B (2:25)

I am calling this. This is just a name that I just thought up, like, 30 seconds ago. The Infinity Gauntlet of capitalism.

A (2:32)

Okay, that's got a good name. That sounds like a movie to me.

B (2:35)

I like it. Okay, so the idea here is that we are on the cusp of there being some of, like, the last companies that will ever exist. And what I mean by that is that some of. There are some companies out there. We're going to talk about them. I want to talk about them with you. That they are just racing towards this outcome where they just become, like, so incredibly entrenched in the world. They, like, stitch themselves into the very foundations of society in a way that's just like, so hard to get uprooted or displaced, you know, like, one example I want to talk to you about is Google. You can't do anything on the Internet without Google, like, pocketing a few pennies here and there. Like Gmail. They have their AI bottle, like Google Ads, like almost anything on the Internet, like Google pockets a few pennies. Stuff, stuff like that. And there are these four puzzle pieces out there, like. Like the Infinity Gauntlet, you know, the four jewels, you know, the Infinity Gauntlet had five in. My Infinity Gauntlet of capitalism only has four, but there's four puzzle pieces that I think companies are racing towards acquiring all four of them. Some of them have more than others. We're going to talk about who's got what. But if you. If one company gets all four, they, like, win capitalism. Like, they just win the game. The world is the monopoly board, and they have, you know, they have hotels on every single space. And here are the four jewels. Intelligence, energy, capital, and labor. These are like the four fundamental things. The logical conclusion that some companies, some companies have. Some of these are, like, pretty close in getting to them. Others are very far behind. But, like, my idea here is that if you get all four of these, you are the company that basically can do whatever it wants. I'll pause there and let you reflect.

A (4:27)

Well, in a way, if you capture all four, then the number gets reduced down to three because you won't need capital anymore because it will be so abundant. You'll just have complete and total control of the resources that matter to generate infinite amounts of capital. That makes a lot of sense. It's. There are these four pillars. It is like a game of civilization, like Monopoly in real life, where everyone has this set of resources and the race is to deploy the most effectively to get to this end state. Because now we have transformers, we have AI, we have abundant intelligence. It's a matter of where you can most effectively apply that to see those capital returns happen.

B (5:00)

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A (6:31)

About once a month.

B (6:32)

And the Defi Report is giving Bankless listeners one free month of access to the Defi Report. So if you're looking for some sharp data driven analysis to make better informed decisions around your portfol, you can learn why and how Michael called the top and what he's doing next all in the Defi Report Pro. Check it out. There is a link in the show notes so I I totally agree with you. CA like Capital is a resource that you can use to get the other resources. But that's actually true for all of them because if you have energy, you can like, energy is the common denominator. Like one, one person we've had on the podcast plenty of times before is Arthur Hayes. On the podcast, he frequently says, I denominate in hydrocarbons. And something that you taught me is that if you have intelligence AI LLMs, you can actually just pump energy through an LLM and get more intelligence. And so there's a feedback loop with all of these things. So like, the more capital that you have, you can buy more, you can buy more energy. You can pump that energy through an LLM and get more intelligence. And then we'll also talk about labor. So all of these things have like a feedback loop. And there's a few companies out there that are hurdling towards all of them. I want to talk about them. I first want to talk about each individual jewel, each individual puzzle piece. Let's start with intelligence. There's this like metaphor of like crossing the event horizon. Right. Where like this event horizon is a thing that once you, once you get there, you kind of don't really come back. And we are in the humanity is working on AI, we are working on growing intelligence. These LLMs are getting so much more sophisticated now. People are worried or thinking about that, like our LLMs are going to start feeding back in on itself and we're going to point the LLM at itself in order to improve itself. This is what Dario from Anthropic has talked about. This is what that AI 2027 paper talked about. And so this is like the, the intelligence puzzle piece. In the pre event horizon era. Intelligence is humans. You know, like companies are built above humans. You have managers, you have engineers, you have analysts. Intelligence is expensive. You have to pay it a lot. It's, it's slow, it's scarce, it makes errors. And like the organizational size of a company is just fundamentally capped by human cognition and just humans, humans just aren't great. We're, we have intelligence, but now there's this thing out there that commoditizes intelligence. And we, we didn't, we did an episode the last time you were on Bankless. It was about the post intelligence explosion. So I want, I want you to help me illustrate this point of, just like in the near term, intelligence is just going to become such a commodity and there are companies out there that are doing that, that are working towards that puzzle piece.

