Hidden inside every swipe, search, and AI prompt is a fingernail-sized slab of silicon — etched with billions of switches — built in $20 billion factories using machines so precise they border on science fiction. And because only a handful of companies (and a few chokepoint countries) can make the most advanced chips, the semiconductor supply chain has become the real front line of the AI race and U.S.–China competition.
In this full length interview, Chip War author Chris Miller explains how microchips are made, why their production is so insanely hard to scale, and why the world’s economic future may hinge on a technology most of us will never see.
Timestamps
00:48 Chapter One: How to build a microchip
01:40 The center of our modern life
05:00 Inside the microchip
08:00 The unmatched pace of computing
11:32 Moore’s Law in the age of AI
14:07 The cutting edge of chip technology
16:56 Chapter 2: The first chip builders
20:00 Silicon Valley was built on chips
23:20 Chapter 3: Global impact
25:15 How the chip supply chain split apart
31:20 The manufacturing model that changed everything
37:36 The COVID-19 chip shortage
42:46 The ubiquity of chips in modern life
46:53 The CHIPS Act
48:00 Chapter 4: The AI revolution
51:35 The power problem
Transcript
The below is a true verbatim transcript taken directly from the video. It captures the conversation exactly as it happened.
When we think about technology, we think about social media, we think about search engines, we think about apps on our phones, but undergirding all of this are chips. The reason that technology that we think of exists is because every year chips get better and better. I think we’ve actually misunderstood what technology means. We think of the easy part, which is writing the software. But the hard part is actually manufacturing the chips that give us the advances in computing that enable us to have a computer on our phone or to attach devices to the internet. All that has been made possible by better and better semiconductors.
I’m Chris Miller, a professor at The Fletcher School and author of, “Chip War: The Fight for the World’s Most Critical Technology.”
Chapter One: How to build a microchip
Well, I first got interested in chips when I realized you really couldn’t understand how the world works without them. Whether it’s walking around your house and realizing there are chips in almost every device you rely on. Or trying to understand big shifts in international trade, there’s no good that is traded more than semiconductors. Or looking at the political dynamics around the world, with the US-China competition focusing on technology. Chips are at the center of all of these major trends.
A chip is a piece of silicon, often the size of your fingernail. And in it is carved thousands, or millions, in some cases billions of tiny devices called transistors, which flip circuits on or off. When they’re on, they produce a one. When they’re off, they produce a zero. All of the ones and zeros undergirding computing, undergirding data storage, all of your Instagram likes, all of your text messages, these are all just long strings of ones and zeros, which are created on the chip by these circuits flipping on and off.
The center of our modern life
There are a couple different categories of chips. Some chips process data, other chips remember data, and a third category turns real world signals, like audio or pictures into ones and zeros so that they can then be processed or remembered. And so when we look at the world, we see pictures. But when a phone, for example, uses its camera to look at the world, it takes in lots of rays of light, and then has to learn how to convert those into ones and zeros that can be stored. And so there’s very specific sensors for pictures, for sound, for radio waves that use semiconductors to convert these real world signals into strings in ones of zeros that can then be re-represented as pictures later on, for example, when you pull a photo up on your phone.
All of this is done by different types of semiconductors. So, generally, chips have a foundation of silicon, but there are dozens of other materials that are layered on top to make the transistors at such tiny scale. So a typical advanced chip could have several dozen materials. The foundation is silicon, but there are many other chemicals involved in the process. Yeah, it’s true that sand is from silicon and so are chips, but the similarities basically end there.
The silicon that’s used in manufacturing chips is among the most purified elements that we have. And the reason is that when you’re manufacturing chips with tiny transistors, you need to place almost every atom perfectly to make those chips work. Which means that if your silicon, or any of the other materials that you’re using, has even a single atomic impurity, it can cause defects in the way your chip functions. The production of the silicon wafers that are used in the chip manufacturing process requires extraordinary levels of purity. There’s really just four companies in the world today that are capable of producing silicon wafers at the right level of purity at the scale that’s required for contemporary manufacturing.
The good news is that there’s silicon everywhere. It’s one of the most widely-distributed elements in the Earth’s crust. The hard part is really the refining and the purification of silicon to make sure there aren’t any impurities that could disrupt the manufacturing process. So on top of your silicon, you could have boron, gallium, gallium arsenide, lots of different chemicals that are used, and every chip maker has its own proprietary process. So we don’t really know, inside of a typical chip, what materials are used, because chip makers usually keep it pretty secretive. That’s their special sauce that lets them manufacture chips with the right level of capability.
Now we’re not going to run out of silicon, nor will we run out of the other materials that are generally used in chipmaking. There are some concerns that certain materials are predominantly refined and processed in a single country. So for some of the materials like gallium and germanium, China produces around 90% of those materials. So there’s geopolitical issues that could interrupt supply, but it’s not going to be that we’re running out of the capability to produce them.
I visited a bunch of chip making facilities over the course of the research. The interesting thing though is that, when you go inside one of these massive facilities, called fabs, what you find is that there are huge machines and not much else. Because the manufacturing process has to be extraordinarily automated because humans are way too imprecise for manufacturing at nanometer scale. So nside of a chipmaking facility, there are very few humans, and lots of big machines that, from the outside, are impressive in their size, but you can’t see what’s actually happening because it’s happening at microscopic level.
Inside the microchip
There are a handful of companies that play a big role in the making of the machines that make chips. A couple in the United States, one in the Netherlands, and one other large one in Japan. Five companies play the dominant role in the manufacture of the machines that make chips. In some ways, it’s actually harder to make the machines that make chips than it is to make the chips themselves. Because these tools are among the most precise tools that have ever been deployed.
Just to give you one example, ASML, a company based in the Netherlands, produces machines that are used in the manufacture of almost every high-end chip today. And these machines are capable of manipulating materials at basically the atomic level to produce chips with billions and billions of transistors like those that are inside of your phone or that are used for training AI systems. So there’s a pretty small number of companies that make chips. And when you look at specific types of chips, you find that there’s even more concentration.
