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

Summary

Summary of "Andrew Homan & Chris Miller - Redefining Semiconductor Progress - [Invest Like the Best, EP.395]"

Host: Patrick O'Shaughnessy
Guests: Andrew Homan and Chris Miller
Release Date: November 5, 2024

In episode 395 of "Invest Like the Best with Patrick O'Shaughnessy," Patrick engages in a profound discussion with industry veterans Andrew Homan and Chris Miller. The conversation centers on the dynamic semiconductor ecosystem, emphasizing its foundational role in the digital age, the impact of artificial intelligence (AI) on chip demand, geopolitical tensions surrounding chip manufacturing, and the future of innovation, particularly at Nvidia.

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1. Introduction to the Semiconductor Landscape

Patrick sets the stage by introducing the guests and outlining the episode's focus on the semiconductor industry's evolution in the context of AI and global geopolitics.

Patrick O'Shaughnessy:
“We explore their ideas, methods, and stories to help you better invest your time and money.” ([03:58])

Key Points:

• Industry Significance: Semiconductors are the backbone of modern technology, powering everything from PCs to AI-driven applications.
• Guest Expertise: Andrew Homan, with two decades at Maverick Capital and now a Managing Partner at Maverick Silicon, leads technology investments. Chris Miller, a Tufts professor and bestselling author of Chip War, provides a geopolitical perspective on the semiconductor battle.

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2. Intel’s Struggles and the Innovator’s Dilemma

The conversation begins with an analysis of Intel—a once-dominant player now grappling with paradigm shifts.

Andrew Homan:
“Their problems… are actually a function of their success. They were too successful… and by the time you realize it's no longer profitable, it's often too late.” ([06:08])

Key Points:

• Over-Reliance on Legacy Markets: Intel's dominance in PC and data center chips led to complacency, hindering adaptation to emerging trends like mobile and AI.
• Innovator’s Dilemma: The challenge of abandoning profitable existing products to invest in innovative, risky ventures can stifle growth.

Jim Keller:
“I would describe it as a Hong Kong action film… a lot of moving pieces.” ([05:14])

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3. The AI Paradigm Shift

Jim Keller outlines AI as the most significant architectural change in technology, surpassing previous shifts like mainframes to PCs and PCs to mobile.

Jim Keller:
“This next paradigm shift… would be AI. And the implications… are probably broader perhaps, than any of those other paradigm shifts.” ([08:04])

Key Points:

• Three-Layer AI Ecosystem:
  1. Chips and Cloud (Infrastructure Layer): Nvidia, AMD, TSMC.
  2. Foundational Models (Middle Layer): OpenAI, Anthropic, Gemini.
  3. Applications (Top Layer): ChatGPT, Tesla's Full Self-Driving, Office Copilot.
• Economic Rent: The infrastructure layer is poised to capture substantial economic value due to its foundational role in AI development.

Andrew Homan:
“The more advanced chips we need, the more less advanced chips we need to be in the systems around them.” ([82:19])

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4. Venture Capital and Investment Dynamics

Andrew Homan and Jim Keller delve into the complexities of investing in the semiconductor space, highlighting its capital-intensive nature and competitive landscape.

Jim Keller:
“Semiconductors are challenging, they're technically complex. Compared to software, looking prospectively over the next 10 years, we're going to see more capital flow into this hardware layer.” ([15:49])

Key Points:

• Capital Intensity: High upfront investments are required for chip design, IP acquisition, and manufacturing partnerships.
• Investment Opportunities: Despite fewer dedicated semiconductor funds, there are attractive returns due to the industry's growth potential.
• Exit Strategies: Acquisitions by large semi companies and IPOs are primary exit paths for startups.

Jim Keller:
“The semiconductor market will exceed the software market by the end of the decade.” ([80:27])

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5. Geopolitical Tensions and Supply Chain Concentration

The episode addresses the strategic importance of semiconductor manufacturing hubs and the geopolitical tensions that influence them.

Andrew Homan:
“There's a whole lot of concentration in Taiwan… a few other countries, but it's not going to be every country producing its own chips.” ([19:15])

Key Points:

• TSMC's Dominance: TSMC's maniacal focus on the foundry model and its advanced manufacturing capabilities position it as the leader.
• ASML's Critical Role: ASML's Extreme Ultraviolet (EUV) lithography machines are indispensable for cutting-edge chip production.
• US-China Relations: Efforts like the CHIPS Act aim to reduce reliance on Taiwan by boosting domestic manufacturing, but the ecosystem's complexity makes widespread replication challenging.

Jim Keller:
“ASML is definitely on that list. Maybe that's a time to chat about EUV… it's incredibly complex.” ([25:36])

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6. Technological Innovations and Challenges

Andrew and Jim explore the technological hurdles and innovations necessary to sustain semiconductor growth, especially in AI.

Andrew Homan:
“The need to move data back and forth from processor to memory.” ([73:35])

Key Points:

• Memory Wall: The latency and power consumption associated with data movement between processors and memory are critical bottlenecks.
• Advanced Packaging: Innovations in chip packaging can enhance performance and efficiency.
• Power Efficiency: As AI models become more compute-intensive, reducing power consumption per operation is essential.

Jim Keller:
“If you look at the types of companies that could sustain that level of spend… the list is not very long.” ([41:55])

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7. Future Outlook and Emerging Players

The discussion shifts to the future landscape of the semiconductor industry, emphasizing the role of startups and emerging technologies.