A (9:16)

Yeah. And why is this possible now in like now, now in 2026, when it hasn't been possible previously to this. And the answer to that is the transformer. The transformer allows you to put energy in one side and like you mentioned, you get intelligence out the other. And it's proven so far to scale with the scaling laws where the more energy, the more GPUs, the more compute you could push into this transformer architecture, the greater the intelligence that comes out on the other side. And what we're seeing today is there are AI labs across the board, across all different shapes and sizes, who are training on the same architecture, trying to solve the same problem, just in slightly different ways. You'll notice Anthropic is trying to be a little spiky towards coding and math, and maybe Gemini is more catered towards real world physics. And what's happening is while they're all competing for the same prize, they're doing it in separate ways that are kind of commoditizing each one of these pillars separately and competing to bring those costs down as fast as possible to allow kind of abundant intelligence everywhere. And what abundant intelligence looks like is real world applications across the board. Previously intelligence is really just constrained to, to humans and textbooks and very laborious knowledge, but now it's available through the natural language of English. You just say words to your computer, you type things into your computer, it's very intuitive. So now not only are there more people capable of using these tools to gain leverage, but the people who are not natively inclined to do things like write code or program or optimize their business can just ask the questions to an AI and defer to that. So the single individual because of this, because the costs get lower, because intelligence is abundant and gained so much leverage in this new world that there, there's just so many more things that they are capable of, but also downstream of that, that entire companies are capable of because everyone is so levered up with this new form of intelligence.

B (11:00)

Yeah, something that I know that Google is doing is like Google is trying to apply AI and intelligence to allow other companies, firms to have a literal like Central Intelligence Agency over its own company. Because like one of the largest frictions in a company is like, especially as at scale, when like your company scales beyond like a hundred people or even honestly before that. And then you, you even get into some of the super scaled companies that have tens of thousands of employees, there's not a single person that knows what's going on. Like that's what the CEO is paid for, paid to do is like know everything about the company. That's how. Who's the. Who's the. Is it the CEO of Google right now? What's his name?

A (11:45)

Right now? It is. Oh, my God.

B (11:48)

He goes. He goes on all the podcasts.

A (11:50)

Wait, Sundar. It's Sundar, right?

B (11:52)

Sundar. Yes.

A (11:53)

Sundar Pichai. There we go.

B (11:54)

He talked about this, I think, on the Door Catch podcast, where, like, there's a product that, like, what Google's trying to do is it allows its AI models to be the central intelligence of other companies. And so somebody can query the. The local LLM, the local intelligence of a company about what the F is going on. And all of a sudden, like, you automate so much labor, which is. Requires this internal bureaucracy. Like, 50% of all companies are just. Big companies are just bureaucracy. And if you can just automate that and like, the center, the hub, the brain of your company is this intelligence that. That is like the explicit future that Google is trying to go for. So in terms of this, like, intelligence puzzle piece, I think Google's kind of the furthest along there. Paint that picture a little bit more for me.

A (12:45)

Yeah. The intelligence, when applied to a company like that, it kind of flattens the hierarchy where generally there's layers of middle managers that are reporting up the chain. And it's a very lossy system that requires, like you mentioned, a lot of bureaucracy with AI. And actually just read an amazing example from Toby Lucky, the CEO of Shopify, and also Brian Armstrong, who copied him, who said that they implemented AI systems into their business. It's scanning through the Slack messages, it's looking through the GitHub repos, and it's analyzing all the changes, all the dynamics between the people, and instead of prompting the AI with decisions that it wants to make, it actually queries against the AI and says, hey, where are the biggest gaps in my company right now based on what you see? Because AI has the context of the entire company, it's able to analyze and find patterns that a CEO otherwise wouldn't have been without needing to go through the many layers of middle management. So the end result was that in the case of Brian Armstrong, that there was a conflict between these two teams, and it was a fairly large conflict that he was blissfully unaware of. That AI surfaced because it has access to these channels. And Google in particular is equipped to, I guess, handle this instance, but also handle intelligence in the past, because, I mean, like we mentioned earlier, the transformer paper was made by Google AI, essentially spawned from Google. Google was a team of researchers and still is. That failed to make a product. But they had all the intelligence, they had all the science, they had all the researchers, they had all the engineers. Now they're building this into products, they're shipping the products to the public. And what you're seeing is, is businesses like Shopify and Coinbase that are actually getting affected, where the CEOs are really changing the org structure because it is so powerful, because it is all knowing. And you have that context like you mentioned, where it could store all of the thoughts in its head and then you query against it and you become the orchestrator, you become the filter. But at the end of the day it is AI doing a lot of the thinking power.

B (14:29)

Yeah, yeah. And as I understand it, Google is like turning this into like a platform for other companies to be able to use like, use Google's intelligence products to be like the internal orchestrator of your company's like, org chart basically. And like who is better positioned to do that other than the person at the company that has, you know, Gmail and the Google Chrome and has the Gemini model and probably like seven other resources that I just can't really name at the moment. But just like the Internet runs on Google. So I feel like Google is particularly well equipped on this, this like jewel of the Thanos gauntlet.

