Bitcoin's Turn Is Next — The Easy Money AI Trade Is Over? | Jordi Visser

Jordi Visser is a veteran macro investor with 30+ years of experience and the author of the VisserLabs Substack. In this conversation, we break down the AI trade — Chinese open-source models catching up, Google's massive CapEx bet, and the memory shortage bottlenecking it all. We also cover Travis Kalanick's stealth robotics empire, what AGI in three years means for jobs and the Fed, and where Bitcoin, Ethereum, and the Clarity Act go next. ====================== Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you’re rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! ====================== This episode is brought to you by TikTok for Business. If you run a company, your next wave of customers may already be on TikTok. With more than 200 million monthly active users in the U. S. and 51% unique reach, TikTok gives brands access to audiences they can't reach anywhere else. Learn how to turn that reach into growth at TikTok for Business ( https://anthonypompliano.splashthat.com/ ) ====================== Uphold is the easiest way to buy and sell crypto unlike any other platform allowing you to trade in just one step between any supported asset. Check them out at https://www.uphold.com/pomp/This video includes a paid sponsorship with Uphold. I’m compensated by Uphold for promoting its products and services and may receive commissions from referrals. Terms apply. Not available in all jurisdictions. Digital assets are risky and may result in the total loss of your capital. ====================== 0:00 - Intro0:48 - Chinese open-source AI models & the risk to portfolios12:10 - Google's massive CapEx bet & the odds it pays off16:53 - Anthropic's growth slowdown & the shift to token efficiency19:39 - The memory & compute shortage29:00 - Travis Kalanick's stealth robotics & ghost-kitchen empire40:06 - The Fed & rate policy43:23 - Bitcoin's setup & why the "easy" AI trade is over50:36 - Jordi's prompting method for AI research & upcoming video

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• 1:00Speaker 02

  Again, I'm more focused on the second half of the year and the fact that at some point here, the agentic side becomes really important for crypto. That's not going to be today's business. The AI trade's over. The ability of getting seven, eight times your money and that is over. I think the things people need to watch, and I've started to post more next on this.

• 1:20Speaker 03

  What's going on, guys? Today, we got a great conversation with Jordi Visser. In this conversation, we go deep into the rabbit hole of AI. What's going on with all the open source models? Does this actually present a risk to all of the American large language model labs? And then we also get into what's going to happen to the portfolios? What companies are going to be winners? What companies are going to be losers? Are companies like Google betting their entire company on winning the AI race? What's going on with the war in Iran, interest rates, the Fed? And of course Bitcoin and crypto, all that and much more in this week's conversation with Jordi Visser. All right, Jordi, all hell has broken loose. People are very worried about the Chinese open source models. There are people who are advocating that the White House bans them. We now have an open letter coming from Nvidia and a bunch of other companies saying, no, we should not ban them. We should encourage competition.

• 2:04Speaker 03

  What is your take as to the impact on investors' portfolio as the AI industry tries to figure out what to do with these open source, open weight models?

• 2:14Speaker 02

  It's just a, I guess the best way to put it. So this week in the video I'm going to do over the weekend, I'm going to go through just the ups and downs that are going to come with AI. We've talked about them a lot. Open source is just another one that causes conversation and it's really related to how fast this is moving. So open source was always going to be a part of the puzzle, always. And I say that with certainty because intelligence, again, will all be different. You'll be using different models. There'll be a race to lower boundary. I mean, Sachin Adella on an interview with Dwar Keshe Patel talked about the fact that AI would be commoditized.

• 2:58Speaker 02

  So you get to the point where you know this is going to happen to some degree where there's going to be open source. So I just think this is another spot where everyone, because of how fast it's moving, we migrate from Anthropic's ARR is going parabolic. What does that mean for every single company? Anthropic's going to be involved in every company and disrupting them to, hey, we don't want Anthropic to have our data. We don't want an AI to have our data. We need to have open source. We need to have AI sovereignty. This has all been headed this direction. It's not like the Chinese open source models are a new thing. I just think we've reached a point where the Chinese open source models have caught up in a very, very big way.

• 3:43Speaker 02

  And, you know, the point of what I'm trying to go through is this needs to happen for adoption to lift off. And the cheaper the models get and the more that open source drives the prices lower, the faster adoption happens and the faster we get into a world that we discussed last week, which is based on routers, where just like in a firm, you have different intelligence levels. Not every firm has all 150 IQ people because there's not that many 150 IQ people. So I think the frontier models will stay the way they are with very high cost. And what the Chinese models are going to run into, and this is the other part that isn't getting discussed, but this is the, if you put everything together,

• 4:23Speaker 02

  the major story is even for Kimi K3, which started this whole thing, you saw they have, they ran out of compute immediately and they're going to have to go IPO. So Eric Schmidt said at the end of last year, and he's repeated it this year, energy is not going to stop AI. The biggest risk to stop AI is capital and the capital is need for the compute. And now we're seeing all of this stuff lead to, hey, maybe it's not, the commoditization means adoption is going to go faster. Maybe we don't have the capital to fund all the compute that we need and the markets and bonds and everything are starting to react that way.