Jim Keller:
“There’s no shortage of need for innovation. Everything around that GPU.” ([46:28])

Key Points:

• Edge AI Opportunities: The integration of AI into edge devices like cars, phones, and industrial machinery presents new investment avenues.
• Startup Ecosystem: Building a vibrant startup community is crucial for continual innovation and preventing monopolistic concentration of economic value.
• Biotech Intersection: Future intersections between advanced semiconductors and biotech could drive significant advancements.

Andrew Homan:
“Since we're in the early stages, we underestimate the amount of change in products that will emerge.” ([55:16])

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8. Political Considerations and Government Policies

Andrew Homan highlights the crucial role of government policies in shaping the semiconductor industry's future.

Andrew Homan:
“Government has three broad goals: mitigate chip concentration in Taiwan, keep US firms technologically ahead, and prevent adversaries like China from accessing cutting-edge AI chips.” ([19:15])

Key Points:

• CHIPS Act: Aims to subsidize domestic manufacturing and control technology transfers to China.
• Regulatory Hurdles: Deals can be stalled by geopolitical considerations, as seen with Intel's attempt to acquire Tower Semiconductor.
• Global Collaboration: Success in semiconductor advancements relies on international cooperation and access to global expertise.

Andrew Homan:
“You need to understand the manufacturing, the IP, the end users in the data center… to see where technology is going.” ([78:03])

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9. Navigating the Investment Landscape

Jim Keller and Andrew Homan discuss strategies for investors looking to capitalize on semiconductor innovations.

Jim Keller:
“The opportunity for returns is actually going to be quite attractive.” ([35:07])

Key Points:

• Valuation Opportunities: Private semiconductor companies often have more reasonable valuations compared to public counterparts.
• Strategic Partnerships: Collaborations with EDA, IP, and foundry players can mitigate the high barriers to entry.
• Sustainable Growth: Ensuring that semiconductor companies can scale efficiently while maintaining innovation is key to long-term success.

Jim Keller:
“If you have the stomach to deal with a down cycle, I think this can create opportunity.” ([69:25])

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10. Concluding Insights and Future Directions

Patrick wraps up the episode by highlighting the critical lessons and future directions for investors and industry participants.

Jim Keller:
“Semiconductors are cyclical but very much a growth cyclical.” ([69:25])

Key Points:

• Cyclical Nature: Understanding the cyclical patterns in semiconductor demand and capital expenditure is essential for investment timing.
• Holistic Understanding: Investors must cultivate a broad understanding of the entire semiconductor ecosystem, from design to manufacturing to application.
• Continuous Innovation: The relentless pace of technological advancement in AI will continue to drive semiconductor innovation and investment opportunities.

Andrew Homan:
“Memories of mentors… helped me realize that with the right tools, you can find something of value.” ([85:35])

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Notable Quotes

• Jim Keller:
  “Intel's manufacturing is the most complex that humans have ever done… almost like hitting a golf ball from Earth and getting a hole in one on the moon.” ([23:55])

• Andrew Homan:
  “The ecosystem in Taiwan is just extraordinarily well developed… bullet train brings people quickly between their fabs, which is a key comparative advantage.” ([22:51])

• Jim Keller:
  “The semiconductor market will exceed the software market by the end of the decade.” ([80:27])

• Andrew Homan:
  “Any robotics in the future is going to need a whole lot of computing power… intelligence is just moving from the data center into your phone, into your car.” ([56:39])

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Conclusion

Episode 395 offers an in-depth exploration of the semiconductor industry's current state and future trajectory, emphasizing the critical interplay between technology, investment, and geopolitics. Andrew Homan and Chris Miller provide invaluable insights into navigating the complexities of chip design, manufacturing, and market dynamics, making this episode a must-listen for investors, industry leaders, and technology enthusiasts eager to understand the forces shaping our digital future.

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Resources:

• Podcast Series: Explore all episodes and resources at Join Colossus
• Book Mentioned: Chip War by Chris Miller

Transcript

[Patrick O'Shaughnessy]

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[Chris Miller]

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[Patrick O'Shaughnessy]

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[Chris Miller]

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[Chris Miller]

Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest like the Best.

[Patrick O'Shaughnessy]

This show is an open ended exploration.

[Chris Miller]

Of markets, ideas, stories and strategies that will help you better invest both your.

[Patrick O'Shaughnessy]

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[Chris Miller]

Can access all our podcasts including edited transcripts, show notes and other resources to.

[Andrew Homan]

Keep [e-mail] Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit PSum VC.

[Chris Miller]

My.

[Patrick O'Shaughnessy]

Guests today are Andrew Homan and Chris Miller. Andrew has spent two decades at Maverick Capital and is a Managing Partner at Maverick Silicon, where he leads the firm's technology investments. Chris is a professor at Tufts and the author of the New York Times bestselling book Chip War, which details the geopolitical battle to control the semiconductor industry. Today, we get into a comprehensive discussion on the semiconductor ecosystem and the silicon backbone of our digital age. Andrew and Chris share insights on how venture capital is navigating this complex industry and what it means for the future of computing. We discussed the AI driven revolution in chip demand, the geopolitics of semi manufacturing, and the next wave of innovation behind Nvidia. Please enjoy my conversation with Andrew Homan and Chris Miller.

[Chris Miller]

So guys, I thought a fun place to begin would be to talk about one specific thing in this ecosystem just as a jump off point. And intel seems like an interesting business to do that with because Intel's been around for a long time. There's been periods when intel was an unbelievably dominant and pioneering business and we're in the midst of a paradigm shift. So maybe you can describe why intel the business is an interesting one to study to learn about what's happening in the field of semiconductors today.

