Tool shortages cap leading-edge chip output near 2x

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 48:00

   So far, this has been about making better chips. The other half of the question is how many chips the industry can make if AI labs are willing to pay for far more of them. I'm getting a chance to talk to Pushkar Arande, who is the CTO of Intel. I'm very interested in understanding how the fact that the entire industry has to rely on the same suppliers, bottlenecks your ability to ramp up production.

2. 48:21

   So for this EUV tool, ASML produces less than 100 of them a year. And they don't plan to produce more than 100 a year, even by the end of the decade, or significantly more than 100 ER. And that is to be split between you, between TSMC, between all the memory makers who are ramping up production like Gutsky Hynex. How does that limit your ability to scale up to all this demand? It is a limiter. So we have to make the most of the capacity that we already have installed, and we'll try to increase the output from our existing fleet of tools.

3. 48:49

   And EUV or ASML is not the only bottleneck. It is definitely a bigger bottleneck than some of the other tools. But to a large extent, we're seeing all equipment seeing tremendous supply shortage. Even though there are multiple providers of other tools, once you lock into a process flow, let's say 18A, right? 18A is a mature process now, so we need a specific tool. We can't just go and get a different tool for the same.

4. 49:24

   So therefore, we're locked into that one tool, one supplier. and so we rely on that. What lessons does this give for 14A in terms of, by 2028, it's going to be such a crazy world. Yes. How do you structure things in such a way that you have flexibility in ramping? Actually, the way to do it, and we've been doing it and generally everybody does it, is you try to maintain as much fungibility as possible going from one node to the next node.

5. 49:48

   So let's say going from 18A to 14A, maybe you would say 80% of the tool set can be reused. And then, of course, 14A, for example, would require some new capabilities because it's a denser geometry, so it would require some unique tools. Do you have a sense of what is the ultimate bottleneck of how many wafers you guys could produce a month, even if you were to decide to invest infinity money into doing CapEx?

6. 50:14

   Given the existing constraints, let's say we had to maximize the output from a given footprint of tools, then I think it's incremental because the process today is already yielding pretty high. And to get, you know, if your yield is already pretty high, to get every 1% extra yield is extremely hard because it's already a finely tuned process. Are there enough tools in the world to say you could 10x the amount of wafers you're producing at the leading edge?

7. 50:42

   Not 10x, but probably like 2x, yes. That's quite interesting because the AI industry for a decade has been 3x in compute. Yes. Year over year? Yes. And you're saying that that just can't continue? Unless the entire supply chain, starting from the equipment suppliers, their suppliers, their sub-suppliers, unless everybody produces more, you can't increase the output collectively. Just to give the audience a sense of how big the AI demand is and how well it monetizes the products you guys are producing, you can crunch the numbers and the numbers seem to suggest that just a couple billion dollars of CapEx on Intel's account results in enough chips or the logic for enough chips to produce, say, $100 billion of revenue for the AI model companies.

8. 51:29

   And of course, there's so many other players within that stack. There's also memory and other things. But it's crazy that within a couple billion dollars of CapEx, which can be amortized over many different years, produces $100 billion of revenue every single year. Which seems to suggest that at some point that should percolate down and there should be some, you know, at some point the AI labs could just say, we'll just buy everything, produce as much as you can.

9. 51:54

   We'll just, you know, guarantee future income streams and stuff. There's early signs that that could actually be. happening already. The demand signals are just so high. But I think you were alluding to how the value is accumulating at the top of the technology stack, which is essentially what is happening is we move from a fully vertically integrated industry like 30, 40 years ago, maybe longer, to a very horizontal industry, right? Where you have foundries, you have equipment makers, You have, you know, their suppliers.

10. 52:30

    And today, you think about it, every hyperscaler is designing their own chips. And the scale of the hyperscalers is so large. And some of the, you know, the model companies, for example, and their demand is so high. Yeah, they could easily just, like, consume an entire fabs worth of silicon on their own or multiple fabs worth of silicon on their own. And they definitely have the capital to fund that.

11. 52:57

    So in some sense, we are moving from a sort of a horizontal world, again, to a pseudo vertical world where it's like the, you know, it's not monolithically vertically integrated, but it's kind of vertically integrated, virtually vertically integrated. Interesting. Right.