A (15:11)

Big time. Yeah. And there's also, there's a second prong to this where they do have the ability to work with businesses. And we, we saw this earlier in the year where they signed a deal with Apple and they are going to be the exclusive AI provider for Apple's new intelligence because Apple just couldn't do it. And that's a huge deal. That is a billion dollar annual deal that is happening because Google is capable of providing this at a cost that other companies can't. The second part of this is the consumer part that doesn't affect businesses but is equally as important because Google has, what is it, about just under 4 billion users that use Gmail on a regular basis. 4 billion. It's like half of the planet is an unfathomable amount of users that use their product, that use their software because they're just so prevalent. They're freely available and they're, they're impressive tools that basically the Internet uses in a way. Google has created the foundational layer of the Internet through Google search, through Gmail, like when you use email, even if you're not using a Gmail URL, you're using the G suite of applications with your own custom domain at the end. It's just so prevalent in the Internet. And as they're starting to build up these intelligent products like Gemini and deploy them into these products, even the average consumer is starting to see huge amounts of upside where maybe they're not running a company, they're not a CEO, but they have aspirations to, or they just have aspirations to run their life more efficiently. These tools that Google has are giving it to them. And one of the, one of the realizations I had earlier this week that really stuck a pin in this Google value thing is there is this, this AI agent called claudebot that you download, you install it on your computer and you give it access to everything, all of your files on your machine, all of the documents that you have. And what I realized is that my Gemini agent that runs in Google Chrome is far more powerful than the one that has access to my desktop because it turns out all of the knowledge work I do, all of the conversations I have, all the messages are stored in Google's data centers. That's where all of my value actually accrues to not on my local machine. And Google owns that. And Google has the ability to build tools on top of it that can and further enhance that experience and offer it at a very, very low case at most points. Free.

B (17:11)

Yeah. Yeah. I guess a data owning data is a very fundamental part of, of this ener, not energy intelligence. Because if you have intelligence without data, you don't, you don't really have, you have computational power, but not without, without any inputs. And so like intelligence without data is kind of, kind of hamstrung.

A (17:32)

Yeah. And getting back to that, that earlier point of intelligence becoming a commodity, the thing that actually separates one company from another is that moat that they have is the reason to incentivize the user to come back over and over again. Because if you're really just competing on cost. So what's the wildcard on top of cost? Well, it's all that data. Google knows everything about me. It has all my emails, my order confirmations, my reservations, my messages, my calendar. And having all that value in one place is extremely sticky and makes me as a user want to come back. And Google is really taking advantage of those 4 billion people that use their products and leveraging it to, to a way that really gives them a very strong advantage in this game.

B (18:08)

Yeah. So, but there are other companies who are also going for the intelligence puzzle piece. Right. OpenAI is known as the AI company also anthropic with Claude. And also there's also XAI. And so like the Google's not The only one in this race. But you said something to me that I thought was very wise about what separates like, Google from Anthropic or Google from OpenAI. We saw like last week, Sam Altman announced that they're going to integrate ads into, into ChatGPT. And like, I think everyone is just like, pessimistic about the future of the Chat GPT product because of ads. We all have seen the quality of our experience on the Internet degrade because of capitalistic incentives. And so when ads come into the picture, like, things just degrade. Google has said that Google doesn't need to do that with Gemini. They have the Gemini product. It's comparable to ChatGPT. Maybe some people even say it's better. But like the Google is explicitly saying, no, we are going to subsidize our product so that more people use it, which is exactly their same strategy that they won, like Microsoft. When's the last time you opened up Microsoft Word, bro? Never, Never, never.

A (19:21)

Like maybe middle school, like when they forced me to.

B (19:25)

Because you use Google Docs, right?

A (19:26)

Absolutely, yeah.

B (19:27)

Because it's free and it's on the Internet, right? It's like, actually it's not like no one even cares about Google Docs as an application. It's on the website, it's on the Internet, it's inside of Chrome. And so the fact that Google also has the second puzzle piece, which is capital, which enables them to do this, is what really differentiates ChatGPT from Google. Talk about why that capital element is so, so powerful.