[Jim Keller]

So I guess maybe to kick it off, I was at an event last week with the Global Semiconductor alliance and this topic came up and someone asked, what film genre would you describe in terms of what is happening at intel right now? Is it a horror show? Will it end as a romantic comedy? And I'm not exactly sure what term I would use to describe that right now, but someone from the company got on stage and his comment was I would describe it as a Hong Kong action film, which is probably a pretty good example of explaining the state of play right now there. And I think there's a lot of moving pieces. You've got geopolitical tensions laid on top of all of them. You've got competitive issues on the design business. They're trying to break into the foundry business, kind of a next new leg of the stool for them. But there are a lot of moving pieces, I guess is how I would kick it off. But Chris, you've been following the company for a long time.

[Andrew Homan]

I think they illustrate how hard it is for a very successful company to pivot to a new business. Because Intel's problems in my view are actually a function of their success. They were too successful in producing chips for PCs, too successful in data center for a long time and it made them risk averse and hesitant to invest in new products. They missed the mobile revolution. Famously. Steve Jobs asked them to produce chips for the iPhone. They didn't do it. And now they're struggling with AI because it was always a huge risk to try something new.

[Patrick O'Shaughnessy]

Why does this happen?

[Chris Miller]

I know that's the reason. I've read the Innovator's Dilemma. Like everybody else, I understand juicy existing profit streams, but also this is so.

[Patrick O'Shaughnessy]

Well documented across business history, especially in technology.

[Chris Miller]

These are all very smart people running intel with lots of experience. Why don't they just say we're not going to fall prey to this specific kind of disruption and we're willing to do what it takes, including betting lots of our free cash flow or whatever, to not lose this way again, because we know this is the way companies like us lose.

[Andrew Homan]

I think it's painful for institutions and for individuals to actually embrace the innovator's dilemma because it means you have to sacrifice the products that you made your career on. You have to promote People from different business streams who are working on new products that threaten the old ones. And so there's just a lot of tension that's involved. It's much easier to keep the status quo, especially if the status quo looks like it's profitable. And it was profitable for a long time. And by the time you realize it's no longer profitable, it's often too late.

[Jim Keller]

Interestingly, Andy Grove, one of the initial leaders in Intel Paranoid Survive. Exactly. Wrote a book about this. And when you read the book, you're like, why is this not mandatory reading the entire industry, but certainly the intel management team? Because as you talked about, you missed this transition to mobile. It seems like they've largely missed the transition to AI. And so you've got one of the founders of the company that had highlighted these risks and these paradigm shifts. Now you need to be ahead of them. And for whatever reason, it's been a challenge for them.

[Chris Miller]

Can you describe that paradigm shift that we're going through right now from your perspective?

[Jim Keller]

So I think when you look at technology every decade, there seems to be what I would describe as an architectural change. And so you went from mainframe in the 80s to the PC, then you went from PC to mobile. Cloud also was happening simultaneously. And now this next paradigm shift that we're just in the very early innings of would be AI. And the implications from that, I think, are probably broader perhaps, than any of those other paradigm shifts that we've touched on so far.

[Chris Miller]

Did you see it any differently? You've studied the history of this as much or more than anybody. Is it that simple or is there more nuance to appreciate?

[Andrew Homan]

I think that's right. In terms of the end markets, I think simultaneous to that, there's been shifts in the business models along the way. So the history of the industry started with companies that were entirely integrated. They designed and produced their own chips. Then you shift to the Fabless Foundry model with TSPC producing chips for everyone. And now you're in a position where you've got a small number of AI companies or cloud companies that are not just big buyers of chips. They're also reverting to the prior practice of designing their own chips and getting really deep into the weeds of the technicals of how their chips are produced, because they want to have that entire integrated process where they can control from the software all the way down to the silicon.

[Chris Miller]

Could you pick one company example that's making that transition away from being just a hyperscaler and going vertical and describe what's happening in a Lot of detail, what this actually means in terms of.

[Patrick O'Shaughnessy]

Outlay of investment, what they're actually building.

[Chris Miller]

Why they're doing it. One of these transitions would be interesting to highlight.

[Andrew Homan]

What you mean there's two directions that's happening. It's happening at the chip companies are going up like Nvidia, we can talk about that. But at the hyperscale level, they're all going down. They've all bought AI accelerator startups, they've all tried to integrate them, they're all trying to understand how to bring the networking together. And they're having to hire hundreds, thousands of new employees who have areas of expertise they've never had to hire in before. So it really is the same story, I think at Meta, at Microsoft, at Amazon, they're all essentially following the same playbook.

[Chris Miller]

Maybe describe the logic as you see it.

[Jim Keller]

I think you look at the enormous capital outlay that all these companies are making right now, primarily for Nvidia GPUs and they look at where that spend is going to go in the future, which I think that number is only going higher. And are there alternatives that they can do, at least for certain workloads where they can custom build a chip that is very purpose built for one specific workload, whether that be Search for example, or some sort of social media app that will allow them to potentially lower their cost to serve those customers significantly.

[Chris Miller]

It's fascinating to watch investors try to figure this out and you can find a brilliant investor for just about any argument for where the value is going to accrue in all this. I'm assuming here that AI is going to be a massive, huge thing on par with or exceeding mobile or cloud or whatever. Obviously there's some version of the world probably where that's not true. I don't know. Let's focus on the world in which it is true. I was with a very well known investor in the private markets last week that said, look, we just think it's 100% going to be in the application. And so that's where we're making all of our bets. You're focused much more on the infrastructure silicon layer and everything around the chip. Why are you making that bet? What is it about your reasoning through where the profits will accrue in the future because of this boom that has you focusing so specifically on silicon and the surrounding technologies?