The biggest chip maker in the world is the Taiwan Semiconductor Manufacturing Company. When it comes to advanced processor chips, like the chips in your phone, or the chips in your computer, TSMC makes around 90% of them. So they’ve got an extraordinary market share, and are probably the most important semiconductor company, and arguably the most important company, in the world, because the chips that they produce, we rely on for basically everything. There’s been a lot of consolidation in the chip industry over the past couple of decades, and it’s been driven by economics and by technology.
Today, a single cutting edge chipmaking facility can cost $20 billion, one of the most expensive factories in all of human history. And so there’s just a couple of companies that can afford to put up that sum of money on a regular basis to build more and more cutting edge facilities. And to make that work financially, you’ve gotta produce a ton of chips. And so there are huge benefits that accrue to the largest firms. The more chips you produce, the more your cost structure makes sense, and the better your technology gets, because you learn from every chip you manufacture, you gather data from it, and you tweak your manufacturing process to make sure you’ve got fewer and fewer impurities at every step.
TSMC is both the world’s largest chip maker, but it’s also the world’s most advanced, precisely because it gathers more data than anyone else. Because chipmaking requires ultra-purified materials and hugely complex equipment, there’s not a single company that can do it on its own. Everyone requires a set of partnerships with supply chain providers to give them the materials, and the intellectual property, and the software and the tools that they need to produce advanced chips.
If you take for example, the primary processor inside of your smartphone, it was probably made in Taiwan, but it was made in Taiwan using chipmaking tools from the Netherlands, and from the United States, and from Japan. It was produced using chemicals from Japan, and then often assembled and packaged in Malaysia before ending up inside of your smartphone. And that’s typical. A typical chip requires components and materials sourced from dozens of different companies because the process is simply too hard for any one company to do on its own.
The unmatched pace of computing
So a nanometer is a billionth of a meter, and chips today are measured in nanometers. If you look at the chip inside of your phone, for example, and try to measure the size of the transistors, of which there will be billions on your smartphone chip, each one of these will be measured in a handful of nanometers. And so that makes them only slightly larger than atoms, smaller than any sort of living thing, far smaller than a bacteria, smaller than a mitochondria, half the size, for the most cutting edge transistors, of a coronavirus. There’s basically nothing we manufacture at such tiny scale as we do with semiconductors.
Every year, we make more transistors than we’ve made all other goods combined in all of human history. And in fact, nothing else really comes close. A typical smartphone chip could have 10 billion transistors just in the main processor chip. A big data center run by Google or Amazon Web Services would have more transistors than you could plausibly count. We know that we make more transistors than there are cells in the human body, for example.
We don’t even know how many we make in aggregate, because there are just so many. Moore’s Law predicts that the number of transistors per chip, and as a result, the computing power per chip will double every couple of years. And that’s been empirically true since the 1960s, which means that the capabilities of chips have gotten vastly better, and continue to get much, much better at a faster rate than anything else. So I like to think, for example, of airplanes to illustrate the difference.
If airplanes doubled in speed every two years from the 1960s up to the present, we’d be flying faster, literally, than the speed of light. But chips have done that. Chips have increased in that capability because the scale of the transistors has shrunk to the level that today we’re manufacturing them smaller than even viruses. And that has enabled the explosion of computing power, both in terms of the computing capabilities in high-powered data centers or in your phone, but also the application of computing to all sorts of devices.
‘Cause today, there’s computing everywhere. It’s in your dishwasher, it’s in your refrigerator, it’s in your coffee maker, it’s in your car. And it’s possible to put computing everywhere because today it’s so cheap, we can produce it almost for free. And that has enabled the application of chips to all sorts of different devices. To understand the change and the rate of innovation, in the 1950s, you could hold a single transistor in your hand.
Today, you can hold 10 billion transistors in your hand in a chip that’s the size of your fingernail. And that’s not an expensive chip, that’s a chip that often will just cost $50 or so. So the rate of shrinking transistors, as well as the rate of decline in their cost, has been unparalleled in any other segment of the economy. So before transistors, computers used vacuum tubes, which are sort of light bulb like-devices that would turn on and off, on and off to produce the ones and zeros.
They were cutting edge for their time, but they had huge inefficiencies. They wasted a lot of heat, for example, they worked pretty slowly. And they also, because they created light, attracted moths, and so computers had to be regularly debugged in the early days of computing, which meant removing moths from the lights that they were attracted to. You can see why it was hard to scale that up into a 10 billion unit system.
You know, I think the transistor is the key reason why we’ve been able to scale down. There’s really nothing else, if you look all across the economy, that has shrunk in size and shrunk in cost at that level. It’s done so not just for a couple years, it’s done so now for over half a century. That’s why when you compare progress in the computing industry to progress anywhere else, there’s really no comparison.
Moore’s Law in the age of AI
Moore’s Law is not a law of nature, it’s not a law of physics. We wish it were, because then we could rely on it to keep delivering advances far into the future. But it’s really a law of economics. It says that, if you’re able to find a way to shrink, shrink your transistors smaller, then you will be able to find a larger market as well. And that has incentivized huge investments in shrinking, in improving manufacturing processes, and making chemicals more purified to enable it, which has sustained this rate of advance.
And if ever it turns out that the economics are on Moore’s Law break down, the technology will immediately break down as well. Thankfully, the good news is that, right now, we’re seeing a new wave of excitement about ways you can deploy computing, which has led to a surge of new investment into AI, but also a surge of new investment into semiconductors, because it’s now clear that if we can shrink even further, we’ll enable a whole new era of advances in artificial intelligence that rely on even more computing than we’ve been able to muster thus far.
