How Gavin Baker Invests in AI, and Where the Bubble is Going Next

Ejaaz: Gavin Baker is one of the most prolific AI investors that almost no one has heard of. Ejaaz: He spent the last 20 years investing in some of the biggest AI companies before Ejaaz: they became household names. Ejaaz: He was an early backer of NVIDIA, as well as Cerebris, which IPO'd very recently. Ejaaz: And he has a very concrete thesis, which is AI isn't in a bubble. Ejaaz: It's quite the contrary.

Ejaaz: It's in a super cycle. He says that by looking at the watts, Ejaaz: wafers and tokens, the infrastructure of AI. Ejaaz: He's identified some of the key bottlenecks and constraints, Ejaaz: and he has one simple thesis. Ejaaz: The biggest returns that you can get in AI is in electricity, Ejaaz: power, and silicon fabrication. Ejaaz: It's got nothing to do with SaaS software as a service. Ejaaz: It's got nothing to do with chatbots, such as Anthropic or OpenAI.

Ejaaz: It all filters downstream from Ejaaz: semiconductors, the picks and shovels that build the entire AI industry. Ejaaz: And he's been expressing that interest to the tune of $4.1 billion. Ejaaz: While most people are calling the AI industry a complete bubble, Ejaaz: he thinks that it is a generational buying opportunity specifically for AI infrastructure, Ejaaz: and he makes the thesis very clearly in his fund.

Josh: And if you hear these constraints that he's talking about, this AI infrastructure, Josh: you realize that this kind of sounds pretty familiar. Josh: We've heard this thesis before, and that's because on the show, Josh: many times we've covered an investor by the name of Leopold Aschenbrenner. Josh: He has been around for three years. He just published his most recent 13F, Josh: and he has a lot of the same core philosophies.

Josh: Now, here's the difference. Leopold's been around for, what, three years? Josh: Gavin's been doing this for 20-plus years. And when we're comparing these two, Josh: Leopold actually has almost three times the assets under management. Josh: But there's this great quote that I was reminded of from our producer Luke before Josh: the show. It's like, okay, you can beat Warren Buffett over a year, Josh: but can you beat him over multiple decades?

Josh: And Gavin Baker has a track record that proves that he might have a slightly Josh: different outlook on this investment thesis.

Josh: For those who don't know, Gavin Baker, he is the basically founder of this company Josh: named a Trades Management. Josh: They are an investing fund, and he has spent 20 years investing in NVIDIA. Josh: Now, if you've invested in NVIDIA for 20 years, it's a miracle he's still working Josh: because those are some pretty incredible returns.

Josh: Some of the early wins that we've recently seen include companies like Cerebris, Josh: which he was a very early investor in, Josh: Cerebus, if you'll remember, just IPO'd for an ungodly amount of money. Josh: Same with this company, Estera Labs. And there's a lot of other companies that Josh: I don't think you've probably heard of before that we're going to cover in this episode.

Josh: As we walk through his portfolio and his guidance on where he sees the AI industry Josh: going in terms of investment and where all the opportunity lies. Ejaaz: So then the question becomes, what is he investing in and why is he investing in it? Ejaaz: Well, if we look at his recent 13F for a tradies management, Ejaaz: which is the name of his fund, They have about $4 billion worth of AUM.

Ejaaz: We look at some of his biggest positions and unpack what some of these companies actually solve. Ejaaz: It kind of points towards the bottleneck that Gavin references in a bunch of Ejaaz: his different interviews as to where AI is going. Ejaaz: So he has some pretty sizable positions in some companies that a lot of people Ejaaz: may not have heard of purely because they're quite unsexy.

Ejaaz: So he has an almost 9% position, so 10% position of the fund in this thing called Ejaaz: Astera Labs. Now, Astro Labs can be described as kind of like the connectivity layer between GPUs. Ejaaz: So if you imagine a data center, you have GPUs, they're kind of like the engine that can like pre-train Ejaaz: post-train your model and also like inference your model. But in order for these Ejaaz: GPUs to work, they need to traverse a bunch of different data.