[Jim Keller]

So when I think about the broader AI ecosystem, we think about it as a three layer cake, right? So the bottom layer, chips and cloud, that's where were focused. The middle layer would be the foundational models and then the top layer would be the applications built on top of those. So the foundational models would be OpenAI, Anthropic, Gemini, et cetera. That chip cloud layer would be Nvidia, AMD, TSMC, et cetera. And then that top layer would be ChatGPT, Office, Copilot, Tesla, Full self driving. And I think the challenge right now is that on those top two layers, it's very foggy in terms of who the ultimate winners are going to be and how much value is going to get accrued to those layers broadly. Eventually, yeah, there will be big dollars that go there. But in terms of who actually captures though, I think it's very opaque right now. When I think about that chip layer though, to me almost in any scenario I see that being the area that's going to capture a significant amount of economic rent through this paradigm shift that we're going through right now with AI.

[Chris Miller]

What would be the reason that it doesn't? Let's say that we get to simulate the future in a whole bunch of different ways and in some percentage of those futures, the infrastructure layer does not capture a lot of the profits. It gets big, but there's pricing pressure and it gets competed down to the cost of capital and there's just not a great competitive advantage period to earn money in. Draw that picture or can you draw that picture? How could that happen?

[Jim Keller]

I think there'd be two dynamics. So one would be did these scaling laws change Right now everything we see would say no, they're not going to change. And the more compute you throw at these problems, the better the model, the quicker you'll be able to train the model, et cetera? I think the question is, do you get into a situation where there's much more competition, particularly in that AI accelerator specific area of the market where prices come down significantly? I think ultimately we do want prices to come down. That's the history of compute. But I think you've seen in prior transition, whether it be mobile or whether it was with PC, that silicon layer still captures a ton of value. With PC and server, intel clearly created an incredible business during those periods of time. And then specifically with mobile, you look at companies like ARM and Qualcomm and others that monetized significantly on that trend. Despite there was more competition, prices did come down. But the TAM was so large that these still great companies were built and created over those time periods.

[Andrew Homan]

And I think the PC mobile era both show that. Describing it just as silicon actually misstates the source of Those moats because it was silicon plus software and the interface between the two. Why are there intel chips and half the world's PCs? It's because of the software built on top of Intel's architecture. The same thing true for whether it's, whether it's Apple and mobile or Qualcomm or ARM at the base of it all. So you've actually had a long history of the silicon software interface playing a big role and the software is often a big portion of the moat.

[Jim Keller]

And one other area that's worth mentioning on the scaling laws is with the release of OpenAI Strawberry model, an area of AI that was thought to be compute light, that being inference, is now compute intense as well. For that model to be better at reasoning, it requires much more in a much longer period of inference.

[Chris Miller]

It's really interesting to think about the history just from an investing perspective up until now and I'd love you to reflect on it where if you ask about semi investors in private markets, they'll often tell you just don't do it. It's capital intensive and brutally competitive and you're just not going to make money as a semiconductor investor. If you're a venture investor and in public markets, there are certainly people that have done tons of semis investing historically, but there aren't a lot of semis funds, semis dedicated funds. There's plenty of software dedicated funds, but not a lot of semis dedicated funds. So why is the technology that has undergirded all of technology progress of the last 40, 50 years, why has it been somewhat of a backwater for public and private investors over say the last 20 years?

[Jim Keller]

I think there's a dynamic where there were a lot of semi focused funds 20, 30 years ago and many of them did very well. And then you had this rapid rise of software that captured everyone's imagination and many of the particularly the early stage community pivoted to software and did fabulously well investing behind that trend. And then you had a situation where a lot of that expertise just retired and left the industry. Semis are challenging, they're technically complex. They are capital intensive though I think comparing them to software today, looking prospectively over the next 10 years versus say the last 10 years, my guess is that we're going to see more and more capital start to flow into this hardware layer because so much value I think will get created there and there's just so much need for innovation.

[Chris Miller]

Where do you think the highest prospective returns are within the infrastructure layer? Everyone obviously is focused on Nvidia because that's where all the market cap is. They make GPUs. Everyone's talking about GPUs. There's so much more going on around them. Data centers are getting built out famously by record pace with crazy amounts of power. There's all this cool stuff happening around the GPU itself. So where else are you most interested to study, look, meet with companies and so on?

[Jim Keller]

This ties into a point that Chris made earlier, less focused on that core GPU itself. And there's many companies trying to go directly after that AI accelerator market. I think it is challenging to go after the Predator that is at the very top of the food chain right now, Nvidia being that player. And there's all these interesting areas around that gpu, whether it's interconnect or memory or power related, where you're just going to need innovation. Because the way of doing business that existed five years ago is just breaking. And the data center that existed five years ago, where an intel processor is king of that data center and there's some simple networking and then there's some storage attached to it. The example that we give when we're talking to folks is that essentially you had a tsunami, an AI tsunami that basically wiped that data center out. And Jensen's riding his surfboard on top of that tsunami. And as a result you're seeing everything needing to get rebuilt because the power needs of these GPUs are off the charts. You're trying to connect as many of them together as possible to create super GPUs. And so right now we're connecting 100,000 together. The next step is going to be connecting a million of them together. And the complexity of doing that is creating, I think, a lot of opportunity.