A (19:56)

Yeah, so like, again, the person with the most resources who can most effectively deploy them the fastest, is going to win the game. And in the case of OpenAI, they started from nothing not that long ago. And they are required to continue to raise tremendous amounts of money. Their most recent round, they're trying to raise $40 billion of capital to continue to pump into scaling these data centers and to give them more intelligence. The problem is, is that they can't actually make a profit large enough to offset the increase in costs that they need in order to scale this company to the place they want to reach AGI to get this abundant intelligence. So that leaves them very little wiggle room to one, make mistakes, but two, kind of ignore the revenue problem. They need to make revenue quickly and, and effectively, otherwise the fundraising rounds are going to dry out and they're going to have a serious problem on their hands because they have a tremendous amount of debt obligations and it's, it kind of catches them in this weird dilemma where good Companies continue to make great products and they continue to add value to their users. And While I believe ChatGPT is going to do that, there is a trap that a lot of companies fall into in the absence of innovation, which is becoming extractive of their user base to further build their revenue model. And the ad model, which is very web2 coded applied to this future abundant AI that should be able to do anything and should be able to generate so much value that it doesn't matter if you're selling ads, feels like a trap that they're getting caught in where they're beginning to become extractive of their user base in a world where that's probably not ideal. And Google has the luxury because they have this gigantic balance sheet they want. They run one of the highest margin businesses on earth. They have the ability to basically subsidize their way out of this competition with OpenAI, where I think OpenAI, when they released ChatGPT for the first time, it was GPT 3.5. That was kind of the opening bell. And it caught Google very much off guard and it caught everyone else off guard. They got like half a billion users before anyone even could create a competitive product. But they don't have the balance sheet to subsidize. Now Google can come and say, hey, we don't need the money now. We have a ton of money. We just want to create the best product. We're going to offer you the best product at the best price and therefore you don't need to go over there and either pay $20 a month to get served ads. We're just going to give you a better product for free here. Go have fun and welcome to our ecosystem.

B (22:14)

Yeah, yeah, yeah. And, and I mean, I'm not Sam Altman. He seems like a very competent operator, but man, seeing being the idea of being Sam Altman right now seems to be very stressful.

A (22:25)

I don't envy his position.

B (22:26)

No, yeah, because, because like, even if ChatGPT is in a vacuum, a better, a better model, a better LLM than Google's Gemini, when you add ads on it, you just might end up tilting the favor in Google's balance. And like all of a sudden your users just naturally flow to Google and Google just incentivizes its own, creates its own and further network effects that it already has massive network effects of. And so like the idea of just like ChatGPT being compelled by capitalism to add ads might also be the thing that makes it uncompetitive with somebody who also has the capital puzzle piece on Its Thanos gauntlet of capitalism.

A (23:12)

Yeah. And it's this impossible problem which has been the contradiction with OpenAI since day one, where they started as a nonprofit and then they were like, oh, wait a second, we really need a lot of capital. And then they're like, oh, wait a second, we actually need to make some revenue so that we can pay back the debts from this capital we need to raise. And it's this perpetual debt that they are accruing just to catch up to these conglomerates that have the capital already to deploy and to build these things. So the intelligence problem with OpenAI is a real one. And you see the struggle as well with their new products like the, the rumored social media feed or the Sora feed. It just feels a little lost. It feels like they're trying to go viral for the sake of earning users and earning revenue versus actually creating a really compelling product that generates net new value. Not just like web 2.0, we're creating the AI Facebook now with ads on.

B (23:59)

Top, but with web 2.0. But make it AI. Yeah, exactly, because they announced that they are working on a, you know, a world coin human verified social network, which is potentially a great upgrade from the social networks that we currently have because of. It's human verified, but nonetheless, dude, it's a social network. Like, who the f cares, man? We got those. What value is that contributing to humanity in the year 2026?

A (24:24)

Yeah, and it's, it's. It would be the ultimate tragedy. Right. Is because the. So much of the engineering density and talent in the early 2000s, mid mid 2010s went towards generating these algorithmic social feeds to get people hooked and addicted, to see more ads, to generate more revenue. And that business model applied to AI just seems so sad and so dry because there is so much upside with this AI. It is uncapped. You can do so many amazing new things, create new products, innovate on top of it. It would be a shame to just get stuck back in that old place and continue to, to build there.

B (24:55)

Okay, so that those are the first two puzzle pieces, intelligence and capital. And I think we did a good job illustrating the relationship between those two things. I wanted to add the third jewel to the Thanos gauntlet of capitalism, Energy. As we alluded to, you get more intelligence when you just pump energy through LLMs. That's actually something that you taught me. Maybe you could talk a little bit more about that, but also talk about just like the importance of energy as it relates to both intelligence and also just like Kind of everything.

A (25:28)

Yeah. In the gauntlet, the most important one, and at the end of the day, the only one that truly matters is this energy pillar. Because in the absence of it, there is no capital, there is no intelligence. It is a direct downstream effect of energy. And we have some trouble getting energy. And this is going to be a continued struggle and probably some sort of a bottleneck in terms of moving forward and how AI progresses. But the energy thing is super critical because there is that direct correlation between energy in and intelligence out. And the companies that are most equipped to leverage this to get to multiple gigawatts to terawatts of AI compute and training, they're going to be the ones that win because it is the scarcest resource. It's so difficult to get energy in the United States. We produce what is. I think we use about 1.3 terawatts of energy per year. We're