You can define Moore’s Law in a bunch of different ways. Is it based on the 2D size of the transistor, or the 3D size of the transistor? Is it based on the processing speed that comes out of it? And I think there’s a lot of people in the industry that are trying to sell a certain chip with given characteristics that have an incentive to say Moore’s Law, based on the other characteristics, has come to a halt. If you look at the rate of increase of machine learning semiconductors, for example, chips that are optimized for AI capabilities, they’ve been doubling in their capabilities every two years for the past decade or so. In other words, exactly what Gordon Moore predicted when he set out Moore’s Law in 1965.
My view is that when you zoom out and look at the rate of technological progress, there’s really no slowdown that’s happening. When I started my research on semiconductors, I thought that because chips were everywhere, chips were easy to make, and because nuclear bombs were only controlled by a handful of governments, they were hard to make. But what I realized is it’s actually the exact opposite. If you take nuclear weapons, that technology has barely improved since the 1960s.
It’s so easy to make nuclear bombs, even the North Koreans can do it. But chips are everywhere because they’re cheap and they’re tiny, and making things very inexpensive and very small is extraordinarily difficult, which is why there’s just a couple companies in the world that can do it at the cutting edge. The reason is that it’s brutally expensive, and it requires manufacturing processes that get better, and better, and better every single year. If you’re trying to catch up to the cutting edge in the chip industry, you’re not trying to catch up to a static cutting edge, you’re trying to catch up to a cutting edge that is racing forward at the rate of Moore’s Law, doubling every two years.
The cutting edge of chip technology
It’s a race between companies, but it’s the fastest race humans have ever undertaken, which is why it’s extraordinarily difficult to reach the cutting edge. A couple years ago, it became harder to shrink transistors in two-dimensional format. For a long time, chips were made, they were just described as planar chips, chips in a plane, in which all the transistors were on the same level. Now we’ve started making transistors that have three dimensions, because we’re learning to stack them on top of each other to package more of them together in a way that produces more computing power.
One of the key trends over the next couple of years is going to be more 3D construction of groups of transistors, which will enable more of them to be crammed into a small amount of space. So the machines that make chips are extraordinarily precise in their manufacturing. For example, there are tools that can lay down thin films of material that are just a couple of atoms thick with basically perfect uniformity. And to pattern the transistors on a piece of silicon, you use a tool called a lithography tool.
And today there’s one company, ASML, of the Netherlands, which makes most of the world’s lithography tools. And for the most advanced chips, these tools can cost $350 million a piece for a single tool. And they cost so much because they require some of the most precise components ever used, like a mirror that’s the flattest mirror humans have ever made, a laser that’s the most powerful laser ever deployed in a commercial device, and a ball of tin that falls through a vacuum that is struck twice by that laser, explodes into a plasma measuring 40 times the temperature of the surface of the Sun, and this plasma emits light at just the right wavelength, 13.5 nanometers, to be bounced off the mirrors in exactly the right geometry and land on your chip to carve the transistors into the silicon. It’s the most complex and expensive machine that humans have ever made, and it’s required to make all of the most advanced chips.
Today, there are just three companies capable of producing cutting edge processor chips, the types of chips that go in phones, or computers, or are used for AI. It used to be a larger number of companies that could produce at the cutting edge, but it’s shrunk into three, and might in the future shrink only to two for two reasons. First, the expense is extraordinary.
$20 billion per facility is a level of spending that many governments can’t afford, to say nothing of companies. But second, the scale required to manufacture efficiently is vast. And that means that the benefits accrue to the largest firm. And in this case, that’s TSMC, the Taiwanese firm that’s at the center of the chip industry. That’s why they manufacture on 90% of the most advanced chips, because they’re cheaper, and they’re better than their competitors when it comes to manufacturing.
Chapter 2: The first chip builders
In the middle of the 20th century, all telephones were managed by AT&T. They were a monopoly, and the government regulated them, and one of the rules was that their research lab had to share its inventions with the rest of the world. And they had some of the most brilliant physicists and chemists working in the world at that time, which they hired to improve the phone system. But in the process, they created some of the key inventions that drove technological progress in computing for decades to come.
The transistor was one of the inventions that emerged out of Bell Labs, but actually many of the processes that are used to both design and manufacturer semiconductors today were first pioneered by researchers working at Bell Labs. But because Bell Labs wasn’t a computer company, they were able to take those technologies and either spin out their own startup or sell it to somebody else. And that’s how many of the key technological advances undergirding semiconductors first emerged. So William Shockley, John Bardeen, and Walter Brattain invented the first transistor while they were working at Bell Labs.
They were initially planning to use these transistors as part of the telephone network. But in the late 1950s, the first engineers realized that you could take multiple transistors, and make them on a single piece of semiconductor material. And so that was the first chip, a piece of material with multiple transistors carved into it. And that was important, because if you had individual transistors, they were connected via wires in a way, that was okay if you had a handful of transistors.
But if you had 1,000 connected together, you had a jungle of wires you had to manage. But the chip managed to have the electrical connection in a piece of material. And so the jungle of connections was replaced by a single block of material, which was much more reliable, and also much more easy to shrink in its size. And so it was the invention of the chip that made it possible to deploy lots and lots of transistors together in a way that was economical, but also possible to engineer and avoided all of the wiring.
The first chips were invented by engineers working at Texas Instruments and a company called Fairchild Semiconductor in Silicon Valley. They were invented simultaneously. Jack Kilby invented one in 1958 working in a Texas Instruments lab. And for a long time they were really at the cutting edge of chip manufacturing. At first, they were building chips primarily for the U.S. government, for the space program, for example, and for weapon systems.
But they realized early on you could take the exact same chips that the government wanted to guide spacecraft, and use them for commercial applications, like computers or pocket calculators. And that set the industry off into its first phase of growth in the 1960s and ‘70s and ‘80s.
