This session looks at how AI can be built to last, focusing on making it safe, useful, and beneficial for people over the long term.
In “Building AI for the Long Term,” leaders across finance, cloud infrastructure and model development argued that AI’s limiting factor in 2026 is not demand but physical and organizational capacity. BlackRock’s Rob Goldstein said the industry is still at the starting line: “the national anthem is still happening,” with adoption and transformation largely ahead. CoreWeave CEO Michael Intrator emphasized the “physical boundary” of power, concrete, copper and skilled trades, describing hyperscale data centers as “functionally the Death Star.” G42’s Peng Xiao framed long-run economics bluntly: “the cost of intelligence will equal the cost of energy,” positioning Abu Dhabi’s planned 5GW AI campus as a strategic advantage and a platform to “export those tokens.” OpenAI CFO Sarah Friar reported Stargate is ahead of expectations and highlighted rapid cost deflation, citing inference costs falling from “$33 per million tokens… to $0.09,” enabling broader access. Panelists rejected “circular financing” critiques, arguing demand is evident and accelerating; Intrator noted efficiency breakthroughs like DeepSeek triggered customers to demand “more GPUs now.” Key risks centered on geopolitics and social license to operate, with Friar warning that trust, local impacts (water, power, housing), and explaining value in “real people speak” will determine how fast AI scales responsibly.
There are no controls.
Good afternoon everyone. I'm Jessica Lesson, the founder of The Information. And I couldn't be more excited to be here this afternoon with an all star panel on AI infrastructure and the future of this important area. So I'll introduce our panelists and, really look forward to the conversation. We will leave time for questions at the end. So, please be saving those. To my left, we have Peng Xiao, who is the head of G42 out of the UAE and pretty much has his hands in every interesting AI project, that of the moment. So we're thrilled to have him. Sarah Friar, the CFO of OpenAI who has been doing business deals with everyone in the ecosystem and, of course, is leading one of the world's most important AI companies. Michael and Trader, the CEO of core. We've, which also needs no introduction. And Rob Goldstein, the chief operating officer of Blackrock. Rob, I'm going to start with you because I thought it was last, you know, I'm going to mix it up, keep everyone on the edge and please, you are all experts on every topic, so feel free to chime in even if a question is not directed at you. Rob, just minutes ago you were telling me that the on the topic of AI and infrastructure. The future is limitless. Let's elaborate and then maybe poke holes in that afterwards. But let's start with that. What is it? When you stare at 2026 that leaves you with that feeling?
Sure. Well, what what is remarkable to me, and I think people very quickly lose sight of is that three years ago at Davos, the conversation was, you have to go check out this thing called ChatGPT, which was a brand new thing. And everyone was like playing with it. Like, how do I drive from X to Y? Like the most basic, basic, basic things. And I think we forget people talk about what inning this is. To use a US analogy of baseball, I think the national anthem is still happening. I don't even think this has started yet. And if you think about the cycle as being sort of build out, then adoption, then transformation, we're still early in the buildout stage. And if anything, I think there's so much dialogue right now on bubbles, when in reality the the bigger issue, at least for the next, you know, one, two, three years is rationing capacity. So to us at Blackrock, as the COO, when I say the opportunity is limitless, I just see if you're someone who's involved with operating a company, for example, where just starting to recognize the transformative capabilities of these technologies. And I think that when you really think about the company, there isn't any aspect of the company that can't be transformed. You know, we were talking earlier about Davos and the nature of Davos and the amount of organization that's required in terms of the many meetings that you have think about. In a few years, everything will be automatic. You'll know that you bump into someone in the street, you'll know who they are, the business that you do with them, what you should ask them. So the productivity cycle, I don't even think has started yet, and I think it's limitless in terms of at least my career, the opportunity for transformation will be enough to keep me busy for the next 1020 years easily.
So job security.
Easily, at least for me. JobSeeker.
And so if we talk about let's break it down a little bit, we're talking about infrastructure here. We've got to build things. We've got to finance things. We're seeing this gold rush. But but there's also been talk about, you know, power, how can we support this our data centers going going fast enough, maybe. Do you? Michael. I mean, what are you are there some bumps along the way in this moment of scaling? What needs to happen in 2026 to to get to the next step, and then I'll come to you paying on the same question.