[Chris Miller]

Chris, I'm curious where you've studied the history of this in detail. We won't go through it all. People should read your book if they're interested, which is excellent. But I'm curious if you take all that history up through to today and then you spend a lot of time with companies, with governments, with investors, with everyone in this ecosystem, what people are not talking about enough, that is not yet enough in the mainstream narrative, but you're hearing a lot about in these conversations.

[Andrew Homan]

I think everyone is beginning to register how much money will be spent on compute over the coming years. Decade driven by data center build out, driven by AI. The numbers are staggering. They're exciting if you're a data center builder or a power provider or if you're Nvidia. But that's Actually a bad thing. We'd like compute to be as cheap as possible. And so I think the key focus right now should be finding ways to minimize the amount of money that needs to be spent in order to build out the computing we need for AI. And we're right now at the stage of admiring the scale of the problem, admiring the billions of dollars that will be spent. And actually the real goal should be finding ways to economize, to bring new technology to bear, to find ways to bring down that cost. Because that's going to be one of the key gating factors of AI development, is can we bring the cost down?

[Chris Miller]

Can we talk about the political considerations around both the infrastructure and the first two stacks? We'll leave the apps for later maybe, but if we're talking about just the infrastructure, the fabs, everything that needs to go in to run these things, and then the model layers, US Companies seem to really dominate this, maybe except for TSMC and a couple in Europe. Talk about the most important political considerations, given that if this technology is the most important one ever, it seems like every country is going to want some.

[Patrick O'Shaughnessy]

Answer to their foundation model or their.

[Chris Miller]

Data center or their infrastructure. What are the key variables in the political landscape right now as you see them?

[Andrew Homan]

I think if you start at the level of where chips produced, you've got a whole lot of concentration in Taiwan, as you mentioned, and the economies of scale in the industry are such that you're just not going to have multiple locations at the size of Taiwan where chips are produced. Maybe a couple other countries, Korea, but it's not going to be every country producing its own chips. Totally impossible at the data center level. If you're talking about data centers for foundation models, those are huge, brutally expensive projects. And so there too, although there's a lot of governments that would like to have their own, the scale of investment is such that unless you're sitting on a lot of oil or unless you're a very large economy, you really can't justify the spend. And so that's why if you look at where big data center projects are happening in the us, happening in China, there's a desire to have them in the Middle east, and there's political issues that come up right there because the US wants most of the world's GPUs to be used in the United States and is wary of letting too many get deployed in other countries, both because there's concerns about China and competition with China, but also because the US thinks there'll be real benefit to training Most of the world's foundation models.

[Chris Miller]

If we had a country leaderboard of who is the most advanced in a couple different areas, let's say foundation models and infrastructure, who do you think will be the largest movers up and down over the next say five years?

[Andrew Homan]

I think the surprise player right now is the uae. The Emirates have put a ton of money into AI. Their leadership is very clued in on this issue. They've spent a lot of time studying it. And if you look at the Falcon models that they've developed, they're pretty sophisticated. I think most people wouldn't have expected five years ago that the UAE would be front and center in AI. I think actually this surprising downside player is China. If you look at the huge capital expenditures that US big tech firms are outlaying right now, that's not really matched in China, with maybe the exception of ByteDance. That's partly for US China reasons and controls on technology, but also for China's own domestic economic situation is not making firms excited about putting out billions or tens of billions of dollars in data center spend and investment in AI.

[Chris Miller]

Andrew, can you talk about the moats in this business that people might have a hard time appreciating? TSMC is an interesting one to talk about because everyone knows what a political danger or hotbed this could be. Most of the world's cutting edge chips are built very far from us and very close to a rival. And it seems sort of insane that we just don't replicate this in the US I know we're trying, but the fact that we haven't begs the question why is it so hard? What is it about the infrastructure, businesses that makes them so hard to replicate or copy? It just seems crazy.

[Jim Keller]

It's changed over time, right? Because there was a period of time where intel actually was at the leading edge and was the most technologically advanced manufacturer of chips in the world. And then TSMC leapfrogged them. That probably happened around 10 nanometer time when intel was struggling with that node. So call that gosh, that was probably almost seven or eight years ago. Something in the zip code. And so like why has TSMC been so successful at what they do? I think in part of it, it's because they're just maniacally focused on just one business model, right? All they are doing is the foundry model, whereas the other players, intel has a very large design business that's designing the chips that will get made in the intel foundry. Samsung plays in multiple areas. Memory foundry, they also design some of their own chips but if you're just singularly focused right on the task at hand in making the highest performant chips and then learning from your customers, because they have all the most sophisticated design customers at this point, making their chips on the leading edge at tsmc, it just gives them the ability to continue to improve and sharpen that manufacturing process to a level that I think at this point is very challenging for anyone to catch up.

[Andrew Homan]

The thing that strikes me is the ecosystem in Taiwan is just extraordinarily well developed. We talk about the software ecosystem in Silicon Valley, but there's a manufacturing ecosystem in Taiwan. That's the chemical suppliers, the materials producers, the people who know how to fix the tool when the tool breaks. And they're all right there in a very small country within an hour and a half of each other on the high speed rail on the western shore of Taiwan. And so if something goes wrong in your factory or you need to prototype a new machine or new process, it's very easy to get it right away in a way that if you're in Arizona or if you're in Japan, you just don't have that efficiency. TSMC will say, and 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.

[Chris Miller]

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. Why is that still the case?