• 5:04Speaker 03

  What I find interesting is at the same time that the large open source or the large LLMs are complaining about the Chinese models using distillation and, you know, kind of drafting off of their innovation, they're also settling lawsuits. Anthropic just settled a $1.5 billion lawsuit where they basically had to pay out to a bunch of authors and publishers for having trained on their information. And so it does feel like in the AI world, everyone is doing the same thing, just in different flavors. But then also Bill Gurley from Benchmark, he's been tweeting the screenshot of, I think his name is Jim Farley, who's the Ford CEO,

• 5:46Speaker 03

  talking about that Ford has been buying Chinese EVs and then basically taking them apart, figuring out how they built them and then trying to improve their own EV. And so, you know, the point he's trying to make is like, dude, this is just how business works. Is everyone tries to take apart their competitor's thing and then rebuild theirs to be better, faster, cheaper, more efficient, more effective, whatever. And so is this all just like a big nothing, Bert?

• 6:12Speaker 02

  No, this is something much more complex than that and much more important and something that I'll continue to say, behind every great idea,

• 6:21Speaker 02

  well, let's start at the higher end, behind every company that is, runs into competition is some sort of intelligence that drove it there. Intelligence is behind the ideas. Intelligence is behind figuring out how to market them, how to get it out there. What has changed is time. There are no moats anymore because the one thing that prevents a moat from happening is the speed of competition. AI is arguably the most complex innovation we've ever seen. It's certainly the most important. The Chinese have been able to stay neck and neck with the US regardless of how it's done. I don't care whether it's distillation. I don't care whether it's algorithmic efficiencies. They don't have the compute and they've been able to do it.

• 7:04Speaker 02

  XAI wasn't even a company and Grok is right with it. So I just think as you go through this, you have to start to realize that if intelligence is becoming abundant and commoditized and free, how will there ever be an idea that has scarcity? How will there ever be an idea? And this is one of the reasons why, number one, you and I started doing this and the reason the name of my company or the research I do is AI Macro Nexus. We are at the point where the linear meets the exponential. And in this exponential world, what we're talking about right now is the most important thing, which is to go from intelligence and idea, a thought,

• 7:46Speaker 02

  and now have it at the snap of your finger means there is no way to run a business and not have competition come up extremely quickly. So what Anthropic and OpenAI are going through is something that no one thought could happen three months ago, which is, okay, there's now a duopoly. These guys have separated themselves. They're going to reach AGI and this is going to take off. And what has happened is we're now having a conversation that open source is neck and neck with closed. What does that mean? And I think that just means that intelligence and this whole moat theme five years from now, I don't think people have thought through what it means with AGI.

• 8:20Speaker 03

  Now, there's an interview that the, let's see, the DeepSeek CEO did. And in this interview, there was a couple of very interesting things that he talked about. But I want to read to you one of the takeaways. There's a guy on Twitter, maybe we can pull it up to show this. But he says that DeepSeek was never created to maximize profits, IPO or dominate the market. Instead, its sole mission is to achieve AGI or artificial general intelligence, which he believes will be one of the humanities' most important technological breakthroughs. Everything else, consumer products, enterprise APIs, revenue and market share, is simply a byproduct of pursuing that mission. Now, this entire interview and the analysis of the interview basically is this idea

• 9:04Speaker 03

  that you almost have a missionary in DeepSeek, which is saying, look, we actually don't want to make as much money as possible. We simply want to have the technical breakthrough to get to AGI. Whoever controls AGI, that's going to be a significant, you know, advantage in the future. And he's almost counter positioning DeepSeek to OpenAI, Anthropic, et cetera, who are doing everything from creating, you know, hardware to doing enterprise, you know, services, et cetera. Is that, like that difference of positioning or that kind of root north star going to ultimately negatively impact the large language models? Like if you have somebody who doesn't care about making money, doesn't that drive significant financial impairment for the companies that are trying to make money?

• 9:49Speaker 02

  I mean, I've written papers about the end of capitalism as we know it, and that's what you're talking about. So wait, let me just, let me just give people a little bit of details because I did a video on this this week for subscribers on what China did this week is China stepped into their stock market. I mentioned that Eric Schmidt said the only thing that can slow the AI race or end it is capital. You know, it's more important than energy. And over time, that's become more evident. Now, he specifically said that the Chinese are at a huge disadvantage because they don't have access to the global capital markets the way the US does. US has the deepest capital markets. We've talked about Google raising money, OpenAI raising money,

• 10:32Speaker 02

  SpaceX raising money, Anthropic, all the bonds being sold, everything in there. So DeepSeek has a very unique situation. Everyone knows DeepSeek because of last January. They still may not remember or know that it started out of a hedge fund. Well, that quant fund was down 16% last week. Yes, that's last week. They did an IPO or they raised capital and the only one buyer of the capital that they issued got voting rights, and that was the Chinese government. So the Chinese government is part of DeepSeek. Last week, Xi Jinping gave an interview or gave a

• 11:13Speaker 02

  speech at in Shanghai that is basically the same thing as what the DeepSeek founder said. So let's just get to the point that this is not about DeepSeek. This is not Sam Altman versus the founder of DeepSeek. This is the difference in philosophy of what China's trying to do versus what the US is. China has also talked, has also talked about possibly not allowing their best models to be out in the world. So this is all strategic. There is no doubt in my mind, based on the fact that the Chinese government has told insurance companies and asset allocators to be buying more money in stock because if people put their money into bank accounts and housing,

• 11:55Speaker 02

  that doesn't help the capital markets. They actually need the money in the stock market, and they need the stock market to be going higher. Now, that takes a lot of cash. It was said that $9 billion is what was put in this week, which happened to be the lows. They have a, an innovation index there called the Star 50, which had its biggest daily performance since the lows in the China stock market in 2024. So I think reading a little bit below this, this is still a race between China and the US. This is definitely them trying to make sure that they realize they need capital because eventually if they don't get more capital for compute, they will run into problems because the compute is not just for the intelligence,

• 12:37Speaker 02

  it's to allow people to use it, which is why Alibaba is raising money and Kimi K3 is raising money. They're all raising money. And the reason they're raising money is because this is on the same path as the US. I happen to do, I do believe, though, that the end game is they're looking forward, and so has Microsoft in a very similar way, believing that these models are going to be commoditized anyway. So we don't want to be involved in building the models and trying to go through it. So I do think there's different approaches here. In the end, I think we're headed towards abundance eventually because intelligence is basically the key to abundance.