So, first of all, thanks for the opportunity to speak. Look, it's such a fascinating business because, the, you know, the way the, the funnel works is, is like, everyone sees these. Unbelievable, products that are coming to market that have changed the world and will continue to change the world over, you know, the foreseeable future in ways that we haven't even contemplated yet. And that is one part of the market underneath that it is physical, right? The defining characteristics of the boundary that exists right now is a physical boundary. And those physical boundaries occur in a bumpy world. Right. And it's about it's about power. It's about concrete. It's about copper. It's about, human resources. And when we think about human resources, you're talking about the trades. You're you're you need plumbers, you need electricians, they need to be trained. You know, four years ago, we were building a data center. You had, you know, 100 electricians. 80 of them were experts, and 20 of them were beginning their career. And now you have 2000 electricians and 80 of them are experts, and everyone else is beginning their career. Like there's there's a physicality to the business right now that the world is struggling to translate into. Valuation, into public markets, into, the path to delivering these products that are you generationally. And I don't even mean like one generation. I mean, like this in my mind goes down as a stepping, you know, the wheel intelligence. It's sort of like that scale of, of, of change that's occurring. And behind the scenes of that, it's so, you know, like to go to one of these data centers to walk into, like what is functionally the Death Star. And you walk through these things and you're just like, wow, there's a lot of building. There was a lot of cables, there's a lot of optics. There's an incredible amount of carpenters that are working here. It's it's wild. Right.
How do you feel about sort of the pace of these projects and are we are they at the pace that we need to to be meeting the demand. And how and then I'm cross border as well. What is the state on that?
Well, let me first say that the top expert here in building is, is Mike, who just spoke to you on the subject very eloquently. We do have a g42, a branch of our business also focused on building what we call token factories. This is basically core and shell and also GPU management business. To put this in context, answer your question right now. Some of you already know this, Abu Dhabi is undertaking to build out of a five gigawatt AI campus, which were announced last May. President Trump visited Abu Dhabi. I have a simpler view. Again, because I'm not a technical expert in building the centers. My view, which I discussed with Sam multiple times and you also saw is eventually, in the long term, the cost of intelligence will equal the cost of energy eventually. This is a unique advantage. Why we are drawn G42 and UAE Abu Dhabi drawn into this business because we have a national advantage in energy production to have five gigawatt on the grid and no permitting issues to be able to build it's blessing. And this is why we're working with OpenAI and Microsoft and many others to provide capacity to them. I speak as we speak right now. There are over 7000 construction workers in the desert, with over 100 cranes building about 250MW per quarter. To deliver on this five gigawatt project plan we have. So we are obviously very bullish and we believe UAE will consume a big chunk of that. But we also will be able to export those tokens as packages of intelligence to the rest of the world. So in UAE, to give you perspective, you mentioned that seem to be doing everything, because we are serving as, as a fairly large company, a fairly small country, we're serving the entire society using AI. And one of the tasks we have, KPIs this year is to produce over 1 billion AI agents to boost our GDP. These agents range from everything on coding agents to petroleum engineers to cybersecurity analysts. So we did our calculation. If we actually can deliver 1 billion agents, agents by the end of this year, and they are actually working even just 12 hours because they can work non-stop just 12 hours a day. They'll be consuming probably close to one gigawatt of AI infrastructure. This is how bullish we are and why we're building this infrastructure in the UAE.
Wonderful. So Sarah, you need to buy a lot of this capacity. And have done so through just a number of different partnerships. I think it's the one year anniversary of Stargate.
It is.
Today, which, how's that project going?