[Andrew Homan]

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 tolerance measured in millimeters. For certain parts in chips, you're talking about nanometers, so 1,000 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. Every 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.

[Chris Miller]

Andrew, I'm curious What you think the 5 ish most important companies are right now outside of Nvidia and tsmc.

[Jim Keller]

I 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.

[Chris Miller]

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?

[Jim Keller]

Well, I think ASML 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, because 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 100 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. And then we're going to essentially the 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 in perfect.

[Chris Miller]

What do you think are the top concerns of the US Government? We can talk about chips act. We can talk about where we will accept external capital to finance companies or projects just by revealed preference, what does the US Government care the most about? And in your interactions, how on the ball are they? We're talking the day after Gavin Newsom vetoed this bill in California, which I think technology is very happy about how well calibrated are our politicians around this stuff. Do you think they've been effective? What are they doing?

[Andrew Homan]

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. Government 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 issues because our entire economy is levered to Moore's Law.

[Chris Miller]

Why can't China catch up if so much money, so many incredibly smart people, so much talent there. Obviously the will seems like more in, 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.

[Andrew Homan]

No one can do it on their own right now. The US can't produce cutting edge chips 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. In 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 because this.

[Chris Miller]

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 couple fold?

[Jim Keller]

I think there's been a view, maybe take the biggest of them all, Nvidia. And 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. And 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. And I think people talk about all the time, it's in the newspaper all the time, etc. But I think people have this fear that oh my gosh, the stock is too expensive or it's run, 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 debt in line with the stock price. And 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.

[Chris Miller]

Can you talk about the changing cost structures and business models of the digital software world in this new era where it used to be very people engineering intensive, now 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.

[Jim Keller]

You'Re seeing this struck me probably 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? So 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 a billion dollars. In 2025 it's 10 billion. And then I think the latest that that Larry Adelson 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 and lead. That'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 and D heavy and programmers, et cetera. And is that now changing where just the cost of business is being compute and chip driven versus people driven? I think you're seeing that shift in the hyperscaler, Capex numbers, et cetera.

[Chris Miller]

Can you outline what you view as the key sectors within semis? Whether that's design, whether that's manufacturing, whether that's whatever. What do you think of are the key 3, 4, 5 areas that matter most?

[Jim Keller]

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, and that's why you're seeing so much interesting innovation on the back end 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 3 nanometer. How can we package that chip with other chips in memory, for example, and get that packaging to be as efficient as possible? Because historically people just hadn't cared about it because you're 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, like coas is probably a term that many people have heard thrown around that was actually limiting the number of Nvidia GPUs are able to get manufactured. And so finding those areas that historically perhaps have been ignored are now actually some of the most interesting.

[Chris Miller]

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.

[Andrew Homan]

I 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 in 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.

[Chris Miller]

And do you think about returns? I know you and I have talked about this in the past. It'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 cost, the S&P 500 or something.

[Jim Keller]

Like that at the chip player? It's interesting when we look at opportunities on the private side, this is an area 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. Interestingly, 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 any liquidity, premium, et cetera. 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. Because, 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 and M and A strategies to really beef up their internal flagship efforts.

[Chris Miller]

Talk about antitrust. It seems like a really important, I don't know, 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 can impact your returns, maybe. What's the state of play with antitrust and what's going to be allowed?

[Andrew Homan]

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. Hard 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. 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. 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. It depends on the state of US China relations. And when's the next presidential summit? That's what matters more than the actual substance of the antitrust.

[Chris Miller]

Can you give an example of that? Just a case study of that playing out.

[Andrew Homan]

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.

[Chris Miller]

And why can't we just say, okay, why isn't there some way around that?

[Andrew Homan]

I think this is a really interesting question. And 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 is 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.

[Chris Miller]

There was this meme going around earlier this week that in the late 90s we really didn't have an Internet bubble, we really just had a telecom bubble. Why might this not be of a similar character or nature to that?

[Jim Keller]

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 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, and 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 op hopping. It would be 500% of operating cash flow in a given year. And then you look at what was the utilization rate of that fiber in the ground. And I think as of even as late as 1990 and early 2000, only 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? If you look at their operating cash flow in this case, so cash to the business 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 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. The 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 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 they'll 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.

[Chris Miller]

So if I were to take your analysis and apply it to today, the place that looks like telco is the foundation model companies, they are spending 5x there or way more. Their operating cash flows, they have negative operating cash flows. That does exist. So does that mean they're all toast if we get to a $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 stream and that these upstarts, even the OpenAI's of the world, are in trouble?

[Jim Keller]

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. And 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.

[Andrew Homan]

It ties back into the Middle east which we discussed before, because you're looking for very large pools of capital. That's one of them.

[Chris Miller]

Will that be feasible? Will the US we have in various cases pretty close ties to the countries with the most money. Talk about the range of feasibility.

[Andrew Homan]

I think the US is pretty comfortable with Middle Eastern governments investing in US based companies to build US based data centers. And we've seen for example Microsoft Mubadala announce a joint investment vehicle. I think the US is a lot more worried about investment in the Middle east because then the US has less leverage, the Middle east has more. Certainly there will be data centers built all over the world, including the Middle East. But the US Government really doesn't want the most advanced frontier data centers being built in the Gulf rather than in the US and so there's a lot of regulation coming down the pipe right now about that particular issue.

[Chris Miller]

What are you most worried about?

[Andrew Homan]

I worry about the time horizon in which we see the return that Andrew's talked about. I 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. I think 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. There'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.