• 13:10Speaker 03

  It feels like these companies are willing to bet the farm on being a leader in the AI sector. There's a chart that has been going viral online mainly because I tweeted it, but the chart basically shows Google's free cash flow, and they just put in the first negative free cash flow quarter. To be clear, they have a lot of cash, so they can do this for, you know, maybe a year, year and a half and not run out of money. But people look at that chart and they say, wait a second, this is obviously a very intentional strategy where they believe that there is some massive ROI, and that brings the question of, you know, will the ROI come or not?

• 13:50Speaker 03

  Is this like, if you do not make that investment, you pretty much will be left behind? Is it almost like an existential everyone's game theory is you have to basically bet the farm to try to be a leader in this?

• 14:03Speaker 02

  I definitely think that's the case. I mean, if you go through Google's numbers, the numbers are insane. Forget the earnings per share because that was skewed by their private investments. But when you go through the revenue gains on all this stuff, their cloud revenue was up over 80% year over year. The backlog of contracted orders that they have in the last year has gone from 100 billion to 514 billion. So they have the revenue sitting there. They just can't monetize them yet. And the reason they can't monetize them yet is because the data centers aren't built yet. So I go through all of these details and just kind of say that whenever

• 14:43Speaker 02

  you see these charts of free cash flow, you said something important. Number one, they have massive cash still. They just raised 80 billion in equity. They're issuing bonds, so they have access to the capital market, so they can continue to go out. Yes, rates are moving higher, but this doesn't change the fact that something you said is important. These companies, to keep the business they have, they have to get AI to be a revenue-producing part of their business. And it's not easy to do, other than the fact that they have a massive business in advertising right now. Well, I think they're believing, which I think most people are, that at some

• 15:27Speaker 02

  point, advertising will not be a great business, but they still have YouTube. And YouTube is competing with Netflix, but they have AI. And all of these things get wrapped into the same thing, that when you tear apart Google's business to Waymo and to all of these different components, all of those businesses to some degree are built on code. And with intelligence, the only thing that you really have is the distribution, you have the brand name, you have all these things. But as we've seen with other businesses, it can come under attack very, very quickly if there's something cheaper or something better or new that's happened. And I think that they're going to have to spend just like all the other companies. So anyone who's worried about the capex

• 16:06Speaker 02

  side, Google has basically a problem right now. If they didn't spend the capex, they're not going to get the 400 or the 514 billion in revenues. 514 billion. I mean, we're talking, they have contracts bigger than, than, you know, 90% of the S and P 500 companies in terms of their market cap. So you're, you're, you're at a point where they don't really have a choice. And so I think the capex is going to continue. And we'll probably have some companies that do run into problem. The bond market is making it more difficult for certain companies to raise money like OpenAI and Anthropic, because these are the hyperscalers with the best balance sheets. It will be harder for other companies that don't have the same balance sheet.

• 16:49Speaker 03

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• 17:34Speaker 03

  automation that works across every major asset class. There's no more emotional trading, no more missing tax opportunities, just smarter, hands-free execution of your preferred strategies. Go to archpublic.com right now. Connect with their team, set up a time, bring your accountant, if you'd like, and then you can learn what automated trading can do for you. Archpublic.com. I saw a chart that shows Anthropic's revenue growth is slowing. So it's still growing, but, you know, obviously, the growth rate is very hard to keep, keep that pace. And I think that the Anthropic revenue growth slowing is happening at the same time that you get Meta, you get Grok coming into the market and specifically positioning themselves with a lower cost, you

• 18:17Speaker 03

  know, per token or more efficient type model. At the same time, we see that Stripe is thinking about buying OpenRouter. Ramp just announced a model router. Us with Silvio, we've created our own model router internally to try to keep costs under control and increase performance. It just feels like there's been this shift from like, who cares how much this costs, to now all of a sudden, it's all about efficiency and total cost per task or kind of per outcome. Could we see Anthropic's growth rate plateau? And some of this is the DeepSeek and Chinese open source model, some is the model router, et cetera. But like, could OpenAI and Anthropic be in, be in a little bit of trouble here?

• 18:56Speaker 02

  No, but I think it was foolish, and I know I said this last week, but I think it was foolish for people to extrapolate, you know, Anthropic's growth rate, that it wouldn't reach a point. I think plateau is taking it too far. I think the growth rate slowing is happening. I still believe that one of the best uses and the highest margins available for this is the ability of giving this for solving some of the world's biggest problems. And I think that's what

• 19:26Speaker 02

  DeepSeek, not DeepSeek, Google DeepMind and also Anthropic and even OpenAI to some degree, they're focused a lot on research and on the bigger picture for things where they probably can get more money for curing diseases and focusing on that part. But we're also at the stage where it would be foolish to not take into account Jevon's paradox and just realize that as compute gets cheaper, it means more companies go from token maxing to token efficiency. You're describing token efficiency. So we went through token maxing, which I would just say to people, having someone that's used AI all the time, you're trying to figure out how to incorporate it into your business, how to get it into your

• 20:08Speaker 02

  workflows. You're going to max out on it. The router part is going to make it easier once you, you know, now that you're through the first phase. So Anthropic is going to grow because we're at the early stage of enterprise agents. We still have consumer agents to come. That'll be less focused for them and probably more focused for OpenAI if they can get the hardware side out. But I will say that for Anthropic, I wouldn't bet against the fact that they're going to continue to grow their revenues. I just think this concept of growing at the pace they were is over. So.