For the past 15 years, they’ve taken a different tack. They don’t today produce chips that are used in computing, they’re not, for example, in AI systems in a large way. Instead, they produce a lot of chips that are in industrial applications, or in automobile uses. And so Texas Instruments chips are all around you, but you don’t see them because they’re buried deep in your devices, making sure your windshield wipers work, for example, on your car, or that your windows move up and down when you press the button. Those are the types of use cases that Texas Instruments produces chips for.
Silicon Valley was built on chips
One of the first startups in Silicon Valley was created by one of the researchers who invented the first transistor, William Shockley, who was by all accounts, a brilliant physicist, but a horrible manager and a horrible person. He hired a very talented set of engineers in Silicon Valley. He moved to Palo Alto, California, where his mother lived, for the purpose. Although he hired lots of great people, they detested working for him.
Eight of them in the late 1950s went out on their own, and created Fairchild Semiconductor, which became one of the key startups that would give rise to Silicon Valley, and played a major role in Silicon Valley even being named Silicon Valley, because for a long time it was the absolute epicenter of chip design and manufacturing thanks to people at Fairchild Semiconductor. Robert Noyce, one of the two inventors of the integrated circuit, Gordon Moore, who later would go co-found Intel, and many others first started their career working at Fairchild.
Intel was founded in 1969, and it initially planned to focus on making memory chips. But they realized early on that there was a potentially larger market for a type of chip that wouldn’t just remember data, but would also process it, especially if that processing could be programmed in different ways for different use cases. And it quickly focused on making chips for personal computers, which at the time was a very small market, but they correctly bet that soon, everyone, would have a personal computer.
Intel, even today, is the world’s largest producer of chips that go inside of PCs. Gordon Moore is one of the two co-founders of Intel. He’s most famous today probably for coining the term Moore’s Law, but he also played an absolutely critical role running Intel’s R&D operations from the earliest days for many years. And when it came to the microprocessor, he was an early advocate of focusing on microprocessors at the expense of the more memory-focused chips that Intel had previously made.
In some ways, he was the key figure in Intel in making the company focus on microprocessors. A tiny computer on a chip, as they originally called it. And it gave rise to the idea that you could deploy chips in lots of different use cases without having to redesign the chip itself, because the chips themselves could have a program running on top of them.
Today, we take it for granted that you can have a chip in your phone, and a chip in your dishwasher, and a chip in your car. But at the time, that would’ve required many different chips for each of those purposes. Whereas, today, thanks to the microprocessor, we have programmable chips.
That was the main source of revenue for the chip industry, the main focus of technology, until about 20 years ago when the first smartphones began being produced. And today, smartphone chips are generally designed by one set of companies, but they’re manufactured largely in Taiwan. So the largest designers of smartphone chips are Apple, which designs its own chips in California. Qualcomm, and other companies, almost all of them manufacture all of the chips that they design in Taiwan.
Today, the chip industry is split into two different parts. There’s the chip designers, which, today, is essentially like a type of programming where each of the transistors goes on the chip, and the actual manufacturing takes place generally in Taiwan or elsewhere in East Asia, where different companies specialize in manufacturing at precision scale.
Chapter 3: Global impact
The chip industry was a global industry from really the earliest days. Fairchild Semiconductor was founded in Silicon Valley before it was even called Silicon Valley, but they opened their first facility in Hong Kong just a couple years later. So there was already a globalized nature to the chip industry from day one. But one of the things that’s changed a lot over the past couple of decades is that, today, each region focuses on a different part of the semiconductor supply chain.
The first chips that were invented in the late ‘50s and early ‘60s were used for space programs and missile systems. So they were at the center of the Cold War competition. And the U.S. was ahead, but the Soviet Union realized that they also needed chips to guide their missiles more accurately or to help their spacecraft launch effectively. And so they were focused on building their own chip industry, but also on copying whatever they could from the West.
Since the earliest days of the Cold War, there were Soviet exchange students in physics, for example, studying at Stanford University, but also transmitting the knowledge that they gained back to the Soviet Defense industrial complex. And so there was a lot of copying, a lot of efforts to replicate what the U.S. was doing. But the Soviets made a couple of key errors.
One was that they focused too much on copying, and not enough on innovating. They got very good at copying, but not so good at innovating, and that left them behind. The second error they made was that they only focused on the military aspects. The military was where the first chips were used, but today, most chips go to the private sector. 99% of chips that are made go into phones, or PCs, or data centers, not for defense equipment.
If you only focus on the government and military uses, you’ve got a tiny market relative to the vast consumer market that was out there. U.S. firms were profit-seeking, they focused on the consumer market as early as they could. In the Soviet Union, they never made that shift, and so their chip industry was always tiny in comparison to the U.S., which meant they could invest less, they could hire fewer workers, and ultimately their technology fell behind even though they were pretty good at copying.
How the chip supply chain split apart
In the U.S. right now, most of the key chip firms only design chips. Most of the manufacturing of chips happens in East Asia, in Taiwan, for example, or in Korea. Many of the chemicals that go into chipmaking come from Japan. And the machines that are used to make chips come from either Silicon Valley, where some of them are still made, or the Netherlands or Japan.
The industry has globalized, but it’s also specialized in the process. And so there’s not a single region today that can make cutting edge chips on its own. Everyone relies on this internationalized supply chain that brings together the U.S., Taiwan, Europe, Japan, and Korea. Japan was a major player in electronics assembly early in the 1950s and 1960s, so devices would be assembled in Japan because labor costs at the time were lower.
But Japanese firms were fixated on moving up the value chain, producing more complex, more expensive types of goods. And Japanese firms realized very early on that consumer electronics could be a major growth area for them, where they could sell not just domestically, but all around the world. And so companies like Sony, which were among the leaders in the 1970s and 1980s, bet on the consumer market to produce the types of goods that would take advantage of the advanced chip technology that they were pursuing at the time.