[Chris Miller]

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?

[Jim Keller]

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? I'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. And when I think about Nvidia and what they've done, this was a company that was initially a chip company 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 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. And 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? I think when you look at the big customers that we just talked about, they are 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. You had a situation where when Apple announced the iPhone, ATT 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. And you fast forward 14 years and Apple's market cap now is 3.5 trillion and ATT is 150 billion. Apple just extracted all the economics out of that transition, capturing obviously the hardware with the iPhone, also the software with the App Store. 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 dumb pipe. 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. Because 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. And I think there's a real incentive to have a healthy ecosystem, generally speaking.

[Chris Miller]

What are the corporate strategy options available to those players that want to accomplish that? Just playing forward, the Apple AT and T thing, how do you avoid that happening to you this time?

[Jim Keller]

Well, they're trying to develop their own chips and so that custom ace of work is probably very high in the list of what they're trying to do. And I think they're very forward leaning. We 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. I think we will see more and more successful 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 then I think the third bucket's going to be the startup ecosystem providing value to help them diversify.

[Chris Miller]

I know you said maybe less interesting to go directly after the GPU and better to attack the area surrounding, but 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?

[Jim Keller]

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. That will be an area, I think, that could end up proving to be a challenge for them. How does Nvidia respond to that? They can obviously make custom chips that go after these very specific markets too. To date, they've chosen not to do so.

[Chris Miller]

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 whoever you want. What three people would you pick?

[Jim Keller]

I think it would definitely be someone at building out the infrastructure at one of the large hyperscalers they're on the leading edge of all of 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, someone at Nvidia. Right. You can say who that would be.

[Andrew Homan]

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 because 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. 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. But considering the political side as well.

[Chris Miller]

What 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?

[Andrew Homan]

I think on hyperscaler buildout, 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 going to be buying? But also B, 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.

[Jim Keller]

Yeah. I think the government piece that Chris brought up is really important here too. Right. And just understanding what is the focus, particularly of 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 US operating at a much more higher level. I think that's another key question and topic to explore.

[Chris Miller]

What about beyond the hyperscalers? Half the market. What about the other half? What's going on there?

[Andrew Homan]

I 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 super power efficient, to provide just the right amount of processing power for Edge devices. And that'll be different for cars, I think, than it will be for phones or for wearables or others. Unlike Datacenter, where we're inning three or four right now for data center, we're still in inning one on the edge.

[Chris Miller]

What 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?

[Jim Keller]

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, the 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 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. 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 just 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 video makes a killer gaming laptop. But 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 200ft 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 their 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? Companies 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 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 Core Weave and Nvidia did an ingenious job really bringing them up to scale where they can get chips out six months before. I think if you look at Coreweave, they had their H1 hundreds out in March of 2023 and, 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 and 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.

[Andrew Homan]

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'd 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 for. 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, meaning.

[Chris Miller]

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.

[Andrew Homan]

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.

[Chris Miller]

What about power? Any commentary on power? There'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.

[Jim Keller]

So maybe this would be a little bit of controversial view. My thought on the so power's 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. And sure enough, capitalism finds a way. Capacity comes online and then there was actually oversupply in that case. And so with power in particular, when I talk 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 nameplate capacity will be? Just because there's almost like a double ordering dynamic. When they're telling the planner in that city or that state how much power they want, they're going to give the absolute 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, talking about intelligence at the edge, the broader energy infrastructure in the U.S. i think people don't actually have 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, and then all of a sudden maybe there is actually more excess capacity than people. It's a little bit of 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.

[Andrew Homan]

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. And I think now Nvidia's getting a lot of calls from its customers saying, hey, we'd like more performance. But also, you got to take power really seriously.

[Chris Miller]

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. Talk 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 way the other direction with a really hands on approach. So how and why are you doing it that way?

[Jim Keller]

Yeah, it's funny, as we spend more time in this and pulled on this thread, I think we've gotten more and more excited about the opportunity here. And 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 on 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? So 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. Not 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.

[Chris Miller]

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 like the nature of the people building these things.

[Jim Keller]

I 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 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 etched with Gavin does fascinating work there and I remember laughing with him the first time I met him. I was like did they teach you any of this at Harvard? And he's nah, not really. But it is, I think for the most part. I think that's probably more 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.

[Chris Miller]

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 semis ecosystem right now. So 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?

[Jim Keller]

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, Stephane 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 they will come into those pre IPO rounds. But 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 out's 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. I 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.

[Chris Miller]

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?

[Andrew Homan]

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 for the first time since COVID but because of the politics, because 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 CPUs at moderate scale, that is going to be the company that defines where China is on the.

[Chris Miller]

What's the scale comparison to Nvidia or something?

[Andrew Homan]

It's small right now relative to Nvidia and they're trying to ramp up and the US government's 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?

[Chris Miller]

Can you tell the Huawei story, how it got to here and what's happened?

[Andrew Homan]

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? Hard 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 an almost monopolistic producer into a Chinese market that is constrained both by the US and the Chinese governments. And so the company itself has had to shift a lot and now it's the Chinese AI monopoly player.

[Chris Miller]

And maybe describe what the US government did vis a vis Huawei just to complete the story.

[Andrew Homan]

So the US government doesn't want China to produce cutting edge chips, and so Huawei works with with smic, the leading Chinese chip maker to actually manufacture its chips. SMIC 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.

[Chris Miller]

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. What about just 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 pine on each of those three.