• 20:40Speaker 03

  Now, we've also seen, I think, a lot of talk, what I'll consider in a generalized way, Wall Street is very focused on memory as a huge shortage, compute, chips, you know, all of these things that we've been talking about, I don't know, six months, 12 months now. And most of that conversation is, what are the publicly available companies that I can go and I can invest in? So whether it's SK or Micron or whatever, that's really been most of the public market conversation. At the same time, venture capitalists, they don't invest in the public market. They've been funding, you know, brand new competitors to the market. And so we've seen companies like Etched and a couple of others show up and say, hey, I have kind of a better mousetrap. I've got the ability to, whether it's compute,

• 21:21Speaker 03

  memory, et cetera, do this in a better way. What I found interesting is Etched, as one example, just announced a brand new fundraising round, and they had the usual players, I think Sequoia and Andreessen Horowitz, et cetera, but SK actually invested as well. And so you're starting to see this kind of cross pollination where the major companies, whether it's the Nvidia's, the SK's, et cetera, they also are helping to fund competitors or potential partners or potential acquisition targets of the future, where it's almost like they're outsourcing their innovation and they understand to solve this bottleneck, maybe they can do it internally, but there's also going to have to be more competition on the playing field.

• 22:02Speaker 02

  Yeah, you've got a big problem with competition catching up. It's one thing to come up with an idea. Again, I'm going to say it over and over again. We got caught in this world where software, you could compete. Physical hardware is different. So let's assume a new company comes out and says, we've developed a better chip that will do XYZ. Well, that's great. Now all you got to do is get the scale. Who's going to make it at the size that you need to supply the demand that's way too big? So, you know, I spent a lot of time creating the logo for my, for my company. And when I was working with, with Fable 5 on this and kind of going through it, I just kept saying, I want you

• 22:46Speaker 02

  to think Nexus, I want you to think the world is changing. And so the logo that came up was a V where the left side is a linear line and the right side is a parabolic line or an exponential line. And that's what fits into this. I think every time we run into a situation right now, it's a hardware problem. And until we get out of that, the hyperscalers had a bad week this week. There was nothing wrong with Google's numbers, but I think at this point, the spenders keep coming under attack, even if they get a rally for a short amount of time. No one can get past the point. And I think it's justifiable because you and I talked about this concept of three years from now, we don't know what terminal value is. One thing I know is if you're spending lots of money, you're taking risk. So I went

• 23:31Speaker 02

  through Fable 5 and basically said, okay, let's go through Google's earnings reports. You're an expert forensic accountant with experience as a CFO at a variety of big tech enterprise companies. Based on Google spending money, the backlog, every single detail, what's the probability of this working out for them? The answer wasn't 100%. The answer was legitimately 75%. And when I went through the 25 to 30% debt outcome that wasn't good, these are all things people know. So I bring this up just because the problem for software companies, the competition's coming and the more that intelligence moves forward and

• 24:13Speaker 02

  the capabilities, the worse it gets for all these companies. If you're spending lots of money, you're running into the physical hardware side. If Google had all of these data centers already built, they'd have $514 billion from Google Cloud and they would have a dominant market share. And while that would be great, instead they're having to rent stuff from other people. So whenever you hear these stories, people, and oh, we're going to catch up, you just have to ask yourself a question and put it into the best model and say, is this a physical problem and will they have the scale to bring this out quickly? Or is this an algorithmic coding thing that can easily be rolled out to everything with the existing chips? And the reality is, almost every single time, it's a hardware issue.

• 24:53Speaker 02

  And the hardware issue is not solved easy. And I just, I've been using an analogy now with, with groups that have asked me the question about why memory is such a big problem. Do you remember the movie First Dates with Adam Sandler?

• 25:10Speaker 03

  Yes.

• 25:11Speaker 02

  Where she couldn't remember anything at, okay.

• 25:14Speaker 03

  Amnesia.

• 25:15Speaker 02

  Daily amnesia, where every day she forgot what happened the prior day. Well, that's basically like a context window. And the problem is, to get agents to remember everything, it's an enormous amount of memory. And the reason we haven't solved this is because this is a far more complex problem than just going into a context window and then going back theoretically to that day and having the same conversation, knowing the context is in there. This is an incredibly huge amount of compute and incredibly huge amount of memory that needs to come through. And the problem is, we know how to make the memory, we just can't make it fast enough. And that's why prices are going higher and that's why GPU availability continues to go down. We still have a compute shortage and it's going to remain for a long time.

