The AI Race: U.S. vs. China

The letters "AI" on a blue cyber background

The AI race is in full swing. China is chasing digital sovereignty, but there’s a glaring hole in that plan…it doesn’t have the advanced manufacturing capabilities to achieve it. Here’s the real kicker: nobody does.

China might be a bit more flexible with its ethics and data manipulation, but that means nothing without the advanced chipmaking equipment. China can produce less efficient chips, but has incredibly low yields on leading-edge chips. To produce the highest-level chips, there are roughly 65 countries involved in a complex supply chain.

Which means that not even the U.S. could go out and do this on its own (unless it underwent a 20+ year tech ecosystem rebuild). America’s real advantage in the AI race comes from the broad coalition of allied countries all working together to produce high-end semiconductors.

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Transcript

Hey everybody. Peter Zeihan here, coming to you from the top of little Castella, taking advantage of a break in the wind to answer a question from the Patreon crowd. Oh, by the way, that’s an ash mountain over there. And all of that is the Turner Ranch. Ted Turner, I guess, is a state, is a single largest landowner in the country. 

And that’s where he used to party. Anyway, the question is, is how is China’s artificial intelligence program coming along? They clearly don’t have any of the ethical restrictions that the United States has. And is that given them an edge? Is this something we need to worry about? Number one, I would argue that if you’re comparing the tech bro culture of Silicon Valley to China and the idea that one of them is morally superior, you need to do a little research. 

Silicon Valley, and especially the folks that are involved in AI, really don’t give a rat’s ass about your personal privacy and are perfectly willing to pillage your data in any possible form. In fact. Hey, I got a little visitor here. Hey, buddy. Yep. Never mind. He’s gone. Anyway, point being that if you are on Facebook or what is it now? Meta, whatever, any sort of social media whatsoever, all of your data is being mined actively in a way that the Chinese honestly sometimes have trouble keeping up with. And while the Chinese certainly do it with a little bit more flair, the AI Kings in the United States, the data kings in the United States have no problem getting all of the information that they need from you already. 

So the info influx really is not much of an issue. There used to be a moment when things had to be manually entered in, and the Chinese had an advantage of that for the numbers, but now AI has reached the point that it can self process. So again, that’s gone away too. So the structural issues really are not relevant. 

It really comes down to hardware. Now the Chinese are under export restrictions, so they cannot import the hardware that is necessary to make high end semiconductors, specifically the extreme ultraviolet machines that come from the Dutch company ASML. And without those, there’s no way they can make anything that’s really under seven nanometers reliably. That means that the reliant on importing chips and their export restrictions on anything coming out of the United States or Taiwan or Japan or Ireland, or any of the countries that make high end semiconductors, that limits them to approximately a 4 to 5 nanometer ceiling. Now, it’s not that those are bad chips at six nanometers. 

I mean, they’re fine, but if you want to do AI, it’s all about the number of computations you can crunch per chip and the power that takes per computation. And right now, in the rest of the world, the high end chips are in the 2 to 4 nanometer range, and we are now starting to get ships that were designed with coolant topography in mind. let me spell that out. What that means for an operational if you have a one gigawatt hyperscale data center, you probably have about a half a million GPUs on top of that. Lots of CPUs, lots of Dram, lots of Nand, different sorts of processing capacity, lots and lots of hardware. 

But the 500 GPUs or the core of it because large models. And when we’re talking about AI today, that’s what most people are discussing. Use those chips almost exclusively. And the better they are, the more computations, the more energy efficient per computation. The Chinese don’t have access to those 2 to 4 nanometer chips. Sometimes they can import some five and especially six nanometer chips. 

But they have made the decision that for sovereign control reasons, they don’t want to depend upon anyone’s imported chips. If they can make anything that’s even partially functional themselves really cool in. But there’s a middle ground. There’s a gray area because while the Chinese can’t import those high end chips in that high end equipment, they can still import a lot of equipment and a lot of gear. And they do that. They imported deep ultraviolet, DUV machines that are still pretty good and that are the basis for a lot more mature nodes. 

And they have used these to successfully make nodes as small as seven nanometers. Now I have to emphasize this. These chips kind of suck. They you generate about one third the computations per chip compared to what comes out of Asme and Taiwan. They generate about twice as much power, probably closer to three times as much power. Once you consider that the rest of the engineering of Chinese data centers, is that just that much worse? 

