Andrew Homan & Chris Miller - Redefining Semiconductor Progress - [Invest Like the Best, EP.396]

22:44in a way that if you're in Arizona or if you're in Japan, you just don't have that efficiency. And so TSMC will say, I think they're right, that the bullet train that goes up and down Taiwan, bringing people back and forth in a single day between their fabs is one of the key sources of their comparative advantage. Why is the yield so low in these things? If you're producing cars in a Ford factory or something, there's very few lemons. Whereas you tell me what the numbers are, but I think for some chips, it's as low as like 70 % of the ones produced actually then go get used in production, which means you're just like literally throwing away a lot of the product.

23:17Why is that still the case despite all that sophistication? The manufacturing is the most complex that humans have ever done. So in comparison to a car, cars can have fault tolerances measured in millimeters for certain parts. In chips, you're talking about nanometers, so a thousand times more precise. And if you look at just the chip in your phone, for example, and pop it open, there are billions of tiny transistors, each one of which is the size of a coronavirus, and almost all of which have to work for your chip to function, to let you like things on Instagram or send a text message. And it changes every year.

23:49Every year, TSMC rolls out a new manufacturing process that is dramatically better than the old one, which means that the transistors are smaller or packed more densely together. And so the tolerances get even tighter year after year. And so the question of yield, how do you produce chips that work, means you've got to be yielding a new process on a regular basis. So you started out last year's process and you start all over again with the next process with even smaller tolerances for error. Andrew, I'm curious what you think like the five-ish most important companies are right now outside of NVIDIA and TSMC.

24:21I would put Broadcom on that list. I would put SK Hynix on that list on the memory front. I would put AMD on that list right now. I think when you look further down, you would put some of these other smaller component players that are in the AI infrastructure orbit as well. There's actually probably a longer list of those more than two or three. But you definitely have a whole group of companies that are benefiting from what I think is going to be one of the most significant infrastructure builds that we've seen. If you think about a company like ASML or something that seems pretty singular, which companies, if they just broke completely, would most mess us up?

24:59But I think ACML is definitely on that list. Maybe that's a time to chat about EUV and all these different acronyms that people throw around and what that means. I think it ties into the yield question and why you only get a 70 % yield or 80 % yield, or maybe even lower than that in some cases. But we were talking about at lunch, how incredibly complex the EUV process is and what exactly you're doing. And we're going to use this laser to heat this tin to a hundred times the temperature of the sun. And then we're going to bounce it off these mirrors that are the most technologically advanced and smooth mirrors in the entire world.

25:32And then we're going to essentially layer of complexity. I think the analogy is I'm going to hit a golf ball from earth and get a hole in one on the moon. That's what you're doing. And so when you're dealing with that scope, I think that kind of gives you a sense for why sometimes these chips don't come off the line and perfect. What do you think are the top concerns of the U.S. government? We can talk about Chips capital to finance companies or projects. Just by revealed preference, what does the U.S. government care the most about? And in your interactions, how on the ball are they? Like we're talking the day after Gavin Newsom vetoed this bill in California, which I think technology is very happy about.

26:13How well calibrated are our politicians around this stuff? Do you think they've been effective? What are they doing? I think there are three broad goals government has. One is to mitigate chip making concentration around Taiwan. Number two is to keep US firms out in front technologically in every segment that's possible. And then three is to prevent adversaries, China above all, from accessing cutting edge AI chips. And I think we've seen a lot of moves the last couple of years on each of these fronts. The Chips Act, which subsidizes domestic manufacturing controls on technology transfer to China.

26:45Government is relatively clued in. I think the people who are working these issues understand them well, but I think government works at government speed. The chip industry works at Moore's law speed. And so what really matters in the long run is actually that Silicon Valley, the US chip industry can keep that exponential growth going. If it does, then the political issues will sort themselves out. And if it doesn't, we have more problems than just political issues because our entire economy is levered to Moore's law. Why can't China catch up? If so much money, so many incredibly smart people, so much talent there.

27:18Obviously, the will seems like more and more of a centrally planned, more centrally focused effort. They can just say, we're going to devote X amount of effort. We don't direct the private sector the way they might. Help me understand why they can't get to parity. And earlier you said they might be on the downgrade list. No one can do it on their own right now. The US can't produce cutting-edge ships on its own. Japan can't. Taiwan certainly can't. They rely on imports of chemicals and software and technology. And so the fact that China's struggling to do it on its own is not a surprise. They're normal for struggling to do it on their own.

27:49In fact, they're trying something that's harder than anyone else has already tried, which is to actually be self-sufficient. The trend over the last 30 years has been to become less self-sufficient. We've collectively decided that we'd rather have specialization. So Taiwan specializes in manufacturing, Japan specializes in the chemicals, US specializes in design, because there's huge efficiencies that come from that. And did we accept a bit too much specialization in the case of Taiwan, one can argue that. But I think China's effort to do it all by themselves is much, much harder because they don't get the benefit of access to world markets and access to the whole world's expertise.

28:25Because this is such a burgeoning space, I'm curious, Andrew, where, if I got a room full of the semi-investors that you respect, whoever those people are, where you think your personal views would most diverge from that group? A couple fold. I think there's been a view, you know, maybe take the biggest of them all, right? NVIDIA, what is the view on that company and how has that view changed in the broader public markets over time? Because it's interesting, a lot of active managers that I've spoken with, actually, NVIDIA has not been a huge position for them, which is interesting because I think people always felt this is too expensive or this story has already been discovered.

29:03And so that's probably been one of the most, I don't know, puzzling or just interesting observations that I've had over time. is surprisingly few people actually own NVIDIA, despite it feeling like it's a very well-known story, right? And I think people talk about it all the time, right? It's in the newspaper all the time, et cetera. But I think people have this fear that, oh my gosh, the stock is too expensive or it's already up so much. But if you actually look at what's happened there, at least on a fundamental basis over the last two years since ChatGPT really was released, the fundamentals have tracked dead in line with the stock price, right?

29:34And so if anything, I think the earnings multiple is probably flat to slightly down versus where it was when ChatGPT was released. And so they've actually delivered on a fundamental basis over that time period. I think many smart semi-investors probably do own NVIDIA, so I don't want to say that's necessarily the case. But I think broader in terms of the broader market view of that company has always struck me as a little bit interesting given that dynamic. Can you talk about the changing cost structures and business models of the digital slash software world in this new era where it used to be very people engineering intensive.

30:09Now it's becoming much more compute intensive. I know we talked about we want that cost to come down, but just the game on the field right now, the difference in the business models that you're seeing. This like struck me probably like early 23. I was tagging along a meeting with the Maverick Ventures team, meeting with one of the Frontier model players. And this was early in their life cycle. And we were getting their financial model for what the business could look like over the next three years, five years, what the cost structure looked like. And this was one of these eye-opening moments where you looked at the cost base and literally 90 % of it was compute, right?