Although we don’t remember it much today, devices like the Sony Walkman in the 1980s was at the center of the tech industry, and it put Japan really on the map. And at that point, Japan was, by a lot of metrics, just as capable as the United States when it came to building advanced chips and then deploying them in very profitable uses like the Sony Walkman. One of the places where the Japanese excelled was in video games, which most people might not think of as driving technological advances, but actually, the computing that’s required to show graphics that look real life is extraordinarily complex.
The Japanese companies like Sony, Nintendo is another one, were fixated on how to make better graphics, and it required more and more computing power to make better and better graphics. And today, they’re no longer major players in that sphere, but NVIDIA, which is the central player in AI, actually started as a video game company, it made graphics cards for computers. And for most of their early history, they were selling chips primarily to gamers, because the graphics were better and rendered more rapidly.
But it turns out that the same essential math that’s used for showing graphics on a screen is pretty similar to the math that’s used in training AI systems. And so NVIDIA was able to take chips that were made for video games, and made for computer games, and pivot them to be used in AI systems, which is why a video game company that was founded in the 1990s has now become not just any AI company, but the most important AI company in the world. In the 1980s, the South Koreans saw Japan becoming a major player in the chip industry and saw Japanese firms rise to the top, both in terms of technology and in terms of the amount of money they were making, selling both chips and devices that used them, and South Korea wanted to replicate Japan’s strategy.
So companies like Samsung and SK Hynix were founded to establish chip industries in Korea. And they replicated the Japanese model, they get very good at manufacturing, they competed very effectively on cost. They also represented an alternative to Japanese production. ‘Cause U.S. firms in the 1980s were very worried that Japan was going to take over the chip industry. So they were excited to have another option besides Japan, and shifted business towards Koreans, both because the Korean producers were cost competitive, but also because it provided a bit more diversification in the industry that would limit the ability of Japanese firms to dominate.
One of the biggest European chip makers in the 1960s, ‘70s, and ‘80s was the Dutch company Phillips, which today still exists, but doesn’t produce any semiconductors. They got out of the semiconductor business several decades ago. But one of the legacy units that they’d created was a unit that made the tools that make chips. And in particular, they focused on the lithography tools that are capable of patterning transistors on a chip.
ASML was spun out of Phillips several decades ago, and at the time, most people thought it would likely fail, the Netherlands wasn’t a big part of the chip industry, Silicon Valley was a long way away. But ASML took a series of pretty wild technological bets on technologies most people thought would fail. And the best example of this is the current cutting edge of lithography called extreme ultraviolet lithography, the tools that cost $350 million a piece to produce, everyone else thought that was a technology that would never work.
It took three decades to commercialize, tens of billions of dollars of research and development money went into it, but ASML made that bet, and it was a bet that looked like a very bad bet for many years until about a decade ago when they first were able to build the initial EUV lithography machines. So chip makers have always used lithography to manufacture semiconductors, but as transistors have gotten smaller and smaller, we’ve needed better and better lithography systems to print smaller transistors onto silicon chips.
And several decades ago, it was clear that the cutting edge in lithography at the time was going to be too broad in terms of the wavelength of light used to print tiny transistors. The cutting edge used light with a wavelength of 193 nanometers, which sounds really small, and it is really small. But if your transistors are measured in 10 nanometers, or 5 nanometers, 193 nanometers is still too broad of a brush with which to paint your transistors on the silicon chip.
And so ASML bet on a new type of lithography system using light with a wavelength of 13.5 nanometers, much more narrow. Which sounds logical, but it was extraordinarily difficult to produce. Research started in the early 1990s, and it took 25 years before these machines were commercialized, because it required building a supply chain that involved these extraordinarily complex components, the flattest mirrors humans have ever made, the most powerful laser ever in a commercial device, all of these had to be invented in the process of making these machines work.
The manufacturing model that changed everything
Taiwan was a major player in electronics assembly, and putting together transistor radios, for example, in the 1950s and ‘60s, or assembling televisions. And they did quite well on that, but there’s not much money to be made in the assembly, the money is made in the manufacturing of the complex components involved. And so the Taiwanese government realized, as early as the 1970s, that they needed to move up the value chain and learn to do the more complex parts of electronics manufacturing.
In 1987, there was a American engineer named Morris Chang who was passed over for the CEO job of Texas Instruments where he’d worked for several decades. And so he left TI, and was looking for something else to do, and he’d gotten to know the Taiwanese government for several years, because Texas Instruments, his former employer, operated a number of plants in Taiwan. And so the Taiwanese approached him and said, “Would you like to build a chip factory in Taiwan?” And he said yes.
And he had an idea, which was to do manufacturing differently than anyone else. At the time, most chips were manufactured and designed by the same companies, but Morris Chang realized that manufacturing is getting more and more complex every single year, that if you specialized on manufacturing, you could manufacture better than your competitors. And so he established TSMC in Taiwan in 1987 with the aim never of designing chips, only of manufacturing.
His vision was sort of like to do for chips what Gutenberg had done for books. Gutenberg didn’t write any books, he only printed them. Morris Chang didn’t wanna design any chips, he only wanted to manufacture them. That’s exactly what TSMC has done. And it’s enabled TSMC to win among its customers, some of the largest companies in the world, Apple, NVIDIA, Qualcomm, AMD, they all rely on TSMC to produce its chips, which means that TSMC is the largest chipmaker in the world by far.
And as a result, it’s got more scale, it can drive down its costs, and it can hone its technology more than anyone else. And so TSMC, thanks to this unique business model, is both the largest and the most advanced chipmaker in the world. Today, China’s the world’s largest importer of chips. They spend as much money each year importing chips as they spend importing oil.
There’s nothing that China’s more reliant on the outside world to purchase. And China imports all these chips, both for its own use, but also because most of the world’s phones and computers and servers are assembled in China. So there’s a flow of chips into China, they’re assembled in the devices, and the many of those devices are re-exported to the U.S., or to Europe, or to Japan, or to international markets.