So you’re looking at overall one ninth efficiency compared to the leading edge stuff. On top of that, the yields for these seven nanometer chips is awful. It’s typically less than 30%. And as a rule, anywhere else in the world, any yield rate below 95% is something that wouldn’t be considered because it’s just such a massive waste of resources. 

China does the math differently, and they’re concerned with digital sovereignty and keeping them with the United States. But what it means is they need to build nine data centers for everyone in the United States in order to get an equal number of compute, and that is assuming the hardware can run the software that is required to do things like large language models. 

Bottom line, the Chinese are doing everything they can. They are sparing no horses, and they’re not even remotely close. They have tried over and over and over and over again for the last four years, to try to push past that seven nanometer limit, and they have succeeded in making a few emphasis on the word few chips, the meter level using technology. But it’s highly inefficient. And you’re talking about yields that are below 5%, nowhere near enough to supply a single data center, much less a raft of them. But before I laugh in their face, I have to say that the technology of AI is changing day by day, week by week, one by month, and the hardware is always two years behind. 

So I don’t want to rule it out there. Certainly motivated, if that’s the right phrase. But when it comes to the domestic manufacturing of the hardware that is required to do this, no, they’re just not even in the same game. Now, before anyone goes and toots America’s horn, the United States can’t make these chips either. Neither can Japan or Korea or Taiwan takes a team effort with 65 countries and 100,000 manufacturing supply chain steps and almost 10,000 companies. 

It really does take everyone. And if anyone is actually trying for real digital sovereignty, they’re going to fail unless they rebuild the entire tech ecosystem. And that is not something you do in less than 20 years. So are the Chinese going to fail at this by the rules of the game, as I understand them? Yeah. Are the Americans going to fail at this by my understanding of the rules of the game? 

Yeah, but the United States is part of a coalition of like minded countries that implement these technologies together. That’s how we do AI. And if the US decides to go it alone, it’ll be at best in China’s position.

My Two Cents on the AI Debate

ChatGPT logo with a synthetic brain hovering above

Hear me out…everyone has been yelling about AI the past few days, and the reality is that everyone is probably right, but it probably doesn’t really matter anyways. Let me explain.

When every industry leader raises concerns about a technology potentially becoming dangerous, it’s probably a good idea to listen. At the same time, both sides of the political aisle are making fair arguments for pumping the brakes or stepping on the gas. And you know the last time we’ve had a unanimous desire to discuss a new technology? The automatic loom.

So, yes. It’s a good idea to discuss the consequences of a transformative technology before it fully arrives, but supply chain issues will likely make this a moot point until the 2040s anyways. But hey, we love a good head start.

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Transcript

Peter Zeihan here, coming to you from Colorado. A lot of folks on the Patreon page have written in with questions about the artificial intelligence debates that have been happening in the last several days, so I thought I would put my two cents in. I don’t have a firm position. I’m kind of a weird belief that I think everybody is right, if that makes sense. 

So let me just kind of go through it. Number one, we’ve had some whistleblowers come out recently and say that within the artificial intelligence companies like Anthropic and ChatGPT. There is an understanding right up at the top that what they’re doing is dangerous and could be used badly and could get away from them. I have no reason to doubt those statements, and it would be very strange if this wasn’t a concern within the industry anyway. But keep in mind that this is something that has never happened before. And so predicting what path it’s going to follow is very, very thin. And so that’s all I have on that. 

Number two, there now seems to be a general agreement in public among the leaders of these companies that maybe we should slow this down a little bit for safety. But as the Speaker of the House said, we can’t really do anything with that because they all have different opinions on what the problem is and what should be done. Agreed. 

Third problem. Trump has basically said fuck all to the idea that we’re going to slow down at all because the Chinese won’t follow anything anyway. He’s got a point. Keep in mind that the United States spends about ten times as much on hardware, for the stuff that is necessary to run AI then the Chinese do, and then several times as much on the actual software. In terms of software, the most generous assessment I’ve seen of the Chinese is that they’re six months behind American companies. It’s probably more like 36 months. But when it comes to hardware, there’s no contest. The Chinese cannot make chips by themselves that are better than 28 nanometers. And you’re not going to run even a sloppy AI engine on something that is worse than, say, 14 or 15. And almost all the stuff that’s being done in the United States is on stuff that it’s five nanometers and smaller. So it really is night and day. And so from the Chinese point of view, they’re not close to where the United States is. So any sort of broad international agreement to hobble AI in any way means that they get stuck several generations behind American companies. So they would reject that out of hand. 

