저자: CathieWood,JensenHuang클립포함 · 외국인
요약 보기
젠슨 황은 AI 수요가 에이전틱 단계로 가속되며 엔비디아 데이터센터 수요가 대형 하이퍼스케일러 외 고객(지역 클라우드, 제약, 자율주행)으로 확산 중이라고 주장. 베라 루빈 칩이 하반기 출시 예정. 캐시 우드는 현재 시장이 'wall of worry'(회의론이 있는) 상태라 닷컴 버블과 달리 건전하다고 보며, 자율주행 모빌리티가 10년 내 10조 달러 시장이 될 최대 기회라고 주장. 중국 AI는 미국에 약 6개월 뒤처져 있으며 경쟁이 혁신을 가속한다고 봄.
다듬은 글
Hello, ladies and gentlemen. I've got two huge gifts for you today. In clip one, Jensen Huang, CEO of Nvidia, explains why AI demand is accelerating even faster than anyone expected, and we'll break down what that means for the companies building this infrastructure. Then, in clip two, Cathie Wood makes a case that we're climbing a wall of worry right now, and she explains why autonomous vehicles could become a 10 trillion-dollar market within the next decade.
Let's get into it. Demand is really strong, and it's diverse. It's coming from all over the place. At the core of it, Becky, what's happening is that AI just went through its third inflection. The first one was 2 years ago with ChatGPT. And then, the second one was about a year ago when the reasoning AI agents came out, reasoning AI systems came out.
And the number of tokens, the amount of computing demand that it needed to be able to reason and produce all the excellent answers that these chatbots were doing was really sky-high. And then now, with these agentic systems, we're now having these agents able to reason, take task, and actually do work.
And so, the agentic systems are doing incredibly well all over the world. Of course, you've heard how Claude Claude code and OpenAI's Codex are doing incredibly well in companies all over the world in software programming, but it's starting to spread out into all these different type different other types of tasks.
And so, at the core, it's because AI has gone through a new inflection point, and the amount of computing demand is off the charts. Let's talk a little bit about your customers, too, because you did say that the the big companies, the big hyperscalers, actually increased the amount of spending, and I think they make up about half of the spending that went into the data center segment in particular.
But, you said the other customers were growing really quickly, and that's where so much of the growth came from. Who are those other customers? You know, most people see AI as a chatbot, and the understandable because Open AI is so popular and they're doing so well, and we hear a lot about cloud code, but remember AI is about a new way of doing software and affects every single industry.
Nvidia is really fortunate in the sense that we are the computing platform, the accelerated computing platform for every cloud, for any model, as well as every different domains of science. And so we're seeing success whether it's in small cloud service providers regionally around the world. It could be an enterprise, our big partnership with Lilly.
We have many others, car companies that are building autonomous vehicles, the robo taxi era is coming, and so there's a whole bunch of computing being built for that. Scientific computing is being completely revolutionized by artificial intelligence. And so, you know, the number of industries that are affected by AI because AI is fundamentally a new way of doing software is going to be very broad-based, and that's one of the reasons why I say AI is a new industrial revolution because every single company is affected, every industry will be transformed, and every country will power it, and so it's a very it's broad-based.
Again though, you talk about their their market share of that data center chips, 95% they estimates run from 90 to 98%, but about 95%, and when you have margins like that, 75%, it's obviously a market that lots of others want to get involved with. You did her earlier this week about AMD cutting a deal with Meta, that's supposed to be a multi-year deal that they are going to be looking at as well.
You have all kinds of competitors who are trying to get in on that, but you also have Nvidia kind of running as fast as they can. The uh the new chips that are going to be rolled out, they talked about the those new chips that are coming, Vera Rubins. That will be the second half of this fiscal year, and that is the way that they are planning to try and keep some of that market share.
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If you run a business and you've ever wondered whether YouTube could actually bring you clients, I made a free training that shows exactly how this work. Check out the link in the description. Back to the video. Nvidia sells the picks and shovels to every industry going through the AI transition, and that customer base is spreading way beyond the big tech hyperscalers.
So, Jensen's laying out these waves of AI. ChatGPT 2 years ago, reasoning models a year ago, and now agentic systems. The agentic phase is where these aren't chatbots anymore. These are systems that can actually take a task and run with it. Code, code, Open AI's Codex, and every time these agents get more capable, they need more compute, way more compute.
So, the demand curve just keeps steepening. Jensen says about half of Nvidia's data center revenues comes from the big hyperscalers, your Microsofts, your Amazons, your Googles. That's expected, but the other half is growing faster. Regional cloud providers, pharmaceutical companies like Eli Lilly, and autonomous vehicle companies.
Let's take a look at drug discovery. Drug discovery is basically a massive compute problem. You're simulating millions of molecular interactions to find the ones that works. That used to take years in a lab. Now, if you've got enough GPUs, you can run it in weeks. So, Nvidia's selling to healthcare, automotive, finance, scientific research, anywhere someone needs to process huge amounts of data quickly.
A CNBC host mentions AMD cutting a deal with Meta. Competitors are trying to get in, but Nvidia's running a full stack platform at this point. Chips, software, networking, the whole thing. Verubian's coming in in the second half of this year, and that keeps the next generation keeping the cycle going.
Each new chip generation gives customers a reason to stay on Nvidia's platform because they've already built their software stack around it. Customer diversification actually backs up Jensen's new industrial revolution claim. When your buyers go from just tech companies to farmer auto makers to national governments, it's broad-based demand, and broad-based demand is a lot harder to disrupt than having three or four big customers.