30:44So these are dollars that we're spending with Azure or AWS or GCP or Oracle Cloud and literally just for training these models. And that was another one of these aha moments. People don't appreciate the magnitude of spend that's going to be happening here over the next decade. The stats that people throw around, train a competitive model in 2022 was$10 million. In 2023, it's$100 million. In 2024, it's$1 billion. In 2025, it's$10 billion. And then I think the latest that Larry Ellison was highlighting was$100 billion in 2026, just like staggering amounts. What types of companies can actually keep up with that level of spend to be able to be on that frontier model edge than lead.

31:29That's one area. You're seeing just the cost of doing business in software in particular just drastically change where you had these old models that were very people-intensive and you had all kinds of salespeople running around selling the product, very R &D heavy and programmers, et cetera. And is that now changing where just the cost of business is being much more compute and chip-driven versus people-driven? I think you're seeing that shift in the hyperscalar capex numbers, et cetera. Can you outline what you view as the key sectors within semis, whether that's design, whether that's manufacturing, whether that's whatever?

32:03What do you think are the key three, four, five areas that matter most? So the design piece is critical, right? And that's where the companies like NVIDIA dominate, right? They're designing the best chips and then TSMC is making those chips. And then I think what is interesting is that you're seeing as Moore's Law slows, and this is something that people are well aware of. There's been press talking about this now for probably the last 10 years. Where are the opportunities to create value as it gets harder and harder to get those Moore's Law benefits on the front end? So the initial manufacturing of that chip itself.

32:36And that's why you're seeing so much interesting innovation on the backend side. So the advanced packaging side of the equation, for example. So, all right, we've made this chip now at TSMC. It's on three nanometer. how can we package that chip with other chips and memory, for example, and get that packaging to be as efficient as possible? Because historically, people just hadn't cared about it because you were getting these massive cost downs with Moore's Law and every two years doubling the number of transistors in that chip itself. And so you're finding these areas that historically have been ignored that are now being, in some cases, bottlenecks.

33:08Like COOS is probably a term that many people have heard thrown around that was actually limiting the number of NVIDIA GPUs were able to get manufactured. And so finding those areas that historically perhaps have been ignored are now actually some of the most interesting. If you think about the emerging players, everyone's heard some of these big names mentioned a lot, ASML, NVIDIA, Cadence, and so on. What are the most interesting emerging players in your mind that will matter a lot more? Like my rankings question, names that we'll hear a lot more in five years than we're hearing about today.

33:39I think the first thing you'd have to say is that you'd be surprised by how short the list is relative to any other sector of technology. Look at AI and list the five most important companies in AI. Half of them were founded in the last decade. Do the same as semiconductors, and it's a very different ratio. I think that speaks to the fact that there are some big incumbents who play a very big role, and it's led to less company formation than I think you might expect, given that the history of the industry is actually in startups emerging in Silicon Valley. And do you think about returns? I know you and I have talked about this in the past.

34:14It's really just, this is like a massive cycle that could be bigger than the ones that have come before it. And obviously technology investing is about riding those waves and identifying them. How do you think about what that means for prospective returns relative to everyone's opportunity costs, the S &P 500 or something like that? At the chip player. It's interesting when we look at opportunities on the private side, this scenario where at least to date, you've seen valuations actually be quite palatable, much different than what you see in software, particularly over the last few years. And so I think the opportunities for returns are actually going to be quite attractive.

34:49Interestingly, looking at this performance of the semiconductor index broadly, it's actually done quite well. I think something like 25 % CAGR over the last decade. And so I think when we think about the opportunity set in front of us right now, you look at the private world of semis, and then you look at the public world, in theory, that private world should outperform the public companies given that there should be an illiquidity premium, et cetera. And what we see in the market now is actually a pretty attractive set of companies that should be either large, independent players in this space looking out three to five years or will become important parts of many of the large existing incumbents, right?

35:30Because as you see it, very challenging for these public companies to merge with each other. They're going to have the need to do these tuck-in M &A strategies to really beef up their internal flagship efforts. Talk about antitrust. It seems like a really important feature of the system when it comes to returns. If NVIDIA wanted to buy all the companies that you backed and they're not able to because of antitrust, that's going to impact your returns maybe. What's the state of play with antitrust and what's going to be allowed? We've heard a lot about antitrust last week with discussion of a potential Intel Qualcomm deal and whether that would face antitrust regulatory issues.

36:05Hard for me to know. There's actually two types of antitrust that matter in the chip industry. One is real antitrust from Western regulators, and two is fake antitrust review from Chinese regulators. And a lot of the deals that we've seen be sunk in recent years were from the Chinese refusing to give approval, not because there was actually real concern, but this was a part of the political game that they're playing with the United States. And so So I think for every major transaction, and even some minor transactions in the chip industry, the question of Chinese approval hangs over. And it's something that companies themselves can't do much about.

36:37It depends on the state of U.S.-China relations and when's the next presidential summit. That's what matters more than the actual substance of the antitrust. Can you give an example of that? Just a case study of that playing out? The most recent, I think, was with Intel's effort to buy Tower Semiconductor. So Tower Semiconductor is a very small foundry company producing different types of chips than Intel produced. They're both in the foundry business, but Tower is a small company. And Western regulators all waved it through, and then China refused to review it. And why can't we just say, OK, why isn't there some way around that?

37:11I think this is a really interesting question. At some point, we're going to see a merger that's approved by everyone but China, and the company is just going to say, screw it. The problem is China's a pretty big economy, and everyone's got assets in China, and everyone needs the Chinese market. And so unless you're in a niche where you don't care about Chinese customers and you don't have any assets in China, you don't have no exposure to the Chinese market, you've got to listen when they say no. There was this meme going around earlier this week that in the late 90s, we really didn't have an internet bubble.

37:36We really just had a telecom bubble. Why might this not be of a similar character or nature to that? All right, I've got a lot of thoughts on this one. The CapEx debate rages on and I think that Gavin Baker did a nice job setting the state of play on this about a month ago. So let's go back to that bubble, right? We spent a lot of time thinking about it. I started at Maverick in 2004, right, as it was in the aftermath, right, of that explosion. And we pulled the data and looked at the biggest offenders and biggest spenders of CapEx during that time period. So the global crossings, the level threes, the quests, et cetera.

38:11And you look at the amount of capital that they were spending was just totally unsustainable versus where we are today. And I'll get into that. But the CapEx, so the dollars that they're spending, whether that be on fiber or Cisco routers or other kind of optical gear, was on average about 200 % of their operating cash flow. So for every dollar that the business generated on an operating basis,$2 was spent on CapEx. So they weren't self-funding. They had to borrow in the high-yield markets or issue equity or what have you, but it was not a self-funding sustainable situation. In some years, we pulled the data and it was even more odd popping, it would be 500 % of operating cash flow in a given year.