So incredibly, this time last year, we announced Stargate to the world, and then very quickly actually had, our president, alongside Suzanne, Sam, and Chuck Robbins, actually from Cisco and Larry Ellison from Oracle. Stand up in, in the Roosevelt Room and talk about the importance of that build and what's wild today. Our Oracle campus, for example, we said at the time, we do, upwards of $500 billion, and we're already well over halfway in terms of getting that built out. We are actually training models in that Oracle campus today on the latest chip. So it's gone kind of, I think, better than we all dreamed a year ago. It's almost a pinch me moment. I think more broadly like to kind of pull all the threads together. A year ago or a year and a half ago opening, I felt like a little bit one dimensional. We worked with one CSP Techniker. We've under microscope, Microsoft, one chip provider, Nvidia. We had one product ChatGPT and one business model, a subscription for $20 today. I think of it as like a corner of a Rubik's Cube almost. Today we have a base of infra that is almost every CSP you can mention. We're diversifying our chip portfolio, including our own inference chip that just taped out on the product side. We've gone from a consumer product that was really a chatbot to now be a task worker that can do things like health care for you on the enterprise side, something that can go from a simple ChatGPT wall to wall deployment to APIs to now agentic behavior throughout the enterprise. We believe we're there and then an API platform. And of course, Sora, because now we have multimodal, so the product platform is multidimensional. And then finally the business model is becoming multidimensional from simple subscription through SaaS based pricing, through enterprise licenses, through credit based pricing, through commerce, into advertising. And then ultimately, I think we can do some real value sharing, for example, in drug discovery. What if we took a license down the line to the drug that is discovered and use that as a way to pay for it? So if I think of that Rubik's Cube analogy, now, you spin it and you say, okay, I'm going to take a low latency chip like Cerebrus that we announced a few weeks ago. I'm going to create a high end, really fast coding SKU, literally best in the world. And I'm going to have a high end, subscription price for it. It's like I've turned all the the yellows, I've created a block. And that brings you back to this conversation about build. We are just getting started, right? You used baseball since I'm a, you know, kind of American, but a Brit under the surface, I'll go to electricity. I'm not going to do a sports analogy, but I think we've wired the house and turned on the lights, but we have not explained to people that now they could heat the home. They could cook in that home using electricity, they can have entertainment. And so the capability overhang is massive. Even if models improved zero from today, there is still so much productivity to be had. Just with what's in people's hands.
I think OpenAI is also said to you're building your own data centers. Is that part of the mix in terms of your infrastructure footprint?
And today, I'd say we're on a journey. We really are utilizing our CSP partners because it's a way to stay lighter weight on the balance sheet and frankly, to be able to work with folks. Like, for example, when we work with G42 and UAE, they have the local expertise. They know how to do the land PowerShell. When we get inside the data center, as Mike knows, we will tend to bring to bear a lot of a very strong point of view on what the kit and the rack and so on looks like. Sitting in that data center, we have a whole scaling team whose job is to make sure that frontier models can get trained on that large fabric, and therefore, what does that fabric need to look like? What is the chipset? What's the cooling? What is the power? How is it just connected. And so that's a place where we've created a lot of I would say our own IP. So we're on a journey. We are. We made an announcement with SoftBank energy to do our first Colo kind of build a suit. So think of that more as the next step. We're not all the way to build our own today because frankly we have great partners to work with. But you know, where will we be in three years? I think you said it well, when just three years ago, ChatGPT was just a new thing. So we're still young in our journey.
But your new chip is being tipped out already. That's impressive progress. That's the heart of data center.
Yeah. That new chip has. You know, it'll be an inference specific chip, and it's all about how do we keep driving down cost on the inference side, right. I find it amazing that from ChatGPT four, where it cost about $33 per token per million tokens today, ChatGPT five, mini cost $0.09, like $33 to $0.09 is a 99% reduction in costs in about two, a little over two years. I kind of blows my mind back to the point about just getting started, because now you're creating a cost backdrop that actually allows you to give access to everyone.
The the other thing that it does is and it doesn't do it yet, because you're still in a market that's pinned, right, like OpenAI can consume the capacity of the world. There's five other models that can consume the capacity of the world. Which gets to part of what you were saying, but the the drop in cost being as precipitous as it is, how many more ideas are going to get an opportunity to come into existence? And that's what I mean by like, we don't collectively, everyone on the stage, everyone in this room, I would argue we don't know what our clients or who our clients are going to be yet because there is a. It is a natural, you know, like supply and demand don't work yet, right? Because the market is literally pinned to the red line. And so it's always up against the top. But as we begin to see and markets are good at this. And so, you know, like they will ultimately bring supply and demand into some sort of balance, which will allow for the creation of tons of new things that we just don't know about yet. And that's really exciting. Also, as a matter of fact, it's probably the most exciting part of it for me because I just think it's, you know, just as people conceived of what exists right now that blows us away, they'll have an opportunity to do it again.