Ejaaz: They need to send data between themselves. They also need to access data from Ejaaz: all these memory chips that they store this data on. Ejaaz: Now, in order to access this, you need some kind of a plumbing system. Ejaaz: And I'm being very high level on this because I'm not going to pretend that Ejaaz: I know the intricacies of all of this. Ejaaz: Astero Labs is a company that essentially fixes that.

Ejaaz: The problem it solves is as AI clusters scale to hundreds of thousands of chips, Ejaaz: The bottleneck stops becoming GPUs specifically, but it starts becoming that Ejaaz: transfer window and sending the right data at the right time, Ejaaz: accessing the right data at the right time is what the plumbing system that Astro Labs builds.

Ejaaz: Now, I haven't heard of Astro Labs until we started researching for this episode, Ejaaz: but I remember another company being the exact same case called Cerebrus Labs, Ejaaz: which is what Gavin was talking about almost like, I think like six months ago, which is quite long, Ejaaz: given the relative scale or timeline of AI. Ejaaz: And then the next thing I know is that they IPO'd for like, what was it, Ejaaz: like $60 billion, and it's just been like, it's up 40% since the IPO.

Ejaaz: So just kind of point towards these different trends. Asher Labs might be something Ejaaz: significant on that horizon. Josh: Yeah, Cerebrus is one of his earliest investments. I mean, he was in Cerebrus Josh: very early in the company's lifetime, which means he's bet on this thesis for years. Josh: There's also a few other ones that he's been betting on for a long time.

Josh: I mean, NVIDIA being that flagship one, being involved in NVIDIA for 20 plus Josh: years is pretty incredible and still having conviction all the way through is impressive. Josh: Gavin was recently on two podcasts where I was listening to him speak about his NVIDIA position.

Josh: And it's very clear that he believes that they're going to be able to maintain Josh: these profit margins and maintain the demand as well, which means he's putting Josh: NVIDIA on a clear path to getting close to $10 trillion in market cap. Josh: It's only halfway there right now.

Josh: A few other noteworthy mentions are Micron, which we discussed on a previous Josh: episode, which I would highly recommend going to watch in terms of the AI investment Josh: stack and where all these companies lie. Josh: Micron is one of the largest memory makers and a crazy statistic about Micron. Josh: A year ago, it was sub $100 billion. Josh: And as of recording this, it just eclipsed a trillion dollars in market cap.

Josh: It got a 10X in a single year. And it's a testament to how important that memory problem is.

Josh: Now, perhaps some of the less noteworthy companies that are interesting, Josh: EGES, there's one I want to highlight for you in particular, Josh: because I feel like you're going to like this one, is Unity Software. Josh: And for those that don't know, Unity, I mean, I know this very well as a gamer, Unity is a game engine. Josh: There's a lot of popular games that are built using this 3D rendering software. Josh: So why would someone who's investing in AI be investing in Unity software,

Josh: the thing that makes my video games? And the answer is the 3D game engine. Josh: Unity is a world model builder, and it has a really deep understanding of physics Josh: and the way the world works and the understanding of textures and lighting. Josh: And when these AI companies are trying to build AGI, they're trying to build humanoid robots. Josh: A big part of that is simulating virtual environments and virtual datasets that Josh: allow these robots to be trained in.

Josh: And Unity just still happens to be one of the best ones. So I feel like that Josh: one I want to highlight specifically for you, EHS. Josh: As the world model Maxi, there is a clear path in which a gaming company that Josh: is known for a scanning engine becomes a pretty serious player in the world of AI. Ejaaz: Yeah, the whole thesis behind world models is pretty simple. Ejaaz: It's AI models or LLMs currently understand the world through text, through books.

Ejaaz: It's kind of like a student sitting in a library, but it doesn't actually have Ejaaz: experience of the real world. Ejaaz: World models basically unlock that. It's like putting a game character into Ejaaz: a simulated environment and understanding the physical reality of how the world works. Ejaaz: If it works, if I drop this phone, if I kick a ball, like what happens? Ejaaz: What are the next consequential steps? What do you do?

Ejaaz: World models effectively fix that. And there are very few players that have Ejaaz: like built this out at scale. I think currently the leader is probably Google with Genie 3. Ejaaz: They actually released a new model called Gemini Omni recently, Ejaaz: which kind of like does this at scale, but it's not quite like where it's meant Ejaaz: to be. It hasn't quite had its ChatGPT moment. Ejaaz: What I like about Gavin in particular is he kind of has this barbell.