And so today, China’s primary interface with the chip industry is by buying chips, assembling them, and then shipping them abroad. But the Chinese government realizes this is not the best place in the industry to be. They wanna do the higher value add parts of the industry, just like Taiwan did, just like Japan did to move up the value chain. And so for the past decade, China’s been trying to build its own chip industry to manufacture more chips domestically.
And right now it’s having a lot of success when it comes to more low-end chips, the types of commodity chips that are in many different types of devices, where China is vastly expanding its manufacturing capacity and making real strides towards becoming a lot more self-sufficient. But at the cutting edge, the types of chips that are inside phones or in AI systems, China’s still meaningfully behind industry leaders like TSMC. Right now, the most advanced Chinese firm, SMIC, is about five years behind TSMC, which might not sound like a lot, but that’s two and a half Moore’s Laws behind TSMC, which means that, for the most cutting edge applications, you really take a performance hit if you want to use a Chinese manufacturer versus a Taiwanese one.
Until 2020, TSMC’S two largest customers were first, Apple, the biggest U.S. smartphone maker, and second Huawei, China’s largest phone company. TSMC manufactured ships for both of their phones. But the United States is worried that Huawei is controlled by the Chinese government, it’s worried about the surveillance capabilities that this might enable, and so the U.S. has been trying to limit Huawei’s access to advanced technologies.
And since 2020, it’s prohibited Huawei from manufacturing advanced chips at TSMC. And so Huawei’s had to turn to domestic suppliers to manufacture many of the chips that it needs. And this has been a challenge, it’s possible to find Chinese domestic suppliers, but they’re not as good as TSMC, the costs are higher, the performance is lower. And it’s been a real headwind for Huawei over the past couple of years as they’ve tried to build their own supply chain to make up for the fact that they’ve lost access to the cutting edge in Taiwan.
So until recently, India was a very small player in the chip industry. There’s a couple of chip companies in India, but they’re not at the cutting edge, and they’re not that large. Much of the semiconductor manufacturing, as well as the rest of the supply chain, the assembly of phones, for example, of computers takes place in Southern India. Tamil Nadu, for example, is one of the key hubs for manufacturing. And then Bangalore is a major center for chip design inside of India.
But right now, India is the country that’s changing the most rapidly, I think, when it comes to investment in semiconductors. There’s a series of new projects underway in India to put it more on the map of electronics manufacturing. And I think if you look at India today, you see what China looked like 30 years ago, or what Taiwan looked like 50 years ago, a country that’s on the early stages of a major change in the types of manufacturing that happened there. And so I wouldn’t be surprised at all if in 10 or 20 years we looked at India as a really central player in the production of all the computing and electronics that we rely on, because they’re taking the exact same steps that China, and Taiwan, and Japan before them took when they were becoming major manufacturers.
The irony of the chip industry is that it’s simultaneously globalized, and yet extraordinarily localized for certain types of production. And that’s inevitable I think, because the engineering involved is so complicated, the dollar values required to spend are so vast that we need specialization. And specialization implies that we’ve got to rely on other people to help in the process. And so I think it’s inevitable that U.S. firms will rely on manufacturing in Taiwan, and chemicals from Japan, and the rest of the supply chain for a very long time because no one has the capabilities they need to produce the chips that they require on their own.
The COVID-19 chip shortage
During the pandemic, the supply and demand dynamics on the chip industry were out of whack. Because a lot of people ordered new computers, for example, to work from home, and so PC production shot up in ways that weren’t expected, or people bought fewer cars in the early days of the pandemic, and so car production declined. And companies couldn’t predict what type of chip they would need. The effect of that was to create shortages of certain types of chips, when demand roared back in the later stages of the pandemic.
Car companies in particular found they couldn’t get the types of chips that they rely on to produce cars. And that was something they hadn’t focused on for a long time, they thought of their supply chain as being about engines, and wheels, and axles, and other parts of the car that you think of when you think of car parts. But today, contemporary cars require a lot of chips, hundreds or even thousands of chips for the most sophisticated cars. And the thing about cars, if you’re missing just one chip, your car often doesn’t work.
And during the pandemic, car companies found themselves often in that situation. Just a single chip, often even the cheapest chips, were causing them to have to leave cars in the factory parking lot as they waited for the right chip to arrive. And that illustrated a couple of things. First is that complex manufactured devices, like cars, need a lot of chips. Second, they don’t just need the same type of chip, they need a thousand different types of chips produced by different manufacturers.
And if even one of those is late, the car has to wait until it arrives. And the third thing it illustrated is that it’s not just the tech sector that needs chips, it’s actually everything. It’s cars, it’s tractors, it’s medical devices, all of these faced shortages during the pandemic because they couldn’t get the types of chips that they needed.
And the really interesting thing about the pandemic that most people don’t realize is that we didn’t actually produce fewer chips. We actually produced more chips each year of the pandemic. The problem was that supply couldn’t keep up with demand. And we had demand in segments in the industry that we weren’t expecting. That created hundreds of billions of dollars of losses for manufacturers like automakers, because they couldn’t finish the goods that were sitting in their factory parking lots, and therefore couldn’t sell them.
And that matters, because the shortages we saw in 2021 and 2022 are tiny in comparison to the shortages we would see if something happened to a large scale chipmaker, like those in Taiwan. Anything that disrupted chip production in Taiwan would be catastrophic for the world economy, for the United States, for Europe, for Japan, for everyone, because everyone relies on chips made in Taiwan. Earthquakes are one thing that could cause problems.
And the reality is that Taiwan’s had a lot of earthquakes, so they’re pretty well prepared. And chip facilities, because they have to be extraordinarily safe from vibration, they’re actually among the most earthquake-safe buildings that exist today. So it’s not a guarantee, but it means that they’ve done a lot in terms of ensuring themselves from earthquakes. Water is one of the materials that’s actually most widely used in chip manufacturing for a number of the manufacturing steps.