And the demand is still very much in the early discovery stage.
Yeah.
And I think that one of the things that often gets overlooked, going back to the the reinforcing nature of creating this intelligence, the number of lines of code in the world is going to increase exponentially. We were talking about this yesterday just from a Blackrock perspective. Our ability to leverage our engineers to just be exponentially more productive. The net result of that is we need more compute for like the old stuff. Yeah. So I think that we are going to have a phase where just the old cloud requirements are going to grow even faster than people expect in addition to this. And then you add on it, it's very clear almost all the software in the world in the next 20 years, you can figure out if it's in the next two or the next 18. Almost all the software in the world is going to be interchangeable with the AI capabilities that we're describing. So everything will be inference in terms of how it actually operates. So I think the nature of the technology and the innovation that enables winds up being self-reinforcing in a way that's only going to accelerate.
I had the opportunity to interview Andy Jassy yesterday, and he was. That's the AWS argument about the growth in cloud. He called it the middle of the barbell right now, staying on chips for a second. He also talked about trainium, which, he also believes will be necessary to get the costs down as well as the individual efforts. I wonder in the infrastructure stack, how much change do you think we'll see in on the chip side of it? Obviously Nvidia is the clear leader, but Michael, maybe to you, I know you're you're I think you're all invidia maybe at Cori right now. Or are you do you see a world in which you're, you're working with other chip providers?
So, the way that we've built our business is we are led by clients. And the best solution in market, Is and has been the Nvidia technology set, and we can't keep up with our demand for Nvidia. It's hard to allocate resources to, for a company that's growing as fast as we are. And, you know, we are, you know, with the exception of everyone else on this stage, unique, right, in terms of our, our growth prospects. And that is a, That is said with the, the, you know, like it's an incredible set of companies that are doing incredible things and going through a growth profile that is, you know, at any other point in my career would have looked at and would have like caused my head to break. So, look, you know, our, our belief and, the way that we have constructed the company is and our and our North star is take the best, computing infrastructure, build the best software solution to be able to orchestrate and deliver it, which will lead to the best product to enable the most companies to be as productive as they can in bringing their products to market. You know, from from where I sit, there's going to be lots of different, alternatives. There's a lot of different ways to define best, whether it's cost, whether it's capacity, whether it's what you can do with it, flexibility. There's, you know, like the concept of best is not that simple in this space. As we look forward in time and think about, the different ways that compute is going to be consumed. So from my seat, and from the business that we are building and the scaling that we are going through, we think that the world will have lots of alternatives, but the best infrastructure out there is going to be built by Nvidia. It's going to be built on a platform that is like ours, if not ours, and is going to have a software layer that's able to deliver it to the market in its most performant configuration. And, until the market explains to me otherwise and markets have a good way of doing that. That's our plan, that's our strategy. And we're going to keep our head down and keep hammering.
So another key component to all of this is capital, of course. And I think last year brought a variety of new flavors of financing deals from, off balance sheet deals to all sorts of new partnerships. I mean, maybe Rob from the investor side or are you seeing, I don't want to call them novel because they're not novel in the history of finance. But what are you seeing in terms of vehicles for financing data centers that's catching your eye?
Well, I think this is a a generational capital opportunity where if you think about the numbers we're talking about and if you think about, you know, we have this this term within Blackrock, the fast river, and you want to put your your boat in the fast river to have it help you along the way. And this is one of the fastest rivers I think any of us will experience in our careers. I think we're seeing, creativity as there always is in the financial engineering side. But at the same time, I think we're seeing more and more people looking to create the ecosystem in terms of not only having it as capital partners, but having it as true strategic partners. And if you go back, for example, to, Blackrock and some of the things we've done, we've actually looked to create investment vehicles that bring together as GPS, people like MDX. So leveraging the incredible innovation of Abu Dhabi, people like Microsoft, people like Nvidia, and bringing that ecosystem together. So that way you're able to prioritize focus in terms of actually bringing these projects to completion.