Ejaaz: I don't know if you noticed this, Josh, where he's kind of old school and he's like, Ejaaz: people are going to need GPUs. People are going to need memory. Ejaaz: I'm going to invest in the biggest players, Micron and NVIDIA. Ejaaz: But then he has this kind of forward-looking thing where he's like, Ejaaz: I think that's where the puck is going to go. Ejaaz: And so I think, let me invest in Cerebrus because I think inference is going to be super important.

Ejaaz: And then let me invest in Unity because I think world models are going to be Ejaaz: the future of how we train robots and future LLMs.

Ejaaz: So he has this kind of like barbell approach. Now, one thing that I see in his Ejaaz: portfolio over here as well is this, well, there's two companies, actually. Ejaaz: It's this company called Positron, which kind of creates inference chips. Ejaaz: Now, if that sounds similar, it's very similar to Cerebrus. That's exactly what they do.

Ejaaz: And it's around this entire thesis, which Gavin has spoken about on his recent Ejaaz: interviews, which is the infrastructure stack, specifically the training stack Ejaaz: for AI models, is moving from pre-training to something more focused on post-training. Ejaaz: Now, if you've been involved in the AI sphere, generally, you kind of had an Ejaaz: idea that this shift was happening. But Gavin is all in on this thesis.

Ejaaz: And if you have a model, it still needs to understand new information that comes in, new data. Ejaaz: It needs to update it. Just because you pre-train it on a specific data set Ejaaz: doesn't mean it's going to be a genius for the rest of its life. Ejaaz: It still needs to learn new information. Ejaaz: That happens in the post-training layer, and it requires a lot of inference.

Ejaaz: Secondly, if you need the AI model to actually think about the problem more, Ejaaz: in the same way that we take in new information, we're like, Ejaaz: hmm, I wonder if this angle makes sense or if another thesis maybe applies. Ejaaz: That's known as reasoning. You need a lot of inference. Now, Ejaaz: the estimates are the cost or the revenue opportunity from inference alone is Ejaaz: worth around 5 to 10x more than the amount of compute that is being put into pre-training.

Ejaaz: So, AI labs and chip makers are suddenly making this big shift. Ejaaz: Like you've seen NVIDIA create a bunch of different GPUs that are aligned to Ejaaz: inference to allow agentic kind of exposure. Ejaaz: And so we're seeing Gavin express this through his different investments on inference alone. Ejaaz: And the final point that I'll make is Gavin made a really cool point, Ejaaz: and we're talking about this before we started recording, Josh, on China specifically.

Ejaaz: It's been very much like China versus the US when it comes to the AI race. Ejaaz: China has a very unique kind of setup where they have an abundance of energy Ejaaz: and the ability to scale chip manufacturers. That's something that the U.S. Ejaaz: Currently struggles with. That's why they outsource a ton of stuff to the likes of TSMC on Taiwan.

Ejaaz: And what he basically explains is that China has a unique opportunity to create Ejaaz: infrastructure or chips specifically that are going to look very different to what the U.S. Ejaaz: Is creating because they're focused so much on inference. Ejaaz: So Gavin, you could say, is leading the charge in the U.S. through his investments Ejaaz: on building or taking a bet on the U.S. Ejaaz: Infrastructure setup for inference. And I think that could be a huge opportunity in the future.

Josh: And it's worth noting that this bet also isn't only for the upside. Josh: There is a large put position here in an ETF named QQQ. Josh: Now, for those who are not familiar, it covers the NASDAQ 100. It's a basket of stocks. Josh: It's the second most traded ETF in the United States. And it's been performing incredibly. Josh: In 2023, it was up 55%. 2024, 25%. 2025, 20%. And so far in 2026, Josh: already up 17%. So QQQ, as an index fund, has been doing incredibly well.

Josh: It's easy. It's a basket of the top 100 stocks. Gavin is saying, Josh: I'm shorting against that. I think that's going to go down. I think you're wrong. Josh: And what this tells me is that he believes strongly in the AI play in the sense Josh: that he's going to invest in the key makers who are solving these bottlenecks. Josh: But as a market-wide general sentiment, he doesn't appear to be very bullish.