38:49And then you look at what was the utilization rate of that fiber in the ground. And I think as a view of like as late as 1999 and early 2000, only like 2 % of it was actually lit up and being used. So it was all on this build it and they will come mentality because the internet was in the early days back then. And so the thought was, this is all going to get consumed in very short order. And it just turned out that it wasn't. And I think it's very different from today where you look at the spending that is primarily done by the hyperscalers. So Meta, Alphabet, Amazon, and Microsoft, what are they spending relative to history on CapEx?

39:25And if you look at their operating cash flow in this case, so the cash the business is generating, right now their CapEx is only about 50 % of that, which is dead in line with where it's been over the last five years. So we are very much in a sustainable level where you could double CapEx and these businesses would still be self-funding and you wouldn't have to have run into an issue where they're having to borrow or issue equity or something like that to fund these builds. Furthermore, when you look at the utilization rates of these GPUs in their clouds, it is nearly 100%. There's nothing sitting around idle, underutilized.

40:01The dynamic, I think, is very different looking at that telecom period of time where you had this massive amount of infrastructure that was built. It wasn't really built in a sustainable manner from like a financing perspective. It wasn't even being utilized. Whereas today we can debate what ultimately will get generated by these large language models and the value that will get created. But I can tell you the GPUs are definitely being highly utilized right now. So it feels like a very different period of time. So if I were to take your analysis and apply it to today, the place that looks like Telco is the foundation model companies.

40:32They are spending 5x there or way more. They're operating cash flows. They have negative operating cash flows. That does exist. So does that mean they're all toast? If we get to$100 billion model, there's just not many places in the world you can get$100 billion. And the very few places you can are the companies that you've mentioned that have these amazing operating cash flows. So does that just mean that this technology is like an incumbent's dream and that these upstarts, even the opening eyes of the world, are in trouble? That's an interesting way of cutting it. And I think you look at the types of companies that could sustain that level of spend, that list is pretty short.

41:09And we talked about them just a few minutes ago. So that's a very interesting way of framing it. And I guess the implications in terms of who ultimately can afford these, the list is not very long. Well, it ties back into the Middle East, which we discussed before, because if you're looking for very large pools of capital, that's one of them. Will that be feasible? Will the U.S. – we have, in various cases, pretty close ties to the countries with the most money – talk about the range of feasibility. I think the U.S. is pretty comfortable with Middle Eastern governments investing in U.S.-based companies to build U.S.-based data centers.

41:40And we've seen, for example, Microsoft and Mubadala announce a joint investment vehicle. I think the U.S. is a lot more worried about investment in the Middle East because then the U.S. has less leverage and the Middle East has more. Certainly there will be data centers built all over the world, including the Middle East, but the U.S. government really doesn't want the most advanced frontier data centers being built in the Gulf rather than in the U.S. And so there's a lot of regulation coming down the pipe right now about that particular issue. What are you most worried about? I worry about the time horizon in which we see the return that Andrew's talked about.

42:13I think making sure that lines up is going to be critical to sustaining. if the scaling laws are true, the CapEx scales up alongside the size and we need real returns right away to fund that CapEx. I think the next couple of years, we have a runway in which the hyperscalers will spend regardless of return. And then at some point, we're going to need to see real business models emerging. And so the time horizon for that, I think really matters. And the other thing going back to the cost to compute is the more we can do to find ways to economize and compute, the more sustainable all this becomes.

42:45There's a huge incentive right now to economize on compute because NVIDIA has shown how large the market is to take a bite out of. And the best way to take a bite out of it is to produce something that is just as performant or even more performant, but at lower price. Andrew, how about from an investing perspective, what worries you the most? You're obviously going to lay out a lot of capital to support companies trying to solve all these problems. What keeps you up? It goes back to some of the points that Chris just made around what is the sustainability of all this? And is this a situation where is there a digestion period?

43:15I've been doing semis for long enough to know that this is still a cyclical business, despite what people will say. I think it's absolutely a growth cyclical business. And so I actually probably welcome any sort of down cycle because it's a great time to put capital to work. But I think just making sure that there will be a tier of new companies that are formed that are able to capture this broader paradigm shift that we're going through. And the challenge that the world I think faces today somewhat is you have one company, an incredible company, that's captured the lion's share of the economics to date.

43:48And when I think about NVIDIA and what they've done, this was a company that was initially a chip company, right, that then became chip and memory company that then expanded onto networking, and now they're selling this full system. And what happens if there's one company that's just capturing all the economic value of a transition like this? And you're going to want to have, I think a very vibrant startup community that's helping solve some of those problems, particularly like in and around the GPU. I think going directly after the GPU itself, we can talk about that more too, I think is a challenging task, but there's no shortage of need for innovation, everything around that GPU.

44:28And so are we going to be able to create an ecosystem here, opportunity that exists around all those things that we mentioned that are breaking earlier around power, around interconnect, around memory, et cetera. And I think when you look at the big customers that we just talked about, they're highly motivated to have a diverse and healthy Silicon supplier base. And we were chatting about, let's look at the last big paradigm shift and what happened with mobile. And you had a situation where when Apple announced the iPhone, AT &T is the launch partner. AT &T had a market cap of$250 billion. When the iPhone came out, Apple had a$70 billion market cap.

45:06And you fast forward 14 years and Apple's market cap now is$3.5 trillion and AT &T is$150 billion. Apple just extracted all the economics out of that transition, capturing obviously the hardware with the iPhone, but also the software with the App Store. And I think when you think about the biggest buyers of a lot of this infrastructure right now, they want to make sure that they don't become whatever you want to describe, a dump pipe, right? And they want to be able to capture value from this AI transition that we're going through right now and not let that all accrue to one of their suppliers.

45:40So I think it creates a tension in the ecosystem when you have a supplier that has a bigger market cap than you, that has more power than you, et cetera. I think there's a real incentive to have a healthy ecosystem. Generally speaking, what are the corporate strategy options available to those players that want to accomplish that? Just playing forward with the Apple AT &T thing, How do you avoid that happening to you this time? Well, they're trying to develop their own chips. And so that custom Acer work is probably very high on the list of what they're trying to do. And I think they're very forward-leaning.

46:09We were having lunch with one of the hyperscalers last week where they have a team. Their whole role of this team is just to be talking to startups in Silicon Valley, understanding what technologies are coming down the pike so that they can be put into their data center and to see if they can help solve some of those pain points that I illustrated. So I think they're trying to have a very wide aperture in terms of what they're looking at, in terms of what other opportunities are out there, even for the incumbents, right? There's, I think, a strong desire to see AMD succeed in this market as well.

46:38I think we will see more and more success come from them as they catch up and are releasing new chips that are higher performing. They figure out some of the software challenges that they've had historically. So I think that's another piece of the equation. So it's going to be a combination of custom chips that these hyperscalers are developing themselves. It'll be looking at other incumbents like the established semi-companies. And I think the third bucket is going to be the startup ecosystem providing value to help them diversify. I know you said maybe less interesting to go directly after the GPU and better to attack the area surrounding.

