Jon Krohn: 00:02
This is episode number 882 on ASML.
00:19
Hello and welcome to another episode of the SuperDataScience Podcast. I’m your host, Jon Krohn. And today we’re diving into something absolutely critical to the future of artificial intelligence that you might never have thought of before. That’s the machines that make AI chips possible. When we talk about AI advancements, we often focus on the show on models, algorithms, and software breakthroughs. But there’s a fascinating hardware story unfolding that will determine the trajectory of AI for decades to come. At the center of this story is a Dutch company called ASML, headquartered just outside the quiet town of Eindhoven in the Netherlands. And in case you’re wonder what ASML stands for, today actually nothing. But when the firm was founded, it stood for Advanced Semiconductor Materials Lithography. So yeah, so there you go.
01:08
ASML, that’s all their name is today, makes lithography machines. And what that means is incredibly complex tools that print microscopic circuit patterns onto semiconductor wafers. ASML’s latest creation is mind-boggling. It’s a 150 ton colossus, roughly the size of two shipping containers, with a price tag of $350 million. And here’s the kicker. ASML is the only company in the world capable of making the most advanced versions of these machines that produce the cutting edge AI chips that power GPUs that Nvidia makes and so on. The technology behind these ASML machines is almost beyond comprehension. ASML’s extreme ultraviolet or EUV lithography machine fires 50,000 droplets of molten tin into a vacuum chamber. Each droplet gets hit twice by lasers, first to flatten the droplet into a tiny pancake and then to vaporize it completely. Why would you do that? Well, it sounds pretty complicated, right? And it has a crazy effect because that process creates a plasma that reaches temperatures of nearly 220,000 degrees Celsius.
02:25
Big number, right? What does that mean in context? That number, 220,000 degrees Celsius, is about 40 times hotter than the surface of the sun. So that’s really crazy. This process generates extreme ultraviolet light with incredibly short wavelengths. Which is then reflected by a series of mirrors so smooth that the imperfections are measured in trillionths of a meter. The light is focused onto a template containing the chip circuit blueprints and finally projected onto a silicon wafer imprinting the design. If you’d like to hear more about silicon wafers in particular, check episode number 875 of this podcast, which we had recently. Anyway, this technological marvel that ASML makes is what allows companies like TSMC, Samsung, and Intel to produce the cutting-edge processors that power everything from AI accelerators like GPUs, to smartphones. No other company today makes machines that can reliably print chips with the smallest features possible today. That is smaller than seven nanometers.
03:26
Even for more mature technologies, ASML’s tools actually dominate over 90% of the market. So ASML isn’t just about this super, super cutting-edge stuff, they’re dominating everywhere in terms of these semiconductor creation machines. To put more of this in perspective, in terms of what seven nanometer means and what these kinds of microchips are that ASML can create, a modern microchip is like an electronic lasagna. It has a base layer of transistors, topped with layers of copper wiring that shuttle data and power. A leading edge processor today can pack over 100 billion transistors containing more than 70 layers of that electronic lasagna. And this is the craziest thing to me. It has more than 100 kilometers of wiring. We’re talking here about a piece of silicon that’s about one and a half times the size of a standard US postage stamp. So basically something the size of a postage stamp with 100 kilometers of wiring inside of it. That’s completely insane to me.
04:31
And a single silicon wafer. So this big sheet, like a vinyl record, which we talked about more in 875 again. So that big silicon wafer processed by these ASML machines can contain hundreds of these individual chips, about stamp sized, with 100 kilometers of wiring in them each. Wild. Obviously it’s complex. The complexity of this technology has placed ASML at the center of a global technology battle. To prevent China from building advanced AI chips, the United States has barred ASML from selling its most advanced equipment to Chinese chip makers. In response, China is investing billions to develop homegrown alternatives. Meanwhile, Canon, a Japanese competitor that you might recognize from digital camera’s namesake, Canon is betting on a different, potentially cheaper technology called nanoimprint lithography to challenge ASML’s dominance.
05:30
But here’s the key insight. Unlike software where industry leadership can shift in a matter of months, success in lithography is measured in decades. ASML spent two decades perfecting its method of producing extreme ultraviolet light, EUV light. Replicating this achievement is not something that happens quickly regardless of how much money you throw at the problem. It’s like that old adage, “Nine women can’t make a baby in one month.” It’s that kind of thing here. And ASML isn’t standing still either. Their latest systems called High Numerical Aperture EUV, extreme ultraviolet, use mirrors with an aperture of 0.55, allowing them to print features as small as eight nanometers. To go even smaller, they’re working on what they call Hyper-Numerical Aperture, which could crank the aperture up to more than oh 0.75. This comes with significant engineering challenges. When ASML increased the numerical aperture from 0.33 to 0.55, the mirrors doubled in size and became 10 times heavier, now weighing several hundred kilograms. Increasing it again will only add more bulk and power consumption concerns.
06:42
Some researchers are already planning to go even beyond that, beyond extreme ultraviolet light, aiming for wavelengths of around six nanometers. This would require breakthroughs in light sources, optics, and the light sensitive coating on wafers. But many see this as a plan B, only if the Hyper-Numerical Aperture approach that I just described with the larger apertures fails to deliver. All right, now let’s talk about China again quickly. So China, cut off from the most advanced tools, is trying to extract more from the older ASML machines it can still import.
07:14
One approach is multi patterning, which breaks a pattern into multiple etching stages, allowing a machine to print details twice or four times as small. While this is effective, it adds complexity and slows down production. China is also trying to build its own lithography tools with a state-owned firm reportedly making progress on a machine capable of producing 28 nanometer chips, which that’s quite a few years behind where ASML is, but China is catching up quickly there. Developing an extreme ultraviolet system like ASML has today would be an entirely different challenge, requiring China to replicate ASML’s vast supply chain of more than 5,000 specialized suppliers.
07:56
And finally, back to Canon in Japan, Canon’s alternative approach, nanoimprint lithography, stamps circuit patterns directly onto wafers, much like a printing press. In theory, this could create features with nanometer accuracy at about 40% lower cost than ASML’s machines. However, Canon has faced significant challenges with defects, alignment, precision, and production speeds. So, so far Canon’s found more success outside semiconductor manufacturing, particularly in things like making smartphone displays and memory chips, where higher defect rates are more tolerable than in the semiconductor industry.
08:31
All right. So hopefully that was an interesting overview of ASML, their competitors, what they do, where they’re going, and how these lithography machines work. The outcome of this technological race will ultimately shape the future of AI. More advanced lithography tools enable the production of faster, more energy efficient chips capable of powering new generations of AI models. While ASML currently holds the crown for the world’s most important machine, the battle to control the technology that will shape computing’s future is far from over. If you’re interested in the nuts and bolts of computer hardware enabling AI advancements, this is definitely a space to watch. The innovations happening in this field are just as crucial to AI’s future as the software and algorithmic breakthroughs I more frequently discuss on this show.
09:16
All right. That’s it for today’s episode. If you enjoyed it or know someone who might, consider sharing this episode with them, leave a review of the show on your favorite podcasting platform, tag me in a LinkedIn or Twitter post with your thoughts, and if you aren’t already, be sure to subscribe to the show. Most importantly, however, we hope you’ll just keep on listening. Until next time, keep on rocking out there and I’m looking forward to enjoying another round of the Super Data Science Podcast with you very soon.