Josh: And this is a hedge against that downside protection, where if the market does Josh: start to fall apart in ways that are less favorable, even though AI still wins, Josh: he has that hedge with QQQ. Josh: We can kind of break this down into a few bottlenecks that he believes are going Josh: to be most important when it comes to investing. Josh: These key things that he is looking at in terms of what the world of AI is going

Josh: to need as we progress forward. What are the actual constraints? Josh: What do they look like? And then how do you invest? How do you convert these Josh: into actual dollars that you could put into companies to earn you money?

Josh: And there's four of them. Josh: The first one is verticalized small language models. Ejaaz: If you think about LLMs in general, like the chatbots that you talk to, Ejaaz: such as Claude and ChatGPT, they're generalized LLM. Ejaaz: So they have a wide understanding of the world in context, and they'll be able Ejaaz: to answer like specific questions. Ejaaz: But it's another thing, training a model around a specific vertical or specific

Ejaaz: problem that you're trying to solve. Where do these specific problems exist? Ejaaz: Well, in enterprises that are deep on solving a particular problem or companies Ejaaz: that have made or formed a niche in their particular subsector. Ejaaz: Now, verticalized small language models basically address exactly this. Ejaaz: They're frontier models, but highly optimized towards running efficiently on Ejaaz: specific enterprise data or locally on device.

Ejaaz: Now, we have spoken about on device or locally run models before, Ejaaz: purely for the case that there's a bunch of data in your phone or the devices Ejaaz: that you use that are highly personable to you, but you don't necessarily want to give up. Ejaaz: And companies don't necessarily have access to that. For example, Ejaaz: medical records, financial details.

Ejaaz: I saw OpenAI release a financial AI agent that can get access to your bank account, Ejaaz: But it can't actually act on it because there's a lot of personal identifiable Ejaaz: information that you don't want to share, such as your social security number, banking details, etc. Ejaaz: Now, locally run models or these SLMs can solve that kind of a problem. Ejaaz: And Gavin is making a huge bet that these are going to become huge in the future.

Ejaaz: One company that I've noted that Gavin is hugely bullish on is Apple. Ejaaz: Although he doesn't express an investment interest, he knows or thinks that Ejaaz: Apple is going to be the device maker, one of the major device makers, Ejaaz: Allows for these locally run models to run on their devices. Ejaaz: Now, in a world where that is the future, you can start thinking of a world Ejaaz: where maybe Claw doesn't need to be the model that you need to interface with every day.

Ejaaz: Maybe you need a personalized AI agent trained on your own data, Ejaaz: and that's what these SLMs end up eventually becoming. Ejaaz: Now, that's the generalized version of it where you can run it on your own phone, Ejaaz: but a bunch of enterprises will run these highly optimized and specialized models Ejaaz: to train on their proprietary data, which ends up helping them sell a product Ejaaz: or market a product much better.

Josh: Oh man, Apple's in such a good position there. So good. I can't wait for WWDC. It's coming. Josh: We are just a few weeks away from Apple's developer conference where they're Josh: going to unveil all of this new AI software that's coming and what that looks Josh: like integrating the hardware. Josh: That's going to be huge. We will be covering that. I'm so excited to talk about Josh: that. In terms of the next pillar of this, it is sovereign infrastructure.

Josh: We always talk about this, that the speed of bits is so much faster than the speed of atoms. Josh: I mean, When you think about AI infrastructure, the quality of models has gone purely exponential. Josh: The amount of intelligence we could generate per watt, the amount of intelligence Josh: per token, is up into the right only. Josh: What isn't up into the right at nearly the same rate is the speed of physical Josh: deployment, because that itself is the mode.

Josh: It's very difficult to take hardware that is incredibly complicated. Josh: We're talking about transistors that are down to the atomic level of precision Josh: and deploying them at scale in a world in which our infrastructure is already Josh: suffering. I mean, with the acceleration of electric cars, the grids have already Josh: been feeling a little bit more restrained. They're kind of at max capacity. Josh: Now they have the energy problem. Now they have the chip problem.