And it needs to be ultra-purified water too. And so chip plants have to draw huge volumes of water from the local water supply, and then try to recycle that at the end to make sure there aren’t any chemicals that are being discharged back into the environment. And it’s a major challenge for chipmakers, because the volumes that they use are huge. And many of the places where chips are manufactured don’t have surplus water. So in Taiwan, droughts have been an issue many times in recent years, and it’s a major limitation on TSMC’S ability to expand its manufacturing footprint in Taiwan.
The other is energy. Electricity is very important for chipmaking, and as we use more advanced chip making tools in factories, they require even more power to operate. And so electricity is a second limiting factor as well. And especially as countries try to use more green energy, that creates more challenges, because you need both more energy, but also you need energy that’s perfectly reliable. And so the Sun or wind power can’t always be relied on.
Which means that if you’re in Taiwan trying to map out your future power supply, you’ve got a limited number of options to look at. I think the bigger risk is not seismic, but rather geopolitical. It’s that China carries through on the threats it regularly makes to use force against Taiwan to take control of the island. And for a long time, I think people wrote off that risk as unlikely, because for a long time, China was weak, and the United States was pledging to protect Taiwan.
But today, China’s getting stronger every single year, its military capabilities are growing on a regular basis. And this has raised questions about whether we need to worry that China might at some point move on Taiwan. And the problem is that even a small move, a small conflict would be disastrous for the chip industry, because it’s not just about the security of the facilities themselves, it’s also about the supply chain.
Taiwan needs to import energy, needs to import chemicals, materials, tools, spare parts, many of which come from abroad, from Japan, from the United States, from Europe, energy coming in from the Middle East. And if any of this is disrupted, chip production could break down. And if chip production in Taiwan breaks down, that matters for everyone, because everyone uses Taiwanese made chips.
The ubiquity of chips in modern life
I like to think of cars as a case study in how we rely on chips for almost everything. If you sit in a new car, it’ll have, on average, 1,000 chips inside of it. It’s a chip that makes the window move up or down when you press the button. It’s a chip that manages the windshield wipers going back and forth. If you have any sort of autonomous braking features in your car, there’s a chip that manages the sensor, a chip that sends that information to the brakes to step on the brakes if there’s a object in front of your vehicle.
If you’ve got a internal combustion engine, there’s a chip that manages fuel injection into your engine to make sure it’s operating the right way. There’s of course, a chip that’s attached to your GPS, multiple chips in the display that tells you where to go when you’re looking for directions. I’ve only mentioned a dozen or so chips, and there are several hundred more that make your car work the way you expect. And cars are not really unique.
Today, everything that we rely on, almost anything with an on-off switch has at least one, and often dozens or hundreds of chips inside. The other way to think about the ubiquity of chips is just to walk around your apartment or your house, and look at the devices. The dishwasher, the microwave, your coffee maker, your washing machine, any sort of consumer electronic you have, they all require chips. And it’s often not just one chip, it’s often a fair number of chips.
And the more complex the chip, the harder it is to make, and therefore, generally, the more companies can charge for selling it. So the chip in your smartphone, for example, that runs the operating system, is extraordinarily complex, billions of transistors, it has to operate at extraordinary speed, draw on as little power as possible because your battery life is constrained. And so having perfectly optimized smartphone processors is really important. Which is why Apple designs its own smartphone processors in-house.
It doesn’t trust anyone else to do it. And so those chips are really expensive, compared to many other types of chips that you’d find in a dishwasher or a washing machine, which can cost less than a dollar, because they’re not required to do anything particularly complex. And the reality is that, as devices get more advanced, as we have more and more things connecting to wifi and Bluetooth, more sensors, more AI capabilities installed in devices, we’re gonna be using more and more chips as far as we can see into the future. Both China and the U.S. see chips as really central to the technology competition between them right now.
China’s worried that because it relies on importing chips from Taiwan and from Korea, which are both U.S. allies, it’s gonna be cut off in the future from getting the chips that it needs. And right now, that’s already happening to some degree, the U.S. is limiting the ability of AI firms like NVIDIA to sell their most cutting edge chips to China, because the U.S. wants to keep the most advanced AI capabilities for itself. And so China’s concerns are understandable.
The U.S. is worried that if it sells advanced AI chips to China, they’re gonna be used not for optimizing food delivery apps, but used for military and intelligence use cases. And the U.S. is not wrong to believe that, because just as companies are trying to figure out how they’re going to use AI, it’s already the case that militaries and intelligence agencies are deploying AI to optimize their systems too. And so both countries recognize that chips will be at the center of the AI race, and as a result, they’re trying to improve their position, become more self-sufficient, and prevent their technology from benefiting their competitor.
As of 2022, the U.S. has made it illegal to transfer the most advanced AI chips made by companies like NVIDIA to China. So today, if you’re a Chinese firm, you can access a less advanced NVIDIA chip that’s been specifically downgraded to meet the U.S. restrictions and is now legal to sell to China. But if you want the cutting edge, you’ve gotta go abroad. And the aim of these regulations is to give U.S. firms an advantage.
To make sure that U.S. companies are leaders in AI, and that the U.S. gets to write the rules of how AI will play out. And so Chinese companies in the AI industry face a disadvantage as a result, they’ve got worse chips, which means that the cost of training AI systems is higher, it takes more time, it’s more inefficient. And that’s the U.S. goal, to kind of throw sand in the gears of China’s AI ecosystem, and hope that the U.S. can race ahead as a result.
The CHIPS Act
There were two concerns that prompted the Congress to pass the CHIPS Act. The first was reliance on Taiwan for our most advanced chips. And the second was a fear that the technological edge that the U.S. has vis-a-vis China was narrowing as China invested more and more. And so in 2022, Congress put forward around $50 billion to invest in the U.S. chip industry.