• 26:00Speaker 03

  I'll take it one step further. There's absolutely the memory and the compute shortage, et cetera. I also, and not because I knew to do this, but the engineering team at Sylvia, they actually built an entirely proprietary agentic file system, specifically focused on spinning up a specific file system for each individual user that helps to increase memory, reduce latency, you know, solve all this stuff. And so what it feels like is there's almost like a sandwich. You have the hardware or like the bottlenecks of memory, compute, et cetera. But then also you can't just use like traditional databases. The whole agentic, you know, memory or agentic file systems are going to be rebuilt and you're going to start to get different architecture. You're going to start to, you know, have

• 26:45Speaker 03

  to take a lot of different information and be able to put it into these file systems, be able to recall it in, you know, very specific ways, have the agents be able to coordinate between each other. Like, it is a software problem as much as it is a hardware. The nice thing about the software is if you throw enough people at it, like you can figure it out. You can't do that with the hardware, which I think is kind of your point, is the physical world just has these limitations that it kind of doesn't matter how much money you have or how smart your people are. There's just no way to solve that piece of the stack.

• 27:16Speaker 02

  Yeah. And I don't see how that's solved until we get to AGI. I think we need solutions that are so far above the things that people are doing. And as a really smart person who's in the tech side from the hedge fund world said to me, the smartest people in the world are working at all of these big companies by now, and they're trying to solve the same problem. Because if they can solve it, then they, their margins go up dramatically because then they don't have to go pay for, like, there's just no way to get through this problem. So they can make the chips. So they're all getting into the chip business. But the memory business, and this is why memory is really, AI equals memory is a paper that I wrote recently. And at the end of the day, you have to watch those stocks because until those stocks are bottoming and rally, and we did see, you know, I mentioned that I bought

• 27:59Speaker 02

  Micron last week, it did see a rally this week, but it's not going right back up to the highs. I don't expect the AI worries to end anytime soon because all the things we've talked about in here. They're all viewed in a negative lens because there's so much uncertainty and I think that's what AI does to everything. I highly recommend if people get the chance, Imad Mostak, have you had him on before?

• 28:21Speaker 03

  Uh, no, I've talked to him, but I don't think he's ever been on a podcast.

• 28:25Speaker 02

  He's, he's a good interview for you to have on. I mean, Imad, the reason I like him so much is because he was in the hedge fund world. He understands economics and he wrote a book recently titled The Last Economy. And it basically, again, is kind of the same as AI Macro Nexus. It's like, it's the last economy. So the end of capitalism for me, the heading into a world of abundance. He and I are mostly on the same page with everything. Um, I, I, I think this is a really important thing for people to start to put into their head now. I think two years ago, when I talked about it, I didn't tell people or suggest to people they should read this type of stuff. But we're only three years away from AGI and this is becoming a

• 29:07Speaker 02

  centralized number that everyone is coming up with. And because of the open source catching up and because of humanoids and the rise that seems to be happening at the exact same time, and you've got these bigger players getting involved in actuators and all of these things, I think it's getting closer and closer to this world that people just haven't thought too much about. It has huge implications for your portfolio, but also I think it has huge implications for crypto. And when you go back to that first dates analogy I gave, where I used it, Sandy Call wrote a great paper. I don't know if you've, you've had Sandy on, Sandy was at Citibank. Okay, she, she's awesome. She was really one of the original people in digital assets that got me focused on this. But this whole thing of the agentic AI economy that I've talked about, she wrote a paper this week that people

• 29:52Speaker 02

  should read as well, which I'll highlight on the video. But I think we're at that stage now where you have to start thinking how the world is going to look different by the time we get to 2030.

• 30:01Speaker 03

  I want to talk about the ward crypto, but before we do that, one other aspect of this like AI industry is Travis Kalanick, who was the founder of Uber. Um, he has been building a company for the last eight or nine years in stealth. Um, and he kind of came back. He did the Michael Jordan, you know, I'm back and, and put the world on notice. Now, the company, I think is like a 15 or $20 billion business. So he, he's been working very hard. And my understanding of what he had been building previously was pretty much focused on cloud kitchens. That was kind of the US consumer business. And the only thing I knew was that the actual legal entity was called City Storage Systems, which is kind of a weird, you know, name. Well, it turns out that he now is reporting

• 30:46Speaker 03

  that they have hundreds of facilities in 30 plus countries around the world. They've, you know, expanded this thing substantially when it comes to food. And my understanding of the business was basically it's a ghost kitchen. It's a, you know, a dark kitchen. They basically have the WeWork model, but for kitchens and that was it. I heard him talk with Ben Horowitz and Eric Thornberg from A16Z, who is his big backer in this round. And he opened my eyes to the merging of AI and the physical world in a way that no one else has. And I'm going to tell you what he said and I'd love for you to react to it. He basically talked about the idea that he has recognized the physical world

• 31:28Speaker 03

  operates the exact same way that computing and networking works. And so he talked about the kitchen is manufacturing. He talked about like, uh, the IP packets or TCP IP and how all of the logistics and the movement of information and the movement of the food and all this stuff, right? So he has this kind of like mental framework of if you take a computer network that you would learn in my computer science class and you overlay it onto the physical world, it's very similar. And so he's basically been eating at this stack. And so one of the things he talked about in the kitchen is, um, it started out as a real estate play, but then they realized, well, if we want more restaurants, we have to make sure the restaurants don't go out of business. So how do we do that? Well, we

• 32:11Speaker 03

  got to bring them customers. Well, could we also help them on their cost? Let's use robotics. And he just kept eating into all of their problems and trying to make sure that he could get them more orders, keep them in business, drive this, you know, huge group.