Josh: Gavin is very strongly betting on the fact that infrastructure is hard. Josh: It's going to take many, many days to months to years to do. Josh: And he's betting on the people that can compress that into weeks. Josh: So the speed of the physical deployment itself is the moat. Josh: He's kind of narrowing in on who the companies are that are able to deploy as Josh: fast as possible. When I think about this, my first thought is SpaceX.

Josh: And how quickly they've been able to build Colossus and then rent that out to Josh: Anthropic and I'm sure companies in the future. Josh: But that infrastructure pillar is one of the key ones that he's looking at. Josh: I think everyone, we looked at. Josh: Leopold's portfolio as well, that was a core component of that. Josh: It's just, it's really hard to build things. And whoever can build things, Josh: they can sell it for a lot of money.

Josh: SpaceX, their largest line item now in terms of revenue is the data center that Josh: they're renting out. It has nothing to do with rocket ships. Josh: And I think that's a testament to how important this pillar is. Ejaaz: So it's speed that he cares about and he thinks that it's important, Ejaaz: but it's also like the cost, right? Ejaaz: He keeps referencing this metric, which is performance per watt. Josh: Perf per watt.

Ejaaz: Yeah, perf per watt. And what he's talking about here is companies are increasingly, Ejaaz: companies being AI labs, are increasingly caring about how many tokens can you Ejaaz: generate per watt, right? Ejaaz: Because if you think about spending billions and trillions of dollars, which is what...

Ejaaz: Five companies are currently spending this year alone on GPUs and compute to Ejaaz: kind of like power these things or electricity to power these things, Ejaaz: You want to get a lot of bang for buck, especially if you're scaling to the Ejaaz: size that most of these hyperscalers are doing.

Ejaaz: So if you think about it, if I prompt Claude and if I prompt ChatGPT and Claude Ejaaz: gives me an answer that cost me two cents and ChatGPT gives me an answer that cost me $1, Ejaaz: I'm probably going to end up using Claude, even if it's like hypothetically Ejaaz: like say 95% of the intelligence hypothetically that ChatGPT has. Ejaaz: Because the point is you can prompt Ejaaz: it even more and eventually get to the answer for a lot less of cost.

Ejaaz: So cost becomes a huge thing. This week alone, Microsoft and Uber announced Ejaaz: that they are effectively reducing their exposure to clawed code because their Ejaaz: annual budgets kind of like got sequestered in about four months. Ejaaz: So the point is like the cost of getting access to this intelligence matters a lot.

Ejaaz: And you see this across Gavin's investment portfolio with Cerebras, Ejaaz: with Alexa, Positron, and with Astro Labs, which basically, like, Ejaaz: what I've noticed is he identifies these really niche infrastructure bottlenecks, Ejaaz: and he basically makes one simple bet.

Ejaaz: He's like, yeah, if this company solves that, the performance per watt gets Ejaaz: to this specific level, which means that AI Labs are probably going to buy more Ejaaz: of these GPUs or more of these companies or more of these things, Ejaaz: and you end up with a bottleneck being resolved by one of these different companies that he's betting on.

Ejaaz: So his thesis actually is quite simple, although it's quite complex, Ejaaz: which is I'm just going to focus on the AI bottlenecks at the infrastructure level. Ejaaz: And if I can identify a company that can increase performance for what by this Ejaaz: amount, that can make tokens this amount cheaper, then my bet is those companies Ejaaz: are going to be valuable and will either IPO or get acquired for a large sum of money.

Josh: And the thinkers to know for the section, for those looking to copy trade, Josh: Gavin, Estera Labs, we have Cerebrus, we have Sci-5, and we have Positron. Josh: Those are the four companies that are really critical in this sector.

Josh: Now, the fourth and final is a combination of energy and space. Josh: Because, I mean, like we talked about in the previous point, Josh: the terrestrial grid very much limits energy. Josh: And it's very difficult to earn new energy. I think a statistic like 40% of Josh: new data centers have very strong petitions against them, or lobbying against Josh: them, people protesting they do not want these data centers.