You put all this together and, you know, honestly, it’s not that I don’t see the concern. It’s that I actually see something really positive. You know, the last time the United States actually had an open, honest conversation about the effect of a technology….It was the loom, the electric loom. Back in the 1700s, Ben Franklin was the one who led that conversation. Since then, new technologies come along. They remake our culture and our society in the aftermath, we’re like, oh, wow, that was that was kind of rough. It was. Maybe we should have discussed that first. And so the fact that this is a hot button issue at really every level of society on both sides of the political aisle, I mean, hell, we’ve got Steve Bannon and who’s that freak from Vermont, Bernie Sanders. Basically joining hands to talk about artificial intelligence. This this is weird, but it’s good. 

So I’m not at the point yet where I’m really concerned at all. And then, of course, in the background of my mind, this is probably all moot anyway, because we’re going to lose the ability to maintain the supply chains that make these chips in the first place. And then we’ll have 4 to 6 years where the AI chips, capable chips that are in data centers will basically run, and then they’ll burn themselves out, and then we have to start all over. 

So this is a conversation that honestly doesn’t need to bear fruit until, say, like the 2040s when we rebuild those systems. And until then, I just think it’s really good practice. So, you know, great.

Korean Exports Skyrocket Thanks to AI

Two Korean flags in front of a building

Korean exports are up roughly 70% year over year, surpassing $100 billion in a single month. So, what’s causing this extreme growth?

It’s all thanks to AI. Korea dominates the global market for advanced DRAM, accounting for ~90% of global high-end memory. As long as the globalized supply chain supporting the AI ecosystem holds, countries like Korea will continue to reap the benefits.

Between chip design, manufacturing, raw materials, packaging, and testing, there is a fragile international AI network that won’t last forever. And no single country can do all of this alone.

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Transcript

Hey everybody, Peter Zeihan here come to you from smoky, Colorado. We are at the 1st of July, and we just got good data out of the Koreans for their exports. And they set not just a record, but an insane record topped $100 billion for country with 150 million people in one month. And that is a 70% increase from just a year earlier. 

You heard that right, seven 0% increase. And really, almost all of the increase has to do with artificial intelligence, as everyone who’s not brain dead is aware, there is an AI boom going on around the world, most notably in the United States, China and Southeast Asia. And there are three big components that go into the hardware that makes AI work. 

The first, the most famous, the one that gets the most press time, is the graphics processing unit. These are high end chips that are typically etched with extreme ultraviolet technology comes out of a company called ASML that’s based out of the Netherlands. And most of these high end chips are fabricated in Taiwan. About 80% of global supply. 

I’d argue right now the balance is mostly the United States. This is where the happens. 

This is the processing that is the core of what makes a large language model. And AI models like Llms work. So number one. Number two, you’ve got something called Nand, Nand which is cold memory. And so when you’re not using your computer or your data center is not using whatever the memory is, things are stored in Nand even if the power is off, Nand will keep its memory. 

And you have a lot of that sitting on the board in the general vicinity of the GPU just to absorb things that are not an act of play. And then third, you’ve got something called Dram, Dram, dynamic random access memory. And this is the hot memory. And so as data is going back and forth and back and forth and back and forth from the GPUs to other things, it’s usually the Dram that holds it temporarily. 

And it can be in two forms. You have your independent Dram stacks off to the side, and you have something called high bandwidth memory, which is basically a stack of Dram right next to sometimes even attached to the GPU. Anyway, the Koreans don’t do much, if anything at all with the GPUs, and Nand is an old technology where they’ve discovered because it doesn’t generate heat, you can stack the chips on top of one another. 

And so it’s not particularly advanced. The Koreans do a lot of it, but that’s not the groundbreaking stuff. What the Koreans excel at is the Dram, the dynamic access memory, the the hot memory, and they produce about 90% of the world’s high end dram. So three things from this. Number one, if you want to dominate your own computer supply chain system GPUs, which is what the Biden administration of the Trump administration are obsessed about, or only one part of the process. 