Sarah, what are you seeing and how do you think about this?
Yeah. So I mean, I think I think it starts with compute. So compute is the defining characteristic of what we need to supply the demand. It is the binding constraint today. And I think it is a core competitive advantage because there's not enough of it. And so if you don't have it you get slowed down. And we have faced that a lot in the past year. People always ask like, well, what if you had more compute? What would have happened? I'm like, it's quite simple. If we had more compute, we'd have more products, we'd have more revenue. We would literally have had frontier models pulled in by six months, 12 months, 18 months, because we had to know what we want to do. And it's not just revenue. I mean, I'm a CFO. I care about our business model. I'm going to come back to it in a second. But like we're talking about breakthroughs in areas like healthcare. And if I'm a cancer patient who with that breakthrough actually gets my life saved, right? In some ways, speed is even more of the essence right now. So I think we're holding stuff back. That just would help the world writ large. That's it. From a CFO sitting in my seat who now has to work through how to pay for that. I mean, there's nothing beats a good business model. First and foremost, cash flow is king. And so what we have seen is, as we have invested in compute, our revenue has kind of risen to meet the challenge. Right? I use often in these rooms. Talk more about IRR because it's the true load of the business. It's the compute I need. It's the business I need to sustain it. So IRR has gone from 2 billion to 6 billion to over 20 billion just in the last. So in that moment we're ChatGPT burst on the scene. There's never been a company like it. Right. To Mike's point, I was a research analyst at Goldman Sachs for over a decade of my career. If someone had showed me that model, I would have said, that's crazy. Like, you're wrong. And we see just this continued momentum as we hit 2026, by the way, it's not stopping. Our consumer business is hitting daily highs, which is super fun to see. And our enterprise business is kind of shooting through the roof. Right. Jessica's not wrong. Davos is just an incredible moment to go talk to CEOs and folks who are making these business decisions, right? I was saying to her as I hit the floor, I was just with the CEO of a large like, if I said, like a world famous bank who, you know, is feeling a little bit behind, had just spent time yesterday with Carlos Torres, who's the chairman of BBVA. BBVA wants to be an AI native bank. They've gone from 10,000 seats, deployed to over 120,000 seats deployed. They're rethinking their call centers. They're rethinking their credit, how they do credit decisioning. They're in 25 countries. So they have to do multilingual. I mean, totally new way of thinking about enterprise growth to finance it. We are trying to be creative. Both we've done equity based financing. We did the largest equity round ever, $41 billion last year. We have done unique partnerships. Our AMD warrant structure I'm really proud of because it's a great alignment of incentives. If we buy those AMD chips, we could get all the way up to owning almost 11% of the company. And we think that if we do buy all of those chips, we really help create a lot of market cap for Lisa and team, and they deserve it. They're incredible company as well. We have talked about our partnership that's brewing with Nvidia to fund us as we buy gigawatts of their chips as well. And so what we see is the ecosystem kind of rising to work with us. And that includes private equity shops as well. Have been very, very interested in how can we deploy into their portfolio companies and with that create a business model around it. So we are just getting started. But I do think it's important that the ecosystem rise together. Otherwise we're just going to go slower. And back to where I started. That means that that patient, that child in school or whatever is not going to get access to intelligence.
Some. There's a habit in my industry, and I am not saying I believe this, but I'm interested in your reaction to it, to calling these circular financing deals in the sense that the the sense is that all these deals basically amount to some amount of risk in the system. Sarah, how do you think about that?