Josh: There's a lot of resistance to them. And the way that we solve this is twofold. Josh: One is creating energy out of the box. It's kind of portable energy you could Josh: bring to these data centers, power them with a smaller phone. Josh: That's companies like Bloom Energy, who Leopold is very bullish on. Josh: But then there's also the orbital compute part of this, which is what Gavin Josh: has really shifted his focus to.

Josh: Now, the first largest company in this sector, of course, is SpaceX. Josh: They're the only one who is capable of being the highway to space, Josh: to delivering actual payload to orbit, to getting maths and data centers in Josh: low-end orbit that can generate enough intelligence and power that can funnel this. Josh: I think the space stack is a little bit bigger than just SpaceX.

Josh: I was surprised to see there wasn't more allocation of space stocks in his portfolio, Josh: given the fact that he believes this is such a huge industry. Josh: Perhaps the reality is that it's just too early and that SpaceX is the linchpin Josh: to unlocking this industry and just kind of closely evaluating Starship V3 launches. Josh: We had a Starship launch last week. It performed very well. Josh: Without Starship functioning, we don't get energy in space. We don't get racks

Josh: to orbit. It is required because the amount of payload is so large. Josh: So I'm sure SpaceX is the one to watch. There's a lot of other second order Josh: companies that can be impacted by this.

Josh: I think we want to get to the end of this with the question that a lot of people Josh: are going to be asking, which is why is this not just the dot-com bubble again? Josh: And Gavin was asked this question many times. He has some pretty strong answers Josh: and I kind of believe him. It seemed his case that he made was pretty convincing. Ejaaz: Okay, so the way I think of his case is as follows. Ejaaz: In the dot-com bubble in the 2000s, it was debt-fueled.

Ejaaz: You had people borrowing a hell of a lot of money for unproven theses and products Ejaaz: that people didn't actually care about or use. Ejaaz: Now, if you compare this to the current AI super cycle, as he describes it, Ejaaz: just from OpenAI and Anthropic alone, they're on track to reach $200 billion Ejaaz: of ARR this year, just two companies.

Ejaaz: And this isn't made up money. This is money that they've signed through contracts Ejaaz: that are already prepaid in large part, I think 40 to 60% from a bunch of enterprise Ejaaz: and retail customers that are funding this. So this is real money exchanging hands. Ejaaz: Now, if you look at the GPU computer, so let's not look at the model labs, Ejaaz: let's look at the infrastructure, the people who are buying the goods from NVIDIA.

Ejaaz: Google, Microsoft, Amazon, and Meta are all paying from their own cash reserves. Ejaaz: So they also haven't borrowed any money at all. Ejaaz: They're just spending free cash flow on this. Ejaaz: Amazon just came to the end of their free cash flow. Now, if they start borrowing Ejaaz: money, then we can start to get worried. But the point is, they are not levered up either.

Ejaaz: Also, this is like five of the top companies in the entire world who are arguably Ejaaz: like some of the smartest companies because they are where they are in terms Ejaaz: of like market cap, value and size. Ejaaz: So the fact is like back to the dotcom bubble, you had a bunch of like no-name Ejaaz: companies that had raised a ton of money that was spending money in ways that Ejaaz: didn't really make sense.

Ejaaz: In this cycle, you have like some of the smartest companies in the world spending Ejaaz: money that isn't levered at all, that isn't kind of like compressed into like Ejaaz: various different margins. Ejaaz: And all the quarterly reports that we've spoken about on previous episodes very Ejaaz: recently over the last couple of weeks have proven that profit is optimizing Ejaaz: through a bunch of these different movements that models are progressing, Ejaaz: they're getting more intelligent.

Ejaaz: So the single argument that Gavin has is, this isn't a dot com bubble, Ejaaz: because we're not levered on money, but also because the bottlenecks themselves Ejaaz: that we're speaking about is constrained by physical atoms. Ejaaz: It's one thing being like, OK, I'm going to buy a bunch of memory chips and Ejaaz: I'm going to buy a bunch of GPUs.

Ejaaz: But it's not like NVIDIA can oversell GPUs. It's not like Micron can oversell Ejaaz: AI memory chips because they just don't have the chip production facilities to be able to do that. Ejaaz: And so his simple argument is it's not a bubble if you can't oversupply the entire market. Ejaaz: We are constrained by the fact that we don't have enough picks and shovels to Ejaaz: do the thing. And that's what he's investing in.