So, that's the supply side. Nvidia's building the infrastructure. Now, let's look at where one of these biggest investors in tech thinks the demand is heading. In this clip, Cathie Wood, founder of ARK Invest, draws a direct comparison between today's AI cycle and the dot-com bubble. She explains why she thinks this time is fundamentally different, and then she names autonomous mobility as the single biggest opportunity in AI.
We're talking $10 trillion. Let's hear her out. I was in the bubble investing portfolio manager during the bubble. And what we witnessed back then were investors throwing money at any company with dot-com or internet in its description. Uh today couldn't be more different. We are climbing a wall of worry.
Investors are very hesitant to continue fueling the AI boom because they're worried that we are in a hype cycle. As a portfolio manager, I would much prefer to invest in that kind of market. Why? Uh because walls of worry, climbing walls of worry, those are the most durable bull markets. And I remember uh, as way back in the '80s '90s, those were the kinds of bull markets we were in.
In the late '90s, uh, that was uh, an irrational, out-of-control end to a massive 20-year cycle. Both the dot-com boom, uh, and today's AI surge were built on a new revolutionary technology, but also, uh, on belief in American economic and technological dominance. Do you think this view is still tenable given the huge progress China has been making on that front?
Uh, we have now, um, Chinese tech companies releasing new AI models, uh, with, um, the market eagerly awaiting, uh, the one from Deep Seek. Uh, so, do you see American exceptionalism to continue driving innovation leadership? Well, uh, I do agree that China is the competitor. The Deep Seek moment, uh, was a wake-up call for all of us to understand that, um, that what China has done actually has been encouraged by our software companies.
Our software companies stopped selling into China because of fears of IP theft. So, they moved into the open-source movement and they are running hard with it. Uh, we are big believers in the open-source movement. Now, in terms of, uh, competition, uh, we think competition is very good for the United States.
That's when we're at our best. Uh, and so, I think the AI revolution is, uh, occurring faster perhaps than otherwise might have been the case because China is so advanced. Many, uh, experts would say China is about 6 months behind the US in terms of the frontier models and our research corroborates that.
We're seeing leapfrogs China kind of encroaching on the US but then the US moving further ahead. Again, competition is good. I think it's it's encouraging faster momentum in the cycle and just to answer one other way the previous question. If you think about the tech and telecom bubble in the late 90s, that was all about laying fiber for broadband connectivity.
Well, that fiber was dark for many many years. There was just too much too soon, too few opportunities. It's completely different today. Every GPU in the world is being utilized and I do think it's this dynamic China US competition that is speeding the revolution along. Interesting. And as an investor, do you see this risk off environment as a buying opportunity?
And in general, where do you see the most compelling opportunities within the artificial intelligence industry right now? Well, I would have to say that the opportunities are are more in embodied AI meaning bringing the physical and the digital together and so autonomous mobility we think will be the biggest revenue generator.
It'll scale the most quickly to the 10 trillion dollar mark which is quite meaningful in a world where global GDP is about 130 trillion. We think that will happen within the next 10 to 5 to 10 years. And you know, this movement has happened slowly, slowly, and now it's happening all at once. Elon Musk was talking about autonomous mobility in his master plan 10, 12 years ago.
And here we are. Finally, he launched this year. So slowly, slowly, and now he's saying by the end of this year, depending on the regulatory environment, Tesla will be autonomous in 25 to 50% of all of the US major cities. So that's one. And then the other one is in health care. While we may see the scaling of revenues the most quickly in autonomous transportation of all kinds.
We think the most profound applications of AI are going to be in health care. And from a regulatory point of view here in the United States at least, we're just strangling the health care sector and with with too much focus on safety and not enough on efficacy. Cathy Wood invested through the dot-com bubble firsthand, and she sees today's AI market as a healthier setup because investors are skeptical rather than euphoric.
Cathy makes a really important distinction here. In the late '90s, investors were throwing money at anything, pure euphoria. Nobody was asking the hard questions. Today, Cathy says it's the opposite. Investors are hesitant, worried about hype cycle, climbing a wall of worry. And her argument is that's actually the best kind of bull market because skepticism keeps things grounded.
Prices don't run away from fundamentals when people are constantly stress testing the thesis. Cathy's got a fair point. Look at how the market reacted to Deep Seek last year. The video dropped significantly on the news that a Chinese lab trained a competitive model cheaply. We've all heard of the dark fiber story by now.
You can argue about whether AI spending is sustainable long-term, but you can't argue that the hardware is sitting idle. It's maxed out. Cathy is making a big shout in the world of autonomous mobility. She's saying $10 trillion in revenue within 5 to 10 years in a global economy of about $130 trillion.
Americans alone spend roughly $2 trillion a year on transportation, cars, gas, insurance, maintenance, parking. If autonomous vehicles can deliver transportation as a service at a fraction of that cost, the value creation is enormous. Cathy points to Tesla launching unsupervised rides in Austin this year, Waymo expanding, and the pace accelerating.
Cathy also points out China. She frames it as a positive for the US. Competition from Deep Seek and Chinese AI companies is pushing American companies to move faster. Arc's research suggests China is about 6 months behind on frontier models, which is close enough to keep the pressure on, but far enough behind that the US maintains its lead.
And that competitive dynamic might actually be speeding up the whole AI cycle. Competition tends to accelerate innovation, and right now both sides are running hard. If you enjoyed this video, please consider hitting subscribe. Cheers.
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