I mean, there's an implication behind it, though, that the demand is not real somehow. And I think, I mean, we can all just start at the beginning of the panel. Again, I don't think that we can deny that the demand isn't here. And I think in particular, people are still have a lot of the folks who are working on Wall Street or working in your world. Jessica lived the bubble bursting before in the internet generation. And that's because when I think about what the internet was like at the time, I mean, it was dial up. Do you remember the like you write as one letter at a time, downloaded? It was kind of hard to imagine why it was going to revolutionize your life. I mean, email was just getting started, but what was the point of email if there were only like three people on the thing? Right? You still had to send letters in the mail. I would say to all of you, right now, if I want to run the room, is ChatGPT not making a difference in your life? Like, do you not immediately see value in it? And again, like for our frontier users, they're using effectively, if you look at tokens as a measure of intelligence usage there, it's seven x what just the average user today is using because they're coding. They're doing deep research. They're in a university lab countries. We've looked at it on a country level. The frontier countries are using three x the amount of tokens already. And so that's where I think the, the idea of kind of circularity and so on. It's that implicit like, oh, the demand is not there. They're all just like trying to shore it up that I completely refute. And so instead I just view it as the ecosystem. You know, the folks in this on this DS right now. Right. We all feel like we're short the thing. And so if we can push because Abu Dhabi and paying her the most AGI pilled of them all have the power. And Mike over here has knows exactly how to build a data center and to really think about the tech behind it. And Blackrock is doing incredible things to create financing vehicles and actually has gotten very deep in data center technology itself. Right. Those are all good things because everyone is bringing their expertise to the table.
I'll add one more thing to it, if you don't mind. Maybe zooming out even further. And Rob and I had a discussion about this during lunch, which is I'm a bit worried about many of our conversations here in the West becoming self-referential. I want to point out another country called China. They may not have the best models in the world, the best computer in the world, but they're doing what you termed as ruthless adoption.
Yeah.
They are driving use cases in every aspect of their society. In fact, there are a model for many of us to emulate. They are charging ahead to use AI. And guess what? Being a user, influencing traffic, getting the intelligence out can circle back to create better models.
Test time compute.
Yeah, exactly. So study the Chinese usage. Adoption of AI technology is a lesson for all governments.
Sarah, I want to ask one more follow up on the business model question you talked about, because, some of your competitors here at Davos have raised questions about why you guys are going into advertising so soon. I don't know if you saw those tweets earlier today, but you've talked about your plans to and outlined your principles. But, I don't know if you have a reaction to them saying, oh, it's a little bit early. They must need the money. How do you think about the ad opportunity?
So, I mean, first and foremost, like the why it goes back to my Rubik's Cube. Remember, at the top layer, I'm trying to create as much optionality as possible. What I know today is that 95% of our users for ChatGPT are free users, because our mission is AGI for the benefit of humanity, not for the benefit of humanity who can pay. And so in order to create access, I have to create a really strong business model. I early is a weird word because in ad models you have to be at scale. Subscale ad models don't work, so that would be early. But when you have 800 million weekly active users, you're already far beyond the scale of many companies who started in that model. But I think we have to be principled. Number one, we are not going to change the output of a model based on advertising. We have to make sure users remain fully trusting us, that you always get the best answer, not the benefit of humanity and an advertiser who sponsored them, right? Second, we are going to be very careful about not sharing your conversations to advertisers nor selling your data. And number three, we always want to make sure there's ad free on ramps, if that is your preference. But for many folks, and I particularly find it at Davos, because you are talking about a globe where what I love about technology, it is the ultimate democratizer because, I'm from Northern Ireland. I already said this once. If you take a farmer in Northern Ireland, they can literally have the same phone with the same ChatGPT level of intelligence as Bill Gates or Elon Musk, or pick the richest man in the world at the moment, hopefully a woman in the world soon.
To.
Literally the same. They can't drive the same car. Probably they kind of the same size of a house. They don't go in the same fancy vacations, but they can literally have the same technology at their fingertips. But it is our mission to make sure that that can be the case. And so we want to be able to pull all levers along the way. We know our users are using ChatGPT not just for things like health, but also for commerce. It's very natural to come down that funnel because you've had a very deep conversation. You might have started by saying, hey, I'm expecting a new baby. I really need a new baby stroller. What are the best out there in the market? But here's my price point with memory. ChatGPT actually really understands a lot of this already. Might give you some interesting other ways to think about that purchase. And then what we hear our users saying is, help me just consummate it. And that's where a very interesting conversation with an advertiser can begin. But I think appropriately so, because you're adding value to the end user. And I think that again, we have to remember our North Star is that's actually why we started by publishing our principles first before we even started testing.