• 32:25Speaker 03

  I say all of that because the business that he unveiled is basically that same concept. He has it in food. He's now doing it in the mining industry. He's got an entire kind of like autonomous, you know, mining facility or vehicles, et cetera. And it sounds like his business is he essentially wants to digitize the physical world. And all he kept talking about was AI robotics and automating this stuff. And, you know, when you hear this, it, it kind of feels like the Silicon Valley pie in the sky. Like, hey, this sounds, you know, awesome, whatever. It's cool. But when he talks about the concrete impact, for example, with the food, he would like to make it cheaper for you to order food than to go to the grocery

• 33:09Speaker 03

  store. And his point is if I can make a better meal that is healthier and cheaper, of course you're going to go and do that. The challenge is how do you do it? How do you do logistics network, et cetera? And so we spend so much time talking about software, but when I hear something like this, I start to say, hey, this may actually be the thing that impacts so many people's everyday lives way before some chatbot or, you know, some other kind of software AI product that they may or may not download, right?

• 33:42Speaker 02

  Yeah. So there, let's start at the beginning. Um, so I'm very big on, on talking about the importance of being a systems thinker right now. And what you just described is Travis kind of looking at a problem and then breaking down each of the vertical pieces that roll up to one and trying to solve each piece with the end goal being very simple, which is how do I reduce the overall cost for people, get them to be ability to, to get food? And let's just use the restaurant example, which is cheaper than what they can do in their daily lives where they don't have to go buy it. They don't, we're going to save them the time on it. So right off the bat, that sounds a lot like how Amazon has disrupted the, the retail world. Um, let's take out the driving. Let's take out

• 34:25Speaker 02

  the gas. Let's take out, it'll just get to you and it, and with drones, which is the next layer for Amazon. Think about what Amazon has done for each parts of the system of getting that there. So it starts as a book place, but then it eventually gets into everything. And now it's unbelievable how many things show up. And anyone who's lived in an apartment complex in Manhattan, and you just go to the package room and you see how many packages are coming in every day and how it's nonstop multiple times a day, you realize how this could work. So that's the first thing is the systems thinking. The second thing is this is the beginning of what I called the end of capitalism. When you start breaking down every component of cost to try and get it down, especially with something like

• 35:09Speaker 02

  food, which is something we all need to have, you're now getting to the point of people looking at abundance. How can I use intelligence to replace the cost? But it's the merging of humanoids and robots, anything intelligence wise with humans. So this is all based on the fact of how do I reduce the cost of making the product, make it, I mean, again, if it's made, and the easiest visual for people on this is to look at Chipotle, because that's kind of what he's doing is saying, okay, how do I create this where it's like Chipotle? And Chipotle did the first version of this. How do people get through this really quickly? They can see all the choices. They can pick the stuff as they kind of go through. Subway did the same thing. All of these different stores with this, this concept. I just think

• 35:53Speaker 02

  that the merging of the intelligence, the physical humanoids, which is the part you're bringing in, use Amazon for just kind of a, an early description of how that'll look like. But now you're getting into something related to food and less about something related to discretionary purchases and more, can you satisfy this for me and get it to me in a way that's very simple to do? I just think this is the world we're headed towards, but I think this is a merging of the physical world that, uh, let's break AI into two parts. Embodied AI, the intelligence part, the software part, and then merging that physical, that into a physical world and then combining it with the way human beings go today, with

• 36:35Speaker 02

  the end goal eventually being abundance 15 years from now, 20 years from now, whatever the case is, we will hit that point in my mind and capitalism and the way that you invest in companies will be disrupted. So think about how many businesses that would not only disrupt, but then how many businesses could be a startup to compete with other places, like you mentioned mining and all of that. It starts to get very scary that any business has no moat now and can't grow anymore.

• 37:00Speaker 03

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  If you want one app for your entire digital asset life, check out Uphold today. Go to uphold.com to learn more. Uphold.com. Go check them out today. It's fascinating, because on one hand, you're like, look what Uber has done in terms of the taxi industry, or, you know, private cars, whatever. On the other hand, they basically turned every single individual driver into a small business owner. So there's kind of, you know, creative destruction, and then obviously, there's the creation component. Restaurants, very similar, right? You hear robotics, and you start saying, oh, my God, this is bad. But I think their argument would be, well, we're helping these restaurants not go out of business. We're actually keeping them in business, and we're helping them grow orders, and we're

• 39:50Speaker 03

  helping them be more efficient, and we're driving down the cost. It's very, like, deflationary for the end consumer. And so it does feel like the robotics component. The other thing that he talked about, that I thought was pretty interesting, is he talked quite a bit about, everyone has almost over-rotated on humanoid robots. And his point is, he was watching the Chinese, kind of, robotics, like, marathon. Remember when they had the humanoids running the marathon? And he said, all he kept thinking about, why don't we put wheels on them? Right? He was like, like, why are we trying to use the humanoid form factor for something where obviously putting wheels would be such a better use case? And so he is very into, like, specialized robotics over humanoids. He doesn't think humanoids are not going to be valuable.

• 40:35Speaker 03

  He's like, there's a time and a place for them to be able to do that. But I think he actually looks at it as, like, humans are really bad at doing specialized work. We're very good at doing general-purpose, low-volume work. But if you need specialized, high-volume work, then you want a specialized robot. And I think you and I have, you know, at least beat around this in the past when we talked about robotics of, there may be this explosion, it just may not be what people think it is.

• 40:59Speaker 02

  Yeah, I agree. Again, we're talking about something that most people haven't put into their minds. And so it can go a bunch of ways. I'll just give people, again, two things to think about with regards to their portfolios and what is happening now. So we're going to get the Fed this week, and the Fed has to make a decision on rates. Last week, it had gone down to about 15% chance of a rate hike in July after the CPI and PPI numbers came in. Well, oil goes higher, you see the long-end yields moving higher, and all of a sudden, as we go into next week, we're at 35%. Now, Warsh has said he doesn't want to have public guidance, or forward guidance anymore.