Josh: And there's one great point. If you scroll down just a hair on this artifact, Josh: you can see the $2 to $3 trillion number. Josh: This is something that Gavin believes is a reality, that NVIDIA could sell $2 Josh: to $3 trillion of GPUs this year and next year if only TSMC could supply them. Josh: So he's saying that TSMC is actually one of the major linchpins of bubble territory. Josh: And I'll explain why for a second, because I found this really interesting.

Josh: If TSMC were able to supply the amount of demand that is required from these Josh: companies to actually provide them with that many chips, it will cost them a Josh: tremendous amount of money. Josh: And in fact, EJS, if you scroll up just a little bit more, you could see the Josh: earned income to the CapEx. Josh: There's like this kind of bar chart there. Yeah, right here, Josh: where you could see AI CapEx is not much different than the operating cash.

Josh: And so far, companies are generating enough cash to fund the build out of these things. Josh: In the case that TSMC came to NVIDIA tomorrow and said, actually, Josh: we could triple our capacity overnight. Josh: NVIDIA wouldn't say no. And they would start spending an unbelievable amount Josh: of money to buy those chips. Josh: Other companies would then have to borrow money to fund the purchase of all these chips.

Josh: And therefore, we would start to see that CapEx bubble really start to grow Josh: and separate from the operating cash of these companies. Josh: But because there are these supply constraints across the board, Josh: we have them in memory, we have them in chip making, we have them in energy, Josh: particularly as it relates to TSMC with the chips, we're not actually able to build out that fast. Josh: And therefore, TSMC is creating a blocker on the rate of acceleration of this bubble.

Josh: And so long as TSMC stays limited and constrained to the amount of chips that Josh: they could produce, and so long as companies like Samsung and other chip makers don't.

Josh: Actually overtake that market share, which seems improbable because it's going Josh: to take an incredibly long time and it's very difficult to do, Josh: then we're at a pretty sustainable rate of growth where it feels fast, Josh: but there's still this overwhelming amount of demand that can't be satiated Josh: because we just can't build it out fast enough. Josh: And so long as that dynamic stays intact, I think we're probably good for now.

Ejaaz: Well, there's also this other thing, right? Because like you could assume that Ejaaz: like demand stays static, but that also doesn't happen. Ejaaz: You have an exponentially increasing demand side for all this AI stuff, Ejaaz: which is outpacing the production supply that we have for all of these different chips. Ejaaz: So the only way that I see this thesis kind of being unproven is if somehow Ejaaz: someone miraculously recreates ASML and we suddenly have ASML competitors all around.

Ejaaz: By the way, those of you who don't know, ASML produces these $400 million machines, Ejaaz: which basically tsmc and every major chip fab Ejaaz: manufacturer needs and asml is only Ejaaz: one team in i believe norway that creates Ejaaz: these things and it takes ages and they're backlogged for like five Ejaaz: years right now or if we recreate a different type of llm that doesn't require Ejaaz: as many gpus or doesn't require as much memory but we're just simply not seeing

Ejaaz: that i saw a story break today about sk hynix which is the number one memory Ejaaz: manufacturer and supplier for nvidia gpus they are basically the top dog when it comes to AI memory. Ejaaz: And they're currently courting, I think it's like $50 billion, Ejaaz: $50 to $100 billion worth of offers from the likes of Google and Microsoft.

Ejaaz: So two companies alone, just to pay for the equipment that they need to scale Ejaaz: up future supply over the next three years to lock in supply that they're going Ejaaz: to create three years from now. Ejaaz: This is how desperate some of these big companies are for memory. Ejaaz: This is one subsector of the AI component. Ejaaz: And SK Hanox is instead just saying, no, I don't want to give you guarantees of our supply.

Ejaaz: Instead, we'll just hike up the price. They have like 70% operating margin, Ejaaz: by the way, which is just unheard of in semiconductor companies at all. Ejaaz: So it makes complete sense why Gavin is just going all in, because it doesn't look like a bubble. Ejaaz: It might seem like a bubble. The market might react to it. We opened our stocks Ejaaz: portfolio today before we started recording and everything was like down.