I'm going to go to questions in a moment. But Pang, you brought up China and, it reminded me of a conversation I had 15 minutes before I walked into this room. I was talking to an entrepreneur who's, I don't want to give too much away, but building an AI company that's not based in the US. And I said, where do you train your models? And this person says, it doesn't matter, because I can do it so much more efficiently than everyone else. And I didn't have time to grill this person on what they were using or how they got it, per se. But it did make me wonder, and I guess both specifically, has China figured out something around training from a sort of research side to fundamentally change this equation? I know this came up in deep seek. There was a little speculation. And then more broadly, if all of a sudden breakthroughs in AI itself lead to training models much, much more efficiently, is the infrastructure opportunity limitless, or do we kind of hack that somehow on the model side, maybe, Michael, maybe. Yeah.
Yeah, I'll comment on that first. I'm not an expert in this, this area, but I can tell you from my personal point of view, China is very good at engineering. I think they're superb in squeezing every bit of engineering advantage, all of the infrastructure they do have. But I believe they are certainly behind on fundamental research and model breakthrough. That's my view right now. This is why earlier I mentioned where China leads today in my opinion, is adoption. It's in fact ruthless adoption. As Bob said. Rob said earlier, this is where they potentially can gain an edge. If we're still debating, can we use should we use it, how do we use it? Well, the other nation or nations are moving ahead to adopt it. Well be falling behind even with the best model in the world. And in terms of, shortcut to AI infrastructure consumption, I think. When you look at China's usage today, it's really actually consuming more inferencing capacity actually needs more capacity to meet the demand of billions of people, training. I think they are limited. But on inferencing, I believe globally there will be a lot more demand.
I want to reframe the question. Sure. I think that it is important that we all take as a basic truth that there will be order of magnitude, step functions and improvement in efficiency within this technology within the next five years. Pick your flavor like the deep sea step function shocked everybody except anybody who even remotely touches AI. This technology, the way that we're using it, what we're doing right. When Deep Sea came out. And, you know, there's two things that matter about when Deep Sea came out, it was, you know what, two years after ChatGPT three.
Yeah.
Okay. So like, the world kind of picked its head up and said, oh, AI, I get it at ChatGPT. And two years later, like, the technology is going through this incredible ramp of maturation, you have to work from the assumption that we will make step functions on the physical infrastructure. We will make step functions on the logical infrastructure. There are going to be unbelievable breakthroughs. And the whole world trembled when that happened. Certainly the financial world. Right. The other thing that mattered is every single one of my clients picked up the phone and started screaming at me, get me more GPUs now! I need more tokens. I need more tokens. Get me more GPUs now. Right? And so that that's a. Indication from where the rubber hits the road, right? Where people are building products, where people are serving inference, where people are monetizing AI. That is telling you that that was an acceleration of the business, not a fundamental change of the business. The improvements that were exhibited in the technology from deep Sea were impressive. Full stop. But we also took tokens from $30 down to $0.09.
Yeah.
Okay. So there is a countervailing component of this, which is okay, hit me with another deep seek. Let's take the $0.09 down to 0.000 $0.01 and tell me what gets built. The world is going to absorb the tokens the world is going to consume. It's not the infrastructure that's endless. It's the it's the voracious appetite for intelligence that is limitless. That's the part that we have to focus on. And every single step function in the foreseeable future, certainly within the horizons we're working on, are going to do nothing more than accelerate the business. Right. That's the way I look at it. That's the way I've positioned myself to build my company as I look forward in time. And I think, you know, whether or not people are, are, are working through it to the same conclusion. If you're in this business, you have somehow, some way gotten to that point where you're saying, yeah, intelligence is a net positive. It will continue to be a net positive until human extinction.
Okay.