Computing is a lot more complicated than rocket surgery, and there are thousands more pieces that go into it than in any other manufacturing sector. So I would say it’s a fool’s errand to try to concentrate it in your country. But if you’re going to, you have to throw a lot wider net that we have in so far. Number two, memory is every bit as important as GPUs and especially the architecture of the memory and integrating it with the GPUs. 

And this is something that Chinese can’t do and the Taiwanese can’t do and the Koreans can’t do. This is something the US already does. So I’d argue that from a value added point of view, the United States already dominates the part that’s most important designing the system. So the geometry of the chips actually does what we need it to do. 

Third, and most important, I think in the midterm is that the same technologies that I have identified over and over and over again, the silicon processing, the carpet processing, the EUV system itself, all of the logistics and the supply chains and the inputs and the testing and the packaging, all of these things that require 50 odd countries in order to get the GPUs also, for the most part, applies to the Dram. 

So we’re existing in this little window where the world is technologically advanced enough and integrated enough that we can get the designs out of the United States and the logistics managed by the United States, and the photographs managed by the Japanese, and the copper out of Chile, and the rare earths out of China and the silicon out of North Carolina, and the GPUs out of Taiwan and the Dram out of Korea. 

And all just works right now. But you lose even one of those pieces, and this all stops. So if you’re into AI or you like the Koreans, enjoy this moment. It’s a good moment. Build everything you can, because very soon that’s not going to work. And we’re going to have to take a decade or three off from AI and its sister technologies. 

And till such time as we can rebuild the bulk of the supply chain in a more geopolitically sustainable manner.

The AI Race to Regression

The Open AI chatGPT logo on a phone

The AI race has been all the rage, but what if we were racing ourselves straight into regression?

OpenAI’s ChatGPT-5 is extremely powerful; however, it’s less user-friendly than its predecessor and is optimized for institutional users. Industrial and research applications are where the real power of AI lies. So, what happens when those energy-intensive data centers begin to falter?

Well, as globalization breaks down, that faltering is going to become a very real concern. Without an ecosystem that produces and shares all of the necessary components to make these AI behemoths run…we could see a technological regression that threatens the future of AI as we know it.

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Transcript

Hey everybody, Peter Zeihan here coming to you from McCurdy peak. Well, the actual peak is there. Anyway, Peter Zane Company from Colorado. Today we’re taking another question from the Patreon page. Specifically, can you please explain to me this new space age that we’re in the race for artificial intelligence, and what we should look for, what we should worry about? 

Well, let’s start by saying that most of the things that people are talking about with AI are generally, not quite on the mark, for example, a lot of folks think that, OpenAI, that’s the premier artificial intelligence company in United States, that their new program chat, GPT or 5.0, which is supposedly an upgrade, is actually a significant downgrade. 

They find it not as user friendly, not as personable, not as complete. That’s for personal users. AI affects potentially thousands of different applications, and how most people interact with artificial intelligence is in some sort of first person single seat. interface. Like what you get on your phone or your laptop. 

I mean, I’ve got that way too. And the jump from chat GPT four to GPT five was not designed for your single user. It was designed for people who do code for people who designed drugs. It’s designed to bring a huge amount of processing power to things on the back end to basically recreate something. So the institutional users, the design users, they’re actually finding ChatGPT all kinds of fun. 

And some Altmann, who is the CEO of open AI, is going back and kind of taking some characteristics from ChatGPT for to put it in the chat, GPT five, in order to make everybody happy. So that’s all going to work out. Here’s the problem. Software versus hardware. If I’m going to really sum it up, it’s that 

Chat GPT for the algorithm that we all found so groundbreaking really only took up about ten terabytes. And you could easily carry that on thumb drives in your hand. Chat GPT five, more advanced, is at least twice that, probably three times. But OpenAI is not saying. So we don’t know that number for sure. 

The point is, in terms of the raw memory required to make the AI function, it’s really not that impressive. And so if, the corporate espionage or an act of benevolence, OpenAI were to lose control of the algorithm and it got out there in the wild, so to speak, it really could be used by almost anyone. What makes a AI function in the way that we think of it today? 