47:08But let's say the GPU is the Death Star at NVIDIA and there's that one little arrow for Luke Skywalker to shoot the laser beam through to destroy it. What's your best guess as to where that vulnerability might be for NVIDIA? I think the challenge will be that NVIDIA's chip is very flexible and nimble, and that's why people like it. If the models change, the GPU can still solve the models of tomorrow. If there is a scenario, this transformer technology, for example, ends up being the structure that everyone is going to be building models on going forward, that will potentially be that opportunity for companies, for startups that are able to just isolate that one very specific use case and do it much more cheaper.

47:47that will be an area I think that could end up proving to be a challenge for them. Like how does NVIDIA respond to that? They can obviously make custom chips that kind of go after these very specific markets too. To date, they've chosen not to do so. Okay. I want to talk about the ways to stay informed in this very fast changing world. And I'd love for each of you to call to mind three specific people. If you only got to ever talk to three people with the goal of always knowing what's going on, just imagine you could access wherever you want. What three people would you pick? I think it would definitely be someone at building out the infrastructure at one of the large hyperscalers.

48:23They're on the leading edge of all this, or you could say even one of the frontier model folks. I think that's definitely at the top of the list. I think it's going to be someone at TSMC that's on the leading edge of the manufacturing front. I think it's definitely someone at NVIDIA that's on the front. I mean, it'd be someone at NVIDIA, right? You can say who that would be. Those are obviously three good answers. I think the other aspect of this that I look at it from is understanding the business model shifts. And that, to me, is something that you understand not by talking at someone who's building the data center at the hyperscaler, but actually who's running one of the hyperscalers.

48:53Because they're looking at this saying, NVIDIA is now bigger than we are. What's our approach to the fact that our supplier is now beating us in scale? And what are the shifts we need to take to deal with that? I think that's one. I think the second is the capital allocation side of it. Where is money flowing from into? too. And I think you learn a lot talking to some of the smart investors in this space. And I think the third would be actually politics matters more here than it has in half a century. And so you really can't understand what's coming in terms of who has which access to which market, in terms of which technology can you sell abroad without considering the political side as well.

49:28What questions would you ask? Let's say we had those six people in this room with us. What would be the couple most pressing questions that you don't already know the answers to that you wish you could have an answer to. I think on hyperscaler build out, what are the key problems that they want to be solving next year, the year after that will provide you a roadmap into a, what are they gonna be buying, but also be how are they positioning themselves in the industry? And to me, that's a hugely important question. That's where all the money is allocated in each hyperscaler's decisions. That's half the market right there when you're talking about AI.

50:01Yeah, I think the government piece that Chris brought up is really important here too, right? And just understanding what is the focus, particularly the U.S. government, and where they are going to be putting potentially restrictions in place. Or probably more importantly, what are they trying to enable, right? Whether that's domestic manufacturing or getting the startup ecosystem in the U.S. operating at a much more higher level. I think that's another key question and topic to explore. What about beyond the hyperscalers? It's half the market. What about the other half? What's going on there?

50:27I think the other market that hasn't really taken off yet, but will, is on the edge of networks. We're going to see a whole lot of innovation coming as we deploy some models in the data centers, some on the edge, and we're not sure what ratio yet. I think we're in the very, very early innings of innovation in semis on the edge to be superpower efficient, to provide just the right amount of processing power for edge devices. That'll be different for cars, I think, than it will be for phones or for wearables or others. Unlike data center, where we're in inning three or four right now for data center, we're still in inning one on the edge.

50:59What does that mean? So does that just mean Tesla and Apple are going to develop better chips? Does it mean the end user devices are pretty concentrated and it's the biggest companies in the world? They already designed chips because it's just them doing a better job of what they're already doing? Or is it some new paradigm shift there too? So in certain cases like Apple, obviously they will most likely be making their own chips for their iPhones. I think when you look out a little bit more broadly, there's definitely going to be the opportunity for new companies to take advantage of this edge AI theme, I guess is how I describe it.

51:33The analogy, and this is actually interesting because it ties into NVIDIA as well, where NVIDIA has clearly shown that it dominates the data center. I think hands down, I think most people would not debate that. Whereas I think on the edge, the story is very much unwritten at this point. And I'm not sure if the game has really even begun. And if I look at NVIDIA and where their focus is, I think Jensen is pulling all or the vast majority of the resources to focus on data center piece of the business, because that's where all the value is getting created right now. Whereas I feel like they perhaps even decrease focus on some of their edge products.

52:06And you can see this even in their financial statements where their data center business has grown at a rate that I don't think I've ever seen any company grow at that scale over the last eight quarters. Whereas on their auto business, for example, that business has largely been stable over the past eight quarters, whereas you've seen this explosion in the data center. And part of that is it's not in their DNA as much to be offering low power chips, which is really critical for the edge when many of these things are going to be battery operated and performance for wise. The key metric, the joke in the industry is that Vidya makes a killer gaming laptop.

52:39But if I'm getting on my flight from JFK back to San Francisco, and I plug that laptop in the plane, the whole plane drops 200 feet because the power usage is so high. Is there an opportunity on the edge to create, I think, some transformative companies that can take advantage of, I think, what will be intelligence just moving from that data center into your phone, into your car, into your PC, into the broader industrial footprint that largely hasn't seen a lot of innovation in probably four decades. And so that's, I think, an area that's really exciting and worth exploring. I think the other point, just in terms of who's buying these things, is this whole rise of the startup GPU cloud, right?

53:20Companies like CoreWeave, for example, they came really out of nowhere to build these just dominant franchises right now. There's one in the AMD ecosystem called Tensorwave that's trying to do a similar strategy. And I think there's a real need for these startup clouds because they're just, they can move more quickly. And it's interesting that we view Amazon and Microsoft, these incredible businesses, which they are, but they're also at a scale that they just don't move that quickly. So there is the benefit of partnering with a core even NVIDIA did like an ingenious job, really bringing them up to scale where they can get chips out six months before.

53:56I think if you look at CoreWeave, they had their H100s out in March of 2023 and you couldn't spin up an instance of H100 in Azure or AWS until probably almost like six months later. And that's a lifetime, right? Given how quickly things are moving right now in the broader AI ecosystem. And so if you're able to be a nimble startup that can move quickly and align with a chip company, in this case, NVIDIA or TensorWave's case, AMD, there's an opportunity there to create a lot of value, both for the chip company and for that startup cloud itself, because you just get this product out into the market.

54:32And these GPU clusters are very finicky, right? And so if you just specialize in making those work, there's a big market. On the edge, one more point there is that I think since we're in the early stages, we underestimate the amount of change in products that will emerge. It's easy to assume it's going to be AirPods and iPhones that are defining the edge in 10 years. But if you looked in 2000, what would be the primary use of mobile computing? You might not have guessed the smartphone. And so I think we should be pretty open minded about where will glasses be or whatever else. It's interesting to watch Facebook.