I mean, could I just though just really fast on the training because I think we're I think oversimplifying as well. Remember what we know today because again, three, four years ago. But there's pretraining which still needs large compute fabrics, lots of data and incredible algorithms coming from the smartest minds on the planet. But then Post-training is where we got to the reasoning paradigm, and our researcher would tell you Post-training. So what we call our series of models is still probably more akin to ChatGPT three or the GPT model, which is the large is already we're at five. But oh, which is then when we do the post-training. Still, we have a lot that we can still do there. And then there's, exactly what Peng said. Test time compute. So at the moment where you're making a call, there actually can be real training done at the on the inference side, like maybe even down at a device level. And that's combinatorial. It's not like a, you know, one plus one plus one is three. It's multiple. It's it's combinatorial. And so I again, I think there's a reductionism that the world likes to use. Markets love to use it. Right. A single thing.
It's so complicated.
It must understand.
But yes, totally.
But it's but it's much more rich and diverse than I think the market often gives it credit for. And that's why I think you get these wild swing moments like Deep Seek or before it was actually the laws of scaling or dead. Yes. Then there was the deep seek moment. And so market loves these moments. But I always say, if you look back at a stock chart or a market chart, it's like it looks like the biggest divot of all time. And in reality, what we've just seen is this ongoing kind of motion for for more catalytic.
I think if you zoom out, what you have to believe is that nothing is more positive for economic growth than productivity step functions. And if you believe, which I strongly do, we strongly do, that. AI presents a generational opportunity for productivity step function. Whatever accelerates that is positive overall, even if in the short term there's a little bit of disruption.
So I'm going to take the last question and oh I'm sorry, I'm just one more. And we do it fast because we have to end on time because some people have some places to go. So what worries you all? This is a very rosy picture. I mean, it's a very exciting picture. I think it but but what could go wrong? Or what could throw a bigger speed bump in the way?
So.
You take such a deep breath in and we're going to let.
You go.
Look, This is like the Kool-Aid stand up here, right? Like we.
Are trying to put a little something in the water.
This is this is. We have all drunk the Kool-Aid. We're all.
On board. AGI pill.
Yeah. Okay, we'll go with that one. What we're doing exists in a broader backdrop, and there are other geopolitical. There are, you know, like, there are a lot of things that occur outside of our, important but narrow, or at least narrow and expanding. Let's, let's put it that way. Line of business. So what worries me, there's, there's, you know, geopolitical. Interactions that can, distort the market. They can, you know, in terms of protectionism, they can distort the market in terms of cost of capital. It can distort the market in terms of accessibility. It can it can do all kinds of wild gyrations. And if I were to put on the top of my list what I think about from a how I manage risk at our company, which I spend an enormous amount of time on, that's, that's got to be first and foremost. Okay. I jumped on that because I.
Knew a very quick question, because I want to make sure to get to one, and we're going to end right on time.
Okay. So, AI is scaling much faster than planetary systems can regenerate. So my question is what will hit first regulation or water, energy and carbon and who should be responsible for that.
So I'll I'll start. But the builders of the underlying should also definitely chime in. So I was going to answer both your questions. I was going to say speed and the ability to bring people along. So that they trust. Right. If we all like we live it, we breathe it every single day. But if you are just a kind of normal person living your life out there in the world, this can all feel like kind of tech. Gobbledygook is one of my favorite words, and there's a lot of trust that still has to be earned. And I do worry that we talk in tech talk not in like, real people speak. Like, what does this actually mean for me? If I'm a mom of a diabetic kid, I work hard all day. I come home, I've got 30 minutes to cook dinner, and it needs to be healthy for my child. How are you going to help me? And the answer has to be, actually, I've got this thing on your phone called ChatGPT. You could take a photograph of your fridge right now. It'll give you a recipe you can cook in 30 minutes or less. That is exactly what you, your kid can have. Like you're like, Hallelujah, thank you. And so then to come to your question, I think we also have to build trust in communities, communities who are going to have a data center springing up. Is that a good thing or a bad thing? It's going to bring me jobs or is it going to ruin my community? Is it going to use my water or are they going to be thoughtful about it? Is it going to raise my.
Steep prices? Or are they going to help protect my community because I still have to put bread on the table for my child. And so I think we all have a real onus up here to be bringing along communities and talking in their language, not at them, but with them taking their feedback and really thinking about how we put that into how we build our businesses, because we can get a little bit in our ivory tower.
I'm going to end it there for a time. Thank you all for the fascinating conversation.
Thank you. Thanks.
Good to see you. Yeah, sure.