Not this Skynet future thing, but how it is now requires massive amounts of processing power at data centers. The largest data centers that the world has ever seen are needed in order to deal with the inflow of requests that come in, run the algorithm and spit out the results. Which means that the limiting factor, for the moment, in artificial intelligence isn’t the software, it’s the hardware. 

And this is where we have a really big problem, and it’s not that far away. The ability to make the high end processing chips that Taiwan is famous for, requires, 100,000 steps, 30,000 pieces, 9000 companies, and they’re scattered around the world. The single biggest concentration is then the United States, which is something Americans conveniently forget when they’re talking about sovereignty. 

Number two, concentration is on the Taiwan centric zone. The single most important company is in the Netherlands, but it has facilities in Germany and in Austria and in California, in Japan. But you’re never going to be able to do the chips at all without all of these steps. And a lot of them are single point failures. 

So if you have any degree of globalization, it doesn’t matter really what the countries. It falls out of work. We can’t make them at all. And for the chips that we already have, life span when they’re in a data center is typically in the 3 to 6 year range. So when we get to the point where we realize that we can’t make the chips, we’re going to have a bit of a scramble to see who can control what’s left. 

And then the ability to use AI will shrink from something that you can all have on your phone to simply the handful of entities, whether governments or corporations, that are capable of having their own data center so they can run by themselves and that will be it. Until we reinvent the entire ecosystem and what we have been seeing with most government efforts around the world, including the United States, to reassure the sort of manufacturing it only focuses on the fabrication facilities, which is what is in Taiwan. 

It ignores the design, it ignores the material inputs, it ignores the photo mask, it ignores the wiring, ignores everything else that goes into a successful chip, much less the downstream stuff like testing and packaging that ultimately makes the stuff that ends up in a data center. No one, to my knowledge, is putting any effort into actually bringing the entire ecosystem under one roof, and I honestly don’t even think it would be possible anyway. 

There are too many pieces. There are too many players. And and if you’re looking at the United States, there are not enough technicians that are capable of doing it because we already have record low unemployment levels. So we are in a moment right now where AI is possible with ChatGPT 5.0 and all the rest that will not last. 

And in the not too distant future, we are going to see a technological regression as we lose the ability to make the hardware. And since it took us 60 years to figure out how to do that in the first place, it’s not something that we’re going to do in a season is going to take a mastery. Industrialization process of different parts of the world to do different things, coming together in different ways. 

And that is something that I am not looking forward to. But we’re going to see at the beginning of that within this next decade.

Will AI Steal My Job?

The world of international trade is constantly evolving, and it’s important to keep up with the latest trends and developments. From emerging markets to geopolitical conflicts, there are many factors that can impact global trade, and we’ll be discussing some of them today. So, grab a cup of coffee, sit back, and let’s dive into this exciting and ever-changing topic.

Go ahead and watch today’s video before you read the rest of the newsletter…I promise you’ll understand why that first paragraph was so painfully awkward!

If you watched the video, you can probably see why I’m not worried about my job security. While AI is going to change the way we do a lot of things, it still needs some time before it’s cracking the kind of nuanced jokes I’m famous for.

However, there are quite a few spaces where AI is already disrupting the job market, and if you don’t want to be fighting the machines…it may be time to adapt or pick up a new trade.

Prefer to read the transcript of the video? Click here

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TRANSCIPT

Hey Everybody. It’s Peter Zeihan. And today we’re going to talk about the future of global trade. Now the world of international trade is constantly evolving, and it’s important to keep up with the latest trends and developments. From emerging markets to geopolitical conflicts, there are many factors that can impact global trade, and we’ll be discussing some of those today. So grab a cup of coffee, sit back and let’s dove into this exciting and ever changing topic.