55:03For two years ago, the metaverse seemed like an idea that wasn't going to materialize very soon. And now you won't call it the metaverse, but actually there's some interesting glasses applications coming out on the consumer side. And I think the other thing is the industrial side, which is less exciting because it's not something we're going to buy for our own use. But as Andrew said, there's been so much less innovation on the industrial side and there are so many potential use cases for AI on the industrial edge. We were talking over lunch about tractors having GPUs in them. I think that's probably just the first of many use cases for industry, which could be a very large market.

55:35Meaning a John Deere that has a couple of NVIDIA GPUs on it, anything that could benefit from the deployment of a cutting edge AI model will actually have these cutting edge chips, not cheap chips like are in most things on devices. And any sort of robotics in the future is going to need a whole lot of computing power. And maybe some of that will be calling back to the cloud. If latency matters, like in a self-driving car, but also in a drone, you probably don't want to call back to the cloud to ask it a question on a regular basis. You want enough compute on the device. What about power? Any commentary on power?

56:05There's all these crazy headlines about building more nukes and all the things that we're going to do to power the data centers and any layer deeper insights on what's going on in the world of power. So maybe this would be a little bit of a controversial view. My thought on that, so power is critical and there's probably not enough of it broadly, but I think there is a dynamic here where capitalism usually finds a way to work. And I remember if you go back to solar, for example, in the 2006, 2007 timeframe, there was a fear that we were going to run out of polysilicon to make these solar wafers.

56:34And sure enough, you know, capitalism finds a way, capacity comes online, and then there was actually oversupply in that case. And so with power in particular, when I talked to folks that I would view to be experts in this space, I wouldn't say I'm an expert in power by any means. But I think there is a dynamic when you see these forecasts for data centers that are getting built. Is there a dynamic where a data center says that it's going to need, pick a number, 100 megawatts, 50 megawatts? And will the real usage actually be a less than what they're saying kind of nameplate capacity will be just because there's almost like a double ordering dynamic?

57:06When they're telling the planner in that city or that state how much power they want, they're going to give the absolute kind of highest number that they can so that in the case that they might need that much, they can have access to that much electricity. I think the other dynamic, and this is an area where I'm talking about intelligence at the edge, the broader energy infrastructure in the US, I think people don't actually have like a crystal clear sense of how much capacity actually is out there and what the utilization rate actually is. And there's this concept of you're building to handle that peak load, but are there creative ways where in Atlanta, for example, in the heat of summer when everyone has their AC on in August, can you somehow incentivize folks to turn their air conditioning to a warmer temperature and bring that peak level down?

57:53And then all of a sudden, maybe there is actually more excess capacity than people. So a provocative statement, because I think the mindset broadly in the investment community is that power, and I think power is very critical, but I think there is a dynamic where maybe some of these kind of shortfalls find solutions. I think the other dynamic is that in data center chips, power has not really been a key focus the past decade. It's mattered, but it hasn't been the case that the primary driver has been bringing down power consumption. And as a result, we haven't brought down power consumption. Whereas in mobile, most people 20 years ago would be shocked by the compute per watt that is in your iPhone because Apple and others have fixated on bringing that down or bringing the compute per watt up because battery life is limited.

58:37And I think now NVIDIA is getting a lot of calls from its customers saying, hey, we'd like more performance, but also you got to take power really seriously. I'm curious how things get done in this world. This is like a side door into asking about the way that you're structuring Maverick Silicon specifically. the players you have around the table, the investments of your time and energy that you're making that will ultimately be called back to benefit the companies that you invest in. It strikes me as a world that you could count on two hands and pretty quickly get to the players that really have the power and whose influence and support you might need to be successful as a breakout company.

59:12Talk through that dynamic of how things are getting done, who matters, how you're cultivating relationships with them. It seems like a much more hands-on style of investing than maybe even Maverick has done in the past where it's like mostly a public markets investment firm. You buy some NVIDIA, you don't have to do anything. You can benefit from it going up. It seems like you're going the other direction with a really hands-on approach. So how and why are you doing it that way? Yeah. It's funny as we spent more time in this and pulled on this thread, I think we've gotten more and more excited about the opportunity here.

59:43And when you talk to many of the founders that we've worked with, there's three big pain points for a semiconductor startup. Pain point one is getting the design tools. So that would be from a synopsis or a cadence. Pain point two is getting the right IP building blocks, right? Because a lot of these chips, you don't need to reinvent the wheel and everything. There's off the shelf IP that you can buy for various pieces of that chip. And then the third challenging bucket is obviously the foundry piece and that initial tape out and then broader manufacturing. Is there a way to work with the key players in each of those buckets?

1:00:16So EDA, IP and Foundry to just ease the burden for these startups. And the concept that we use is that many of these startups are on the airplane, they're in the middle seat, they're in the last row of the plane. How can we get them upgraded to first class? All the large semi-players benefit when they're interacting with those foundry players, the IP players, the EDA players, et cetera. And so it's been exciting to have those conversations because many of those incumbents on those three buckets will benefit from having these startups in their ecosystem rather than one of their competitors' ecosystems.

1:00:50Not all these companies will be successful, but some of them will become big customers. And which company will be the next Annapurna or which company will be the next Astera Labs? There will be others like that in the future. And I think those different incumbents are very excited about working closely with them, but it's been fun. You've worked with Jim Keller, is a well-accepted genius of the field who's also entrepreneurial. Is that generally the description of the founders in this space versus the 22-year-old dropout YC types or the sort of classic Silicon Valley disruptor? Talk us through the nature of the people building these things.

1:01:26I would say the vast majority tend to be much more experienced. So these are individuals that have run divisions at the large public semi-companies, right? That have had the experience of building out chips at scale, which is, I think, much different than software where you have a much, I think, younger average age of your startup founder. It may be even 20 year difference or something along those lines. There's some exceptions to that. I know with Etch, with Gavin, does fascinating work there. And I remember laughing with him the first time I met. I was like, did they teach you any of this at Harvard?

1:01:55And he's like, no, not really. But it is, I think, for the most part, I think that's probably more of the exception than the rule. This is going to be a much more experience-based management team that you're going to be investing behind. Who do you compete with for deals? One of the things I've learned talking to you is the interesting distribution of where capital is available for investing in, especially in private companies. And obviously this can change really quickly and supply rises to meet demand and so on. But it does strike me that there aren't a lot of people doing in a dedicated way what you're trying to do in private markets for the semi's ecosystem right now.

1:02:29So who in a given deal that you're trying to invest in that you think is the best deal of the year, who are you up against most often? When I think about the lay of the land of the semiconductor, private semiconductor investing landscape, you have some very good early stage folks like Lipu at Walden, for example, Stefan at Sutter Hill. These are just experts in their craft, right at that early stage company formation period. And then I think when you look at the very latest stages and even the pre-IPO rounds, you have some, what I would deem to be traditional public market players. Fidelity has got a very strong team, Adam Benjamin leading that, that will come into those pre-IPO rounds.

