastructure for the world. And AI is several things. AI is energy, AI is chips, the models and the applications. And so you could see Nvidia and you could look at me working across that entire stack of ecosystems around the world. And we need more energy. We need more chips. We need better mod