Ejaaz: But it's just reactionary because the directional goal of all of this is that Ejaaz: we're just going to need more GPUs. going to need more semiconductor chips and Ejaaz: we don't have enough supply we don't have enough manufacturers for this Josh: So in conclusion, watts and wafers, that's it. Those are the two brick walls. Josh: Those are the two limiting factors, the limiting constraints that are going Josh: to prevent us from accelerating too fast.

Josh: And so long as those watts and wafers stay valuable, stay in high demand and Josh: stay limited in their supply, there will be good times ahead.

Josh: Now, if you are looking for a TLDR on Gavin's portfolio, I will read out some Josh: of the largest holdings for you. Josh: That way you can just, again, not financial advice. This is what Gavin's in. Josh: This is not what we're in. Josh: I have no idea if any of these are gonna go up, down or in circles. Josh: But his largest position, ironically, is that QQQ put position. Josh: He's generally speaking bearish on the market, which I think is very noteworthy to talk about.

Josh: Second to that is Astera Labs, 7.4%. Alab is the ticker. Third is Unity, the 3D software. Josh: Then there's a whole bunch of others. Sienna, Micron, NVIDIA, Josh: Amazon, Lumentum, Alphabet, Coherent, Roblox, EchoStar, Twilio, Wayfair. Josh: Wayfair is a furniture company. This guy's in everything. There's a lot of investments. Josh: I think if you're interested, you can take a look at a 13F online.

Josh: We can link to it in the description. But that is the Gavin thesis, Josh: that the bottleneck is Watson wafers. Josh: So long as these things stay intact, we are up only. Ejaz, how are you ingesting Josh: this information and what are you doing with it? Ejaaz: So the market's been pretty rocky since the Leopold 13F. Ejaaz: And I'm starting to realize as we're recording this episode that Gavin's kind Ejaaz: of like an older, wiser Leopold.

Ejaaz: He's been around for a while. He may not have $13 billion in AUM, Ejaaz: but I have a feeling he's going to be around a decade from now. Ejaaz: And so if you're listening to this and you're like, listen, I don't want to Ejaaz: keep up to date with AI every single minute of every single hour, every single day. Ejaaz: And I want to just kind of park my money and kind of like see how it grows over Ejaaz: the next couple of months or years.

Ejaaz: Gavin's portfolio probably kind of makes a lot of sense. Again, Ejaaz: this is not investment advice, but he takes a more cautious, Ejaaz: long-term, futuristic approach to a lot of these things. and if his trends indeed Ejaaz: end up playing out like he early backed Nvidia and Cerebrus, Ejaaz: you could end up having like exponential gains over the next couple of years. Ejaaz: But again, it's all based on his one thesis, which is we are not in a bubble.

Ejaaz: I'm curious whether the listeners of this show agree with this. Ejaaz: Obviously, most people aren't as technical or in the weeds as Gavin, Ejaaz: but just generally speaking, after you've heard this episode, Ejaaz: do you think we're in a bubble? Ejaaz: Do you think we're not? What are the arguments for and against? Ejaaz: Is there anything that we particularly missed? Ejaaz: I don't know, Josh, do you think we're in a bubble as we round up?

Josh: I think we're certainly in a bubble. Where we are in that bubble is to be debated. Josh: It seems like it's in the earlier stages. Josh: So hopefully it continues to be that way. According to Gavin, Josh: so long as TSMC continues to limit their ability to produce chips, it will be fine. Josh: But that's the outlook. We have Leopold now that we've covered, Josh: whose success is measured in quarters. Josh: We have Gavin, whose success is measured in decades.

Josh: And perhaps somewhere in the middle is where a lot of people think of themselves. Josh: So if you did enjoy, please don't forget to share this with your friend. Josh: Let us know which ones you are most. If it's not a thesis, perhaps there's a Josh: ticker that we should be looking at. I think it's exciting time because everything's moving quickly. Josh: Whether it be up or down, there is a lot of movement. There's a lot of volatility. Josh: It's fun to get involved in.

Ejaaz: See you guys tomorrow. Josh: See you tomorrow.