Part of that money goes to directly incentivizing companies to build new manufacturing facilities in the United States, which in the past, they hadn’t been doing much, they’d been relying on suppliers in Taiwan and Korea instead. And part of the money would go on R&D, building better chips, better chip making equipment, better chemicals used in the chip manufacturing process to help U.S. companies stay ahead of their competitors. Because the U.S. government believes, and I think they’re justified in believing this, that keeping a technological advantage in chips is key for retaining your advantage in a whole set of industries that are downstream of semiconductors. And as we deploy AI in all sorts of different segments of the economy, you can already see that playing out.
Chapter 4: The AI revolution
The biggest change in the past couple of years has been the explosion of investment in AI. The release of ChatGPT in late 2022 encouraged all the big tech firms to spend tens of billions of dollars building vast AI infrastructure, which means data centers full of the most capable semiconductors. And I think right now we’re seeing just the early phases of a new wave of investment in an AI industry that is just emerging.
And if we know one thing, it’s that this industry will require a ton of semiconductors. Because one of the key trends in the history of AI is that more advanced systems require being trained on larger volumes of data. If you wanna train a system on more data, you need more computing power, which means better chips to train it. And so today, companies like OpenAI or Anthropic are spending millions and millions, and soon billions of dollars training their AI systems.
And most of that budget goes to buying chips, buying ultra-advanced semiconductors from companies like NVIDIA. So to train a cutting edge AI system requires tens of thousands of NVIDIA’s most cutting edge chips. It requires using these chips for days, or sometimes months on end. So you’re investing hundreds of millions of dollars, if not billions of dollars in data center capacity, and using the data center solely for the purpose of AI training.
And you need the most advanced chips inside, because the most advanced chips are twice as good, on average, than the prior generation due to Moore’s Law. And so there’s a strong incentive to buy the best chips that NVIDIA has every single year, because it actually drives down your training costs, even though the chips themselves are extraordinarily expensive. One of the key challenges of AI is gonna be to drive down the cost of deploying AI systems.
So we know how to train big systems right now, that’s what open AI and Anthropic and others are doing. But to make AI really widespread across the economy, we need the cost of using it to be so cheap we don’t even think about it. It’s sort of like Google Search today. No one thinks, “What’s the price of my Google search?” Because it’s approximately zero.
Google spends a bit of money on the data centers, but it’s so low, you don’t have to think about it. Today, AI is actually pretty expensive. A single query to ChatGPT is an appreciable amount of money, such that sometimes OpenAI has to slow the rate at which it rolls out new capabilities, because it’d be too expensive to actually deploy. There are a lot of companies that are exploring, how do you do deployment more efficiently?
And there are a number of startups that are pioneering new models of chip design that are intended to increase the speed and drive down the cost of deploying AI models. Which I think is gonna be really important in making AI cheap enough, and therefore prolific enough to make a major impact on the economy.
NVIDIA’s chips, which are at the center of the AI ecosystem right now, are pretty general purpose in their capabilities. They can train many different types of models, and are useful both for training and also for deployment. But if you design a chip for a specific type of model, or a specific type of deployment, you can make it perfectly optimized for that use case. So a lot of startups right now are looking at individual workloads, or individual deployment opportunities, and saying, “We’re gonna design a chip that’s perfectly tweaked for that use case.” And if so, it’ll run a lot faster, and run more efficiently than a sort of general purpose chip like an NVIDIA GPU will.
Now, this is startups tackling this industry, but it’s also big tech companies, Facebook, Microsoft, Google, they’re all designing their own in-house chips as well. Because they know the specific workloads that are inside their data centers, and they’ve realized, if they design chips specifically around those workloads, they can operate more efficiently in many cases than a general purpose AI chip like NVIDIA’s can do.
The power problem
On a silicon chip, the transistors flipping on and off are turning on and off electrical circuits. And so it’s electrons flowing through copper wires that are carved into your silicon chip that make all of the ones and zeros that chips rely on. And so electricity is at the center of how chips work. And one of the things that we’ve seen over the past several decades is that chips get much, much more efficient in terms of how much power they use, but they also get much, much more capable in terms of computing.
And one of the challenges that we face is that we’re getting better at producing more capable chips at a faster rate than we’re getting better at producing energy efficiency gains. Which means that we’re using more power, in aggregate, every single year. When you look at artificial intelligence, which involves some of the most power-hungry chips that exist, one of the limiting factors to building vast AI infrastructures is gonna be the availability of power.
Because for big data centers, they require a huge increase in electricity relative to smaller data centers that aren’t focusing on AI. And there are very smart people in Silicon Valley who think that the biggest limitation to AI might actually not be the quality of the chips, or the algorithms that are behind AI, it might be the ability to deliver power to data centers. Because in many cases, this requires bringing new power supplies online, building new power plants that are capable of delivering electricity to power the chips inside of these new data centers.
Well, when I look at the surge of investment in AI chips right now, I see no reason to doubt that Moore’s Law won’t continue for a very long time. That means more advanced chips, which means more computing power that we can apply to all sorts of uses, AI and all sorts of devices. And that means we’ll be using even more semiconductors, because the trend has been that, as chips get better, they get cheaper, and we put them in more and types of uses.
And so today, if your car has 1,000 chips, I wouldn’t be surprised if it has 10x that number in a decade. And that basic trend is true of everything we rely on. And that’s only made possible because chips get better, and they provide more computing for a lower price on an annual basis. The biggest geopolitical risk by far is that something goes wrong between China and Taiwan and the Taiwan Straits.
Because it’s not just Taiwan whose fate hangs in the balance today, it’s our entire economy. And if you think of the biggest companies in the United States, Apple, NVIDIA, Microsoft, Amazon, Google, Facebook, they all rely on chips that, today, are only made in Taiwan. So it’s not just a question of geopolitics in East Asia, it’s a question of our tech sector, and it’s a question of all the devices we rely on, because, today, for many of those devices, they rely on chips that, in some cases, can only be made by one company in a single factory in Taiwan. And so that illustrates the ways in which chips made in Taiwan are critical for the way we live our lives.