• 41:41Speaker 02

  So every single Fed day is going to be like this, unless, you know, something is structurally changing, which I'm not really sure it's going to be. The inflation side is not built in. So I bring this up because he's talked about the fact that we have to change the way the Fed thinks about raising rates or doing monetary policy, because it can't be based on the last month's CPI. It has to have a forward-looking side, the same way the stock market moves. Meaning, we discount a multiple, like we're doing with Google, it's down to below 20 PE. And the reason is because we don't know if they're going to make it or not. And it's one of the biggest companies in the world. So with robotics, you have to think about the fact that three years from now, we could

• 42:24Speaker 02

  have an incredible deflationary pressure, and shouldn't the Fed be thinking about that rather than the other side? The second part is, and again, this gets into it, once we start talking about robotics in a real way, it's still early. Every business is up for risk now, because a startup can come in, and they don't need the human labor. So right now, to find electricians and plumbers, impossible. To be able, all of these physical jobs, it's really, really hard. That's going to change in the future. And I do want to end on one point here, because now everyone is swinging the other direction on the labor side, which to me is insane. AI is having an impact on the jobs market.

• 43:09Speaker 02

  It's not destroying jobs, which I didn't think it would. But last month, we had a massive fall again in labor participation rate. So the labor force participation rate has been going down since about 2000, and it's just going lower. Some of this is demographics, but it's demographics plus the household net worth in the country. And the household net worth in the country is being driven by people owning effectively profit margins. They're all along profit margins, because they're along the stock market. And if the stock market's going higher, they're making money, and it allows them to retire earlier or not look for a job the way they would have. So I bring that up, because part of this thing, when you connect everything, no one's losing their jobs overnight, because this humanoid story is going to take time.

• 43:52Speaker 02

  But what will happen is, the pressure on all of these, the forward-looking side, the way that the market deals with things, the reason that the inflation swaps market hasn't budged, guys, as oil's gone back up to the highs. We haven't done that at all, and it's because we're starting to look through all of this and start looking out two to three years. That is why the multiple in the market is compressing, in my opinion, and that is why you have about two to three years to really start to make sure your portfolio is shaped more for the future of robotics, and less about the capitalist world that's ending.

• 44:25Speaker 03

  Let's talk about Bitcoin and crypto. Bitcoin has had a little bit of strength this week, but I don't think that anyone is, is kind of cheering. It's still down, you know, almost 50% from its all-time high. Do you have any different views or anything that happened this week that really caught your attention?

• 44:42Speaker 02

  No, I think, I think it's held in well. I mean, as of when we did this, it was unchanged for the week. I think there is a tremendous now amount of hope that's being built into the Clarity Act being passed, even though the probabilities in polymarketing and Kausi is still below 50%. If it did pass, it'll be interesting to see, see the reaction, not only day one, but, but two weeks out. Again, I'm more focused on the second half of the year, and the fact that at some point here, the agentic side becomes really important for, for crypto. That's not going to be today's business. I do think the AI, you know, what we talked about, Anthropic, the AI trade's over, like,

• 45:27Speaker 02

  and let me re, you know, as someone who basically has subscribers that pay attention to AI, it's not that AI is over, it's that the easy money of it is done. The ability of getting seven, eight times your money in that is over. Now you get into the grind of, oh, my gosh, 30% a year is horrible. No, 30% a year in the AI infrastructure trade's going to be great, which is why I got interested in Micron again. I'm still got a very small position in Micron, because I still think there's a chance there could be another leg lower in this panic side. I don't think it'll stay down there very long, so I want to be ready to put money in. Same thing I did with Bitcoin when it's been trading down here. I think it's going to go higher. I think the things people need to watch, and I've started to post more next on this, and the subscribers who are interested, I will start a YouTube channel on it.

• 46:12Speaker 02

  I've been posting more and more the ecosystem index that I created of crypto. It took out the, you know, the mid-June highs. Bitcoin did not take out the mid-June highs. Ethereum's been outperforming Bitcoin. All these things are suggesting that the market is starting to look more towards the revenue side of the equation, which would be more towards Ethereum and less towards Bitcoin. And that's a positive thing in the long run, and I think we're much closer to this look again. Doge, which was something I never thought I'd talk about, but I'm very interested in getting retail back into crypto. And until I see Doge break above, it's been below the 20-day moving average for the longest

• 46:53Speaker 02

  time in its history, until we break above it, and we've run into it multiple times over the course of the last three months. Until we break above it, I don't think retail is participating in this, and I think this is people just trying to stick their nose in a bear market trend, hoping that it'll go higher. I think it's coming soon, but Clarity Act needs to happen. If we don't get passed on that, then we're going to go right back down towards the lows, and we'll have to go through this bottoming process again.

• 47:17Speaker 03

  To me, the Clarity Act is so performative. And I know that some people will not like hearing that. But I said to a friend earlier, Bitcoin doesn't need the Clarity Act because Bitcoin already has clarity. It is kind of everything else. And it really is like the industry and the incumbents fighting it out, trying to figure out, you know, who gets to do what, who has a regulatory advantage, who has to get certain licensing. Like, it's all the edge case stuff. But the assets themselves are going to continue to do what they do. The reason I bring that up is I think that there was a lot of excitement around tokenization.