1:03:07But in that middle section, let's call it series B and beyond, where the capital needs really start to pick up, I think there's a real dearth and shortage of capital in that market. And I think that's the opportunity that we're so excited about, because as these capital needs pick up for these companies, and that's right, is that tape-outs happening and the IP costs are starting to ramp because they're actually starting to manufacture chips. The EDA and emulation costs start to pick up because you're testing that chip to make sure that it's working. And that can total$50 million. And there's just not that many players that are willing to commit that level of capital to these companies.

1:03:42I think once you're able to satisfy that need, the reward can be enormous. We've seen that with some of these recent semi-IPOs. I think just comparing it to software, for example, where I think there's a very long list of capital providers that are going after that market. I think it's frankly just much shorter when it comes to semiconductors. If you could fly anywhere tomorrow and have a meeting of your choice based on what's going on right now, where would you go? I feel like the part of the industry that is harder to understand right now is in China, actually. Just went back earlier this year, first time since COVID.

1:04:16But because of the politics, because of the regulation, industries that used to be very closely knit are being split apart. And so I think understanding, for example, Huawei, which is the AI leader in China, producing China's leading GPUs at a moderate scale, that is going to be the company that defines where China is on the AI. What's the scale comparison to like NVIDIA? It's small right now relative to NVIDIA. And they're trying to ramp up and the US government trying to slow their ramp. And one of the key questions, I think, over the next couple of years is, will they succeed or will they face real supply constraints for the next couple of years?

1:04:49Can you tell the Huawei story, how it got to here and what's happened? It really is a fascinating company. And I think had it not been for the politics, we probably would see it like a Sony or a Samsung, a real electronics powerhouse. And in some ways, it still is. It started out in telecoms and networking equipment, founded in Shenzhen, right across the border from Hong Kong and grew by selling first to the Chinese market, but very early on pivoting to international sales. And so they were able to learn from their customers abroad, improve their technology, some IP theft along the way, but was it more or less than the average?

1:05:21Hard to say. And it was only really in the last 10 or 15 years that the relationship between Huawei and the Chinese state got closer. And now given the politics, Huawei's business model is to sell as a almost monopolistic producer into a Chinese market that is constrained both by the U.S. and the Chinese government. And so the company itself has had to shift a lot. And now it's the Chinese AI monopoly player. And maybe describe what the U.S. government did vis-a-vis Huawei, just to complete the story. So the U.S. government doesn't want China to produce cutting-edge chips. And so Huawei works with SMIC, the leading Chinese chipmaker, to actually manufacture its chips.

1:05:56SMIC is like the TSMC of China. But SMIC isn't allowed to buy the most advanced tools, including the newer lithography systems from ASML. And so right now, SMIC is trying to produce pretty close to cutting edge GPUs using second tier machinery. And it's learning just how hard it is to produce nanometer sized transistors using tools that weren't really designed for that purpose. And so I think they're a scrappy company. They are innovating on the fly, but they're also hitting real scale limitations, at least for now. When you think about the components of returns, You mentioned the entry prices can be reasonable sometimes in the space relative to some other stuff you've seen.

1:06:37What about just like the size they can get to, the capital intensity along the way that will dilute you as an investor if you're an early investor, and the paths to exit? Those seem like the remaining three components. I'd love you to just like pine on each of those three. I think maybe we'll start with the last one in terms of the path to exit. If there's 10 companies, my guess is one or two will end up going public. the traditional kind of IPO route, I think the majority will end up getting acquired by the large established semi-companies that will be using these startups to help basically bolt onto their flagship efforts where they can buy an engineering team or they can buy a product that can really solve a product gap that they have.

1:07:17And these are companies that are generating collectively something like$200 billion of free cash flow a year. So there's ample dry powder to pay for assets like this, even to the tune of$1 to$2 to$3 billion. And we've seen several examples of that happened over the recent term. And that is how I think about the exit path. And then a couple of them obviously won't work. In terms of the capital needs and the dilution that's required, I think it's interesting because there's this mindset with semis that they are very capital intensive, which I think is broadly true. I mean, each company is not making its own fab, right?

1:07:47They're making their chip at TSMC, but there are capital needs in terms of some of those startup costs that we talked about, having a deep engineering team, et cetera, that are not inexpensive. But I think comparing to software, yeah, software is not very capital intensive when you start. You can only have three or four people and you can do it all in the cloud and it doesn't cost that much to spin up the first product. But I think to scale, software is actually pretty darn capital intensive. It's just that capital intensity hits you later. In semis, it hits you early. But then I think actually the margin profile of a young semi-company can be actually be far more attractive than software.

1:08:20And so you can look at a semi-company that is doing a couple hundred million dollars of sales and is operating at 35 or 40 % operating margins relative to a software company that could be still burning significant cash, which may be the right decision for that software company if the LTV of these customers that they're winning will justify that level of spend. But I don't think that you should kid yourself that software is not capital intensive. I think it's just when in that life cycle of the company that it hits you. So maybe that's how I would frame that. What about the word bubble? When does the word bubble enter your minds, if at all?

1:08:53I think when people talk about bubble, it means you probably aren't in a bubble. There's usually one rule of thumb. It's usually only like afterwards. First rule of Fight Club. Yeah. So I think that's probably one just broad observation. Whenever people talk about a bubble, I think people were talking about this being a bubble like 12 months ago, right? And I think it's proven to not be the case to date. And so I think that's just one overarching view. As I mentioned earlier, I've been investing in semiconductors for long enough to know that this is a cyclical industry. And at some point, there will be a digestion period.

1:09:23But I will say that this is a growth cyclical. And this is actually a very attractive end market to be putting dollars into. And I think if you look at where the industry structure is today and where the operating margins are relative to some of these other sectors in tech, it's very attractive. And so if you have the stomach to deal with, if there is a bubble or there's a digestion period or what have you, I think there's actually can create opportunity because I think we know the endpoint is going to be up and to the right. Is that going to be a straight line up there? Probably not. But I think taking advantage of any down cycle, hopefully you can do that from a position of strength.

1:09:58Chris, if you had to study or encourage people to study any of the historical episodes in semis to better understand the future, what would you have them study? The PC revolution and Intel's role in it gives you an example of what it's like to be early in the stage of a growth cycle. The chip industry was always cyclical around DRAM, the memory chips that were in all sorts of products, computers, consumer devices. But Intel was early to the PC revolution and was able to ride that wave two and a half decades, three decades, of which there were cycles in the midst of it. But because more people were buying PCs, you didn't really notice those cycles anywhere near the way you noticed the DRAM cycle because they were just less protected.

1:10:37And so I think that's the optimistic view of where we are right now is that it's a cycle, as Andrew said, heading up to the right. You can suffer some ups and downs. And I think that's probably the right analogy because we're seeing an entirely new type of or new category of chips emerge to prominence that we hadn't used before. And that's what happened in the 80s with microprocessors that were used for the first PCs. It was really a niche market before then, and PCs made them a mass market. How do we get to this state of the world where so much of the manufacturing is done overseas? I think there were two drivers of the shift overseas.

