The most important piece of technology in your lifetime is this tiny chip

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

And so 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 1, 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

are 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, on and off. And when they're on, they produce a one. When they're off, they

produce a zero, and 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

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 a 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 are used in semiconductors to convert these real world signals into strings and ones and zeros that can then be re-represented as pictures later on

For example, when you pull a photo op 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

And so 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 chipmaker has its own proprietary process

So we don't really know inside of a typical chip what materials are used

because chipmakers usually keep it pretty secretive. That's their special sauce that lets them manufacture chips with the right level of capability

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 chipmaking 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

And so inside of a chip-making 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

So 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

And 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

where 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 chip making facility costs $20 billion. They're 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 got to 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. And so TSMC is both the world's

largest chipmaker, 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. And so 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 chip 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. What is nanometer scale, and how does it relate to the innovation process of silicon chips

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

Because 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 were sort of light bulb-like devices that would turn on and off, on and off to produce the ones and zeros

And 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

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

And it's done so not just for a couple of years. It's done so now for over half a century

And that's why when you compare progress in the computing industry to progress anywhere else, there's really no comparison

Well, 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 transistor 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 capability 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

And so 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 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. And the

reason is that it's brutally expensive and it requires manufacturing processes that get better

and better and better every single year. And so 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. And so 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 of years ago, it became harder to shrink transistors in two-dimensional format

For a long time, chips were made. They were 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

So 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 and 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 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. And it used to be a larger number of companies that could

produce at the cutting edge, but it's shrunken to 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 around 90% of the most advanced chips

because they're cheaper and they're better than their competitors when it comes to manufacturing

Chapter two, 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 manufacture 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 Bratton 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 a thousand 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. 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. And so he hired a very talented

set of engineers in Silicon Valley. He moved to Palo Alto, California, where his mother lived

for the purpose. And although he hired lots of great people, they detested working for him

And so 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 to go

co-found Intel and many others, first started their career working at Fairchild. Intel was

founded in 1969 and 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

it 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

And Intel, even today, is the world's largest producer of chips that go inside of PCs

Gordon Moore was 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

And so 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 have required many different chips for each of those purposes

Whereas today thanks to the microprocessor we have programmable chips And 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

And so today the chip industry is split into two different parts. There's the chip designers, which today is essentially like a type of programming almost

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 of 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 ship industry, but also on copying whatever they could from the West

And so 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

And so they got very good at copying, but not so good at innovating, and that left them behind

And the second error they made was that they only focused on the military aspects. And 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

And so 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

So 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 chip making 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

So 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. And so 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

And so 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

They replicated the Japanese model. They became very good at manufacturing. They competed very effectively on cost

They also represented an alternative to Japanese production. Because 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 Philips, 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 Philips 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 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 on 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

So 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 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 an 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 want to 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 chip maker 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 is 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 is more reliant on the outside world to purchase

And China imports all of 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 into devices. And 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 want to 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 is 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 chips 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 has 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, or 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 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 US 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

the capabilities they need to produce the chips that they require on their own

What happened during the COVID-19 chip shortages? 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 face 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 chip maker 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. 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. 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 chip makers 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 chip making. 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 is 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

The problem is that even a small move, a small conflict would be disastrous for the chip industry because it not just about the security of the facilities themselves It 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. How would you describe 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 will have on average a thousand 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 an object in front of your vehicle

If you've got an 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 Wi-Fi and Bluetooth, more sensors, more AI capabilities installed in devices, we're going to 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 going to 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 going to 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

If you're not the cutting edge, you've got to 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

What is the CHIPS Act? And what did it do to boost manufacturing capabilities in the United States

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 four, the AI revolution. The biggest change in the past couple of years has been the explosion of investment in AI

I think 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 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 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 want to 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 going to be to drive down the cost of deploying AI systems

So we know how to train big systems right now. That's what OpenAI 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 chat GPT 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 going to 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. And so a lot of startups right now are looking at individual workloads or

individual deployment opportunities and saying, we're going to 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. 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 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 going to 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. 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 more types of uses. And so

today, if your car has a thousand 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. It's a question of

all the devices we rely on because today, for many of those devices, they rely on chips that

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