• 47:58Speaker 03

  If you look at, you know, secure ties went public, obviously, stable coins have been very popular. But you don't really see the retail demand for a lot of that stuff. It's not like, you know, the retail investors on X, maybe just like a sentiment check. I don't see them talking about buying Circle stock or securety stock or some of these things that are more traditional finance infrastructure that is coming from the crypto industry. And so, just like you maybe look at Dogecoin as an interest, I do wonder, at some point, will there be that like froth of retail interest in all of these, what is really kind of more boring aspects of crypto? But if you go and you talk to the traditional folks, they're like,

• 48:40Speaker 03

  tokenization is going to be a huge thing, stable coins are going to be a huge thing, right? It's just like a mismatch between what Wall Street is excited about and what like the crypto retail folks are excited about.

• 48:51Speaker 02

  Well, let's make this all AI related now in terms of crypto. Honestly, you know, whenever you listen to someone say, how are we going to regulate AI? You can't regulate intelligence, like this is ridiculous. So the problem is, a year ago, it was very hard for me to say the network effects of crypto and not have someone roll their eyes and be like, I don't even know what that means. I will tell you right now, every single person on the hedge fund world understands what it means now. No question about it. It's not working yet, and I've seen this too many times. Investing and trading is about making money. Nobody wants to buy an asset that has no enthusiasm, no interest.

• 49:34Speaker 02

  Trust me, I remember Micron the first quarter of last year. So Japan put through major, major regulation last week on an acceptance of crypto and specifically of Bitcoin. South Korea, same exact thing. Russia, this week. The reason I think this is important is there is a race now to the acceptance that, okay, Bitcoin is not a global currency, it's not replacing the dollar. What is replacing SWIFT is stable coins. Like, you can't get away from it now, everyone's adopting it. So this is where I think your comment about this is performative. I actually completely agree. I just want the Clarity Act out of the way. If it gets done, I think it's a big positive.

• 50:19Speaker 02

  I mean, when you have the CEO of Goldman Sachs publicly come out and say, let's just get the Clarity Act through now, you're starting to reach a completely different time where they get tokenization is happening. There's no way to get away from it. I presented the New York Stock Exchange on it, it's happening. There's no way to get around stablecoin adoption. There's no way to get around the fact that the move that Stripe tried to do with PayPal, it's a big merging of the two worlds. PayPal is an old, boring company, the way you described kind of, you know, the way maybe people perceive at this point, some of the public companies that are out there. But why did they do that? Because Stripe has the merchants and PayPal has the consumers.

• 51:00Speaker 02

  Like, you have to understand, we're getting to a world where we are merging these two worlds of the past and the future. And it's happening at a very, very fast pace. So I think crypto will be looked at as connected to AI every single day. And the US has had the ability to sanction people, it's had SWIFT. Everyone's going to want their hands on the new financial guardrails. This is a very, very important thing from a government perspective and also from an investor perspective. People have to be over crypto. It's way past the time of you not doing your homework and worrying about whether Clarity gets through. I agree with you. I think this is something very important for people to be spending their time on because of AI.

• 51:37Speaker 03

  Where do you want to send people? Send people to the YouTube tomorrow?

• 51:42Speaker 02

  Yeah, they should go to the YouTube for Sunday morning at 8:30. And they should go see what's going on. And if they want to go visit the website and read some of the papers. Oh, I have a new prompt. You'll like this one too. I'll give you a little description. So I spend a lot of time thinking about how to use AI in this mixture of experts type approach. So I've done it with my investing side, meaning I'll use all five of the models. And each five of the models, I'll give them a different expertise and have them do deep research on the exact same topic. So if I say, I want you to do a deep research on the companies that will benefit from Vera Rubin. I want you, you're an expert in financial accounting. I could do another one that's an expert in hardware and semiconductors.

• 52:26Speaker 02

  I could do another one that's an expert in thinking about the way things look in the future on the power side. And you have them all come out and then they come back with their answers. Well, I started doing the same thing. I used to go to conferences. And at a conference, I might see five people speak on the same topic. But because they were spread out over, you know, maybe a three-day period, it's very hard to get the nuances and remember to connect dots on all of these. The brain does not process information like that. It processes things one at a time. And that's why, like, you can't listen to music and read a book and be able to sit there and consume both of them at the same time. Your brain's picking one. So what I did is I created a prompt called the Mosaic prompt,

• 53:11Speaker 02

  which I upload three separate transcripts, which I did this week with Moonshots. I did it with the All In Pod and I did it with the Steve Ho interview on Forward Guidance. And I created a mosaic of the answers. It came out really cool. I'm putting that up on the subscriber site and people can see it at ai.22vresearch.com. But it's a new way to go through it. And for you fantasy football fans that are ready, get to do your draft, this is actually a great way to take five separate experts, upload their podcasts and find the places where they connect on the same thing. It's kind of a crowdsourcing feature. So you're getting the mosaic and a bigger picture. But what it really allows the AI to do is to be the conductor of the experts

• 53:53Speaker 02

  and do more future forecasting like a super forecaster would.

• 53:57Speaker 03

  Well, you know, if you start solving people's fantasy football problems, you'll be very popular, Jordy.

• 54:04Speaker 02

  As someone who doesn't have the time to do fantasy football, because I don't half-ass anything, I decided about five years ago, I couldn't keep up with the people that were doing it because it was way too time consuming. So now my job is to help my son and other people who are still obsessed with this stuff.

• 54:21Speaker 03

  I love it, I love it. All right, well, I appreciate the time today. As always, I had learned something and I hope other people did as well. And we'll do it again next week.

• 54:29Speaker 02

  See you, bud.