1:11:11I think one was that U.S. companies naturally, in some cases, rightly focused on what they were good at, which was design. And two is that manufacturing was cheaper overseas. Today, it's cheaper in Taiwan, not primarily because of labor costs. There's actually very few people that work in a fab, highly automated. It's cheaper because of the ecosystem dynamics. And those are very hard to reverse. And I think for that reason is also why companies are less excited about investing a dollar in manufacturing versus design. Because if you're going to invest a dollar in manufacturing, you've got higher costs and less developed ecosystem.

1:11:45You'd probably rather develop it, put it in design. Government's trying to change that with the CHIPS Act, putting$40 billion at work in the US. And that's a lot of money. I think it's also important to keep that amount of money in context. TSMC spent almost that much in CapEx last year. And so even really substantial government money is enough to move the needle, but it moves the needle on the margin. And it's going to take, I think, a long time to really shift where manufacturing happens. What could most disrupt the trajectory of this whole story? What could be an example like a new architecture, not a transformer, but something different that re-kicks off a different kind of rate of improvement?

1:12:21Or you already talked about maybe the scaling laws level out and that could change things. What other things could happen that would drastically change the trajectory of the semis industry? Memory. One of the key limiting factors in performance improvements is the need to move data back and forth from processor to memory. And so there's a variety of new memory architectures that are being experimented with. I'd emphasize experimented rather than prototyped, but a lot of researchers refer to this as the memory wall. The key pain point is that your memory is too far from your processor and this slows everything down.

1:12:52And so I'm not going to bet on it next year or the year after, but down the road, we might need new memory architectures. Maybe just explain in a little bit more detail what is literally going on there. What is happening? And then if it were to get revolutionized, what it would unlock? You literally have a memory chip and a processor chip. So in the case of an AI accelerator, you have your GPU and your high bandwidth memory, and you need to move data between them, which means move electrons between them. and the distance coupled with the speed at which electrons move, which is slower than the speed of light, for example, you could move it photonically and increasingly do, creates friction in your training.

1:13:28And so if you were to design chips differently to have processor memory more intertwined or closer together, or if you switch to optical interconnects, those are all ways you can increase the speed at which that happens. And the knock-on effect of that would be just a more efficient system. More efficient system, but also potentially changing... Lower cost of compute. Lower cost of compute, yeah. Yeah, and potentially changing who's good at producing them. I think that's fair. You have this dynamic in the industry where the GPU performance has been increasing at a much faster rate than the networking and memory performance.

1:13:58And so you're not able to get as much utilization out of that GPU as you would like because of some of these other bottlenecks. What happens if the networking piece and that memory piece can't keep up? Does that end up just slowing down just the level of innovation that we're seeing in the market and the ability to train a bigger and bigger model? I think my expectation would be there's a lot of interesting activity happening at that networking and memory level to try to solve some of those pain points and catch up with the performance improvement that you're seeing with the GPU. But to me, I think that's a key issue to understand because if you're in a situation where you've got this incredibly powerful processor, but you can't get data in and out of it quickly enough, or you can't get enough data in and out of it, does that end up being a bottleneck that slows down innovation?

1:14:45Just imagine that your whole portfolio is already built, the general types of companies that you're going to invest in. On average, where do you think the source of sustainable power and differentiation will come from, business power, not literal power, will come from for those companies? Is it mostly scale? Is it intellectual property? Is it cornering the best researchers as you think about not just who's going to grow, but who's going to grow in a defensible way. Where do you suspect most of that defensibility will come from? I think it's got to come from the intellectual property piece, right?

1:15:16And the value that these companies are bringing to the table and the problems that they're solving, right? Because the scale piece comes from the foundry players. These startups are designing the chips for the most part, and then they're going to outsource that piece. So the scale gets solved by that third-party foundry. Whereas I think the value really is going to be created from the pain point that company is solving? And are they able to do it in a way that no one else can? Is that world like AI model research where frustrating how few people seem to really matter? And it's like dozens of people that seem to have any real impact on frontier models?

1:15:47I think it's broader than that, to be totally candid. I think you've got, in Silicon Valley in particular, right, you've got thousands of engineers, tens of thousands, probably frankly, even hundreds of thousands, right, that are very technical. Are they all going to be startup founders? Definitely not. I think it is actually probably a wider talent pool than maybe what you're seeing with some of these AI kind of frontier model places where it seems like there's these 100X engineers, right? If you're able to have one of them, that solves all your problems. I think there are folks like that in the STEM industry, for sure.

1:16:14You highlight Jim Keller, his reputation, I think clearly precedes him and there's others. But I think broadly speaking, I don't think you have quite that same pain point. What do you two most commonly debate or disagree on? I don't know if we disagree. I mean, we talk a lot about government stuff, right? In terms of when headlines come out and there's a lot of news flow coming out of DC and just trying to understand what it means and what the intentions are of the various restrictions that are coming out or whether it's CHIPs Act related. What are the end goals that they're trying to achieve with both the fab side and the R &D side?

1:16:43Chris has got incredibly tight relationships there. I remember I told you I was in DC last minute and then you had me meeting with Biden's CHIP liaison. I was like in the West Wing of the White House like four hours later. So you definitely have those people really trust and respect what you have to say. But I think it's more of a collaboration just trying to like, what does this really mean? Because I think you are probably more effective than I am reading the tea leaves a lot of this. Yeah. The other facet, I think this is a fair statement. There are more different ecosystems that need to be brought together to understand the full picture.

1:17:13You need to understand the manufacturing, the IP, the end users in the data center. The supply chain is longer than a typical software company, for example. You've got to understand where all the players are to see where technology is going. That's a very interesting point, right? Because I think you look at software that tends to be much more siloed. And in the semiconductor ecosystems, when we touched on these different players earlier in the conversation, where like so many different folks just interlap and it's very interwoven, where everything from semi-cap that's making the tools to the foundry player, to the design folks.

1:17:47And even with design, there's these different buckets like mobile and compute, and there's analog. And then you have the EDA folks that are selling the tools that are designing the chips. And then you have the IP players like ARM, etc. But like everyone needs to work together to push the industry forward. And so being able to see that bigger picture and have the connectivity with those different players, I think is a really critical piece of successfully pursuing this market. And I just think it's different than what you see in software, for example. I was struck when I first started learning about the semiconductor industry.

1:18:20I figured there'd be someone I could call to get a view of the whole thing. And I quickly realized that there are brilliant people who know their slice and know a bit about the slice below and above, but there are so many steps in the supply chain that actually it's really hard, almost impossible to have a view of the whole picture. What are the most sensitive parts of the supply chain? The manufacturing step is sensitive, but so too are the tools that make manufacturing possible, the ASML level, if you will. But then you can't do the manufacturing off the chemicals. And the chemicals are made in many cases by a couple of Japanese firms, which have the unique knowledge to produce chemical X with 99.99999 % precision.