[Jim Keller]

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. They have. And 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 happen 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's not making its own fab, right. They're making their chip at tsmc. But 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 actually be far more attractive than software. And so you can look at a semicompany 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. That's how I frame that.

[Chris Miller]

What about the word bubble? When does the word bubble enter your minds, if at all?

[Jim Keller]

I think when people talk about bubble, it means you probably aren't in a bubble. They usually. One rule of thumb, it's usually only afterwards.

[Chris Miller]

First rule of fight club.

[Jim Keller]

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 12 months ago. And I think it's proven not be the case to date. 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. But 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, particularly 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, that'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 this actually can create opportunity because I think we know the end point 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.

[Chris Miller]

Chris, 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?

[Andrew Homan]

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 notice the DRAM cycle because they were just less protected. And 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. Really a niche market before then, and PCs made them a mass market.

[Chris Miller]

How do we get to this state of the world where so much of the manufacturing is done overseas?

[Andrew Homan]

I think there were two drivers of the shift overseas. I think one was that US 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 and you've got higher costs and less developed ecosystem, you'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.

[Chris Miller]

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. Or 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 semi's industry?

[Andrew Homan]

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. And 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.

[Chris Miller]

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?

[Andrew Homan]

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. And 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.

[Chris Miller]

And the knock on effect of that would be just a more efficient system.

[Andrew Homan]

More efficient system, but also potentially changing.

[Chris Miller]

Lower cost of computer, lower cost of compute.

[Andrew Homan]

Yeah, and potentially changing who's good at producing them.

[Jim Keller]

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. And 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, does that end up being a bottleneck that slows down innovation?

[Chris Miller]

Just 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?

[Jim Keller]

I think it's got to come from the intellectual property piece. Right. And 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?

[Chris Miller]

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?

[Jim Keller]

I think it's broader than that, to be totally candid. I think you've got, in Silicon Valley in particular, you've got thousands of engineers, tens of thousands, probably frankly even hundreds of thousands that are very technical. Or are they all going to be startup founders? Definitely not. I think it is actually probably at 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 semi industry for sure. You highlighted Jim Keller, his reputation and then clearly precedes him and there's others. But I think in the broadly Speaking. I don't think you have quite that same pain point.

[Chris Miller]

What do you two most commonly debate or disagree on?

[Jim Keller]

I don't know if we describe. 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 D.C. and just trying to understand what it means and what the intentions are of the various restrictions. 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 and D side. Chris has got incredibly tight relationships there. I remember I told you I was in D.C. last minute and then you had me meeting with Biden's chip liaison. I was in the West Wing of the White House four hours later. So you definitely have those people who 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 at reading the tea leaves. A lot of this. Yeah.

[Andrew Homan]

I think 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. You need to understand the manufacturing, the ip, the end users in the data center, the supply chain is longer than in a typical software company, for example. You've got to understand where all the players are to see where technology is going.

[Jim Keller]

That's a very interesting point. Right, Because I think you look at software that tends to be much more siloed and, and in the semiconductor ecosystems, when we touched on these different players earlier in the conversation, where so many different folks just interlap and it's very interwoven where everything from semicap that's making the tools to the foundry player to the design folks. And 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, et cetera. But 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.

[Andrew Homan]

For example, I was struck when I first started learning about the semiconductor industry. I 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.

[Chris Miller]

What are the most sensitive parts of the supply chain?

[Andrew Homan]

The manufacturing stuff 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 of 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 99.9999% precision. And 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.

[Chris Miller]

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 5, 10 years and how big is it today?

[Jim Keller]

Today the semiconductor industry is probably $700 billion, give or take. Software's probably a little bit higher than that, like $800 billion. When 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. Is that because being the primary resource that's going to drive AI.

[Andrew Homan]

I think 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. So 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 and 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 on 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.

[Chris Miller]

Anything 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.

[Andrew Homan]

The other 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. And 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 in 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.

[Chris Miller]

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.

[Jim Keller]

Yeah, absolutely. I think that ties into that broader edge AI bucket. And we talk to a lot of these companies, they're more analog based 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. And so I think anyone who's on the edge should realize that that wave is coming for them next.

[Chris Miller]

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?

[Andrew Homan]

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 semiconductor technologies 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.

[Jim Keller]

So I've been living and breathing semis here in particular over the last nine months. So this is 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 D.C. 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? How do you motivate that very 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 help. Creating that culture is something that I try to think about because I think it's really important for the US 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. And 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.

[Chris Miller]

Having read the book and talked to you a lot about what you're building at Maverick Silicon, I'm really excited to see the companies that start to come through here. 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. You'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 Etube?

[Patrick O'Shaughnessy]

You.

[Jim Keller]

The caveat here will be this is excluding family. 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 had such a huge impact on who I am today. That probably is the kindest thing that anyone's ever done for me and 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. And 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 a really valuable lesson. I just encourage everyone take the time to do that because I think it's important.

[Andrew Homan]

I'd mentioned a mentor as well, my advisor, when I was doing my PhD in history, John Gaddis, who often when you have a PhD advisor, your advisor wants you to study what they study. That 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. And 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 had the right set of tools, you could have confidence to go into a new area, understand what was 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.

[Chris Miller]

The world's infrastructure is changing. Thank you for teaching us about what's going on. Thanks for your time.

[Andrew Homan]

Thank you.

[Jim Keller]

Thanks.

[Patrick O'Shaughnessy]

If you enjoyed this episode, check out joincolossus.com there you'll find every episode of this podcast, complete with transcripts, show notes.

[Chris Miller]

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[Patrick O'Shaughnessy]

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