The world is changing fast and technology is a big reason why. Now you’ve probably heard about automation and A.I. and how they’re really shaking things up in the business world. I mean, who knew robots would be better the packing boxes than humans? Now we just need to make sure they don’t unionize. One thing we’re seeing is the emerging markets like China and India becoming major players in global trade. They’ve got big populations and are growing middle class, which means they’re buying more stuff. And that’s great news for businesses that want to sell to them. So if you’ve got a product, it’s hot in India, get ready to see those profits skyrocket. Just make sure you have a good recipe for curry because you might need to impress some clients. But there are some challenges to. The United States for example, it’s become more protective of its industries, which has led to trade tensions with other countries. And Brexit has made things a little bit more complicated between the UK and Europe. I mean, who doesn’t love a good geopolitical drama, right? And then there’s the going ons of the Ukraine conflict. Now I know what you’re thinking. Wow, this is getting heavy. But hey, on the bright side, it’s not all doom and gloom. You can still order your favorite Ukrainian vodka online. You have it delivered right to your doorstep. So let’s raise a glass to international trade, even in times of conflict. So what does all this mean for the future? Well, it’s hard to say for sure, but one thing’s for sure, we are in for a wild ride. And as a geopolitical strategist, I’ll be keeping a close eye on things and I’ll share my insights with you as we navigate this ever changing world. Thanks for tuning in. And remember, laughter is the best medicine, even when we’re talking about serious topics.

Okay, now, that was not my words. That is chat GPT. Who was asked to write a script? For me, it took about 60 keystrokes and it came up with that. Now, from a geopolitical analytical point of view of my own, it’s out of crap. It’s at best freshman, not even sophomoric. But remember that GPT is barely into beta testing right now.

And the fact that it was able to analyze what I’ve written and said in the past and pick up on my cadence and insert the odd joke, even if they were just horrible jokes, is an indication of what’s coming down the pipe. And for folks that don’t require my depth of knowledge in order to tease out things like the caveats and the long term forecasts, you got to admit that just kind of splattering that on the wall like spaghetti for a first try was disturbingly good.

Now this isn’t going to disrupt every industry, but now that the context and the grammar and the sentence structure is something that AI can do, we’re going to be seeing this get more and more mature as it builds in more information now from my point of view, as somebody who’s authored a few books, copy editors are in trouble now because this thing was flawless from a grammatical and copy editor, point of view and again, it generated this thing in less than a second. But when it comes to drawing connections between different topics or, say, diving into demography, all it knew was to say the word demography. And all it did was to say the word trade and protectionism. It doesn’t have a deeper understanding of what those mean in a broader context. We’re in a human context. So at the pace we’re going, my job is still good for probably the rest of my professional career. But for folks who are dealing with low value added white collar work or even mid value, where the strength is not the cross context and the cross disciplinary experience, but simply running the numbers. And I’m thinking here about basic accountants. This is a pretty problematic innovation for you. So the trick will be for folks who are a little lower on the value added totem pole to figure out how to use this technology themselves to leverage themselves among their peers. Using this, I probably could put together too much of a framework, but most people are not in my field. And in terms of teaching someone English, oh my God, what a great tool. So is it the end of the world for all of us? No. Are the machines rising up? Know clearly the value add in this system is still relatively limited, but it does have the capacity to form complete sentences in paragraphs and thoughts now, and as it gets better, it’ll start hanging ornaments on those in a way that we’ve already start to challenge those low and mid-level white collar jobs.

Now, the way the economy is evolving globally anyway, we’re going into a system where there’s more breakup. And as capital costs get higher because of the retirement of the baby boomers, we are seeing different industries suffering benefit in different ways. So for the tech industry, for example, having really, really cheap capital, a lot of people in their twenties and thirties is the lifeblood, and that’s not the world we’re in. And so we’ve seen significant layoffs. If they can’t maintain their output without inputs that are of lower cost. But as the world of globalized manufacturing is moving around and countries like the United States that still want stuff are going to have to build it themselves. Well, higher capital costs aren’t great for that. But if you are building something real in an environment of shortage, it’s relatively easy to get capital in even workers. What we’re seeing now is kind of the revenge of the real, as you will, as intangible goods no longer have the demographic and economic and capital situations that they need to thrive. But if you want to build industrial plant to build a real physical product, all of a sudden in relative terms, it’s gotten a lot easier because the Googles and the Facebooks of the world are not sucking all the oxygen out of the room and all the capital out of the markets. It’s part of the transformation.

Where Chat GPT is going to push in the opposite direction of a lot of those trends, which means that all those white collar workers who have done really, really well in the last 20 years suddenly have some competition. At the same time, that base inputs, capital and labor for their industry are starting to dry up somewhat. It’s a real reorientation, and if you’re in the bottom half of the income scale, you’re more likely to be blue collar.

You have a really, really good decade ahead of you. Okay, that’s it for me. I’ll see you guys later.