1:18:59And that's only the manufacturing side. Then you look at design where the IP and the EDA tools are. It's hard to say one of them is more critical than the other because you need all of them. It starts to feel like Arrakis or something in Dune. It's this precious compute resource that just fuels everything else. And there's a revelation going on in it that kind of we've never seen before. How big do you think this gets? How big is this industry in five, 10 years? And how big is it today? Today, the semiconductor industry is probably$700 billion, give or take. Software is probably a little bit higher than that, like$800 billion.

1:19:35When I think about where we go, maybe this is a bold statement. I think the semiconductor market will exceed the software market by the end of the decade, which just given this flow of shift into compute from people into compute as that being the primary resource that's going to drive AI. I see the other thing that makes me optimistic about the future rate of progress is the application of compute to solving chip design and chip manufacturing problems. There's this sort of flywheel of we make better chips, we produce more compute, and we use it first and foremost to make better chips and produce more compute.

1:20:07So whether it's at the chip design, where the leading chip design companies have essentially been doing AI for chip design for decades now. You can't lay out a chip with 10 billion transistors that a whole lot of computing to do it for you. Or whether it's the lithography process, how do you know what shape to print? There's now extraordinary amounts of computation that go into the actual figuring out how to get the shape you want on your transistor or the shape of the transistors and your piece of silicon. There's already a huge use of computing in the design and production process. And I think there's immense excitement about ways to find even more applications for AI to make the chip design and production process more efficient.

1:20:45Anything we've missed that you think is critical to what's going on in this world that you spend time on that we haven't talked about? The thing that stands out to me is that one might think the more advanced chips we need, the fewer less advanced chips we need, but it's actually the exact opposite. The more advanced chips we need, the more less advanced chips we need to be in the systems around them. So take a new car, for example, you've got a couple of pretty high-end processors for the self-driving. But if you need self-driving, you need a ton of sensors around that. You need more chips managing the data transfer between different sensors.

1:21:16And so a new car will have more lower tech chips than an old car will, in addition to having a couple of higher end chips. I think that's an interesting dynamic for the entire industry, because it means even if you're not NVIDIA, if you're an analog devices, which produces a lot of the sensors, for example, AI is a really interesting transformation for you too, because the sensors that you produce are going to be converting the data that will be necessary for AI training or inference. And you see that in basically every corner of the industry. Is that an investment opportunity? That strikes me as something that is a far less sexy story and therefore perhaps more interesting price, but nonetheless similar long-term prospect in terms of market size.

1:21:54Yeah, absolutely. I think that kind of ties into that broader edge AI bucket. And we talk to a lot of these companies, they're more analog based, right? And so not the leading edge digital chips where you try to make it very clear with them, what just happened in the data center, that tsunami is coming for you next. And if you don't embrace change here and widen your aperture to be able to put intelligence into your historically kind of dumb chips, you're going to be on the wrong side of change and someone's going to come disrupt you, just like you saw NVIDIA disrupt the incumbent in the data center market.

1:22:26And so I think anyone who's on the edge should realize that that wave is coming for them next. If I were to force you both to leapfrog one or two degrees away from just core Semi's focus, what is going on in the world right now that most interests you? The other place I'm spending a lot of time is in biotech genetics space, which I think not this decade, but next decade, there'll be a very interesting intersection of improved semi-technology and biotech. And I think if you spend time at places like leading universities and ask, what are the PhD researchers working on? There's a whole lot of interesting work being done there, which I suspect will lead to company formation and new technology down the road.

1:23:06So I've been living and breathing semis here, in particular over the last nine months. So this is, it's a refreshing question. I think just trying to zoom out, and this ties into the semi piece of the equation, but like, how do you help create a more vibrant, healthy startup ecosystem for this set of companies and for this industry? And how do you collaborate with folks in DC, which I think to their credit, the Chips office is doing a great job being proactive, talking to investors, talking to companies, not trying to be in that DC echo chamber. What can be done to de-bottleneck all these pain points that makes it so challenging for a chip company to start up?

1:23:44How do you motivate that really smart engineer who's at NVIDIA right now or AMD or Broadcom to say, hey, I'm going to start this new company because I think the rewards of that are going to be both financially and personally massive. And so creating that culture is something that I try to think about because I think it's really important for the U.S. broadly to being competitive on the design side where it dominates today. But the fear is that, does that slip away because you don't have a very active startup pipeline that's pushing the incumbents to innovate and keep moving this ball down the playing field?

1:24:18And so that's something that I think about a lot and try to figure out how can you collaborate with the different players in this ecosystem, whether it be the incumbents, whether it be the US government or other governments, to create a really vibrant, healthy ecosystem. Having read the book and talked to you a lot about what you're building at Maverick Silicon, And I'm really excited to see the companies that start to come through here. Like you guys have put so much time and thought and attention into not just who to back, but how to help back them. So I'm sure the signal coming off of what you invest in is going to be a fascinating way.

1:24:49You'll be my answer to my earlier question about who to call to figure out what's going on. My traditional closing question for everyone, what is the kindest thing that anyone's ever done for each of you? The caveat here will be this is excluding family. But yeah, so this ties back to when we had lunch this summer and I was leaving. for that trip, my first trip to Taiwan. And so if I go back to high school and college, the mentorship that I got from my teachers and my coaches over that period of time, it's such a huge impact on who I am today. That probably is the kindest thing that anyone's ever done for me.

1:25:23And the reason why I bring up that Taiwan trip, so that ended up turning into two Taiwan trips over the course of eight days. And I was at an airport hotel working out at the gym, trying to maintain some semblance of fitness and got an email from my rowing coach from high school that probably hasn't coached me on the water for over 20 years. Just, hey, Andrew, checking in. How are you doing? How's your family doing? And it just totally brightened my day. And just individual still cares about me. Long after I left his program, I left that university, I left that high school, just like really brought a smile to my face.

1:25:56And I think just trying to do that at Maverick, where can we mentor that next generation of leaders at the firm and spend time with them and invest in them? I try to do that like people did with me. I don't think necessarily do the best job, but I think that's just like a really valuable lesson. I just encourage everyone take the time to do that because I think it's important. I'd mentioned a mentor as well, my advisor when I was doing my PhD in history, John Gattis, who often when you have a PhD advisor, your advisor wants you to study what they study. That's the standard trend. And John said, study whatever you want to study and gave me sort of an intellectual blank check and trust that I could find something interesting and accurate to say in whatever field I wanted to.

1:26:34And at the time, that was a niche area of Russian history when I was studying them. But it, I think, helped me realize that if you have the right set of tools, you could have confidence to go into a new area, understand what's happening there, make sense of it, and produce something of value at the end of it. And that initial willingness to take a bet and write that blank intellectual check is something that I value today and hopefully I've produced value from. The world's infrastructure is changing. Thank you for teaching us about what's going on. Thanks for your time. Thank you. Thanks. If you enjoyed this episode, check out joincolossus.com.

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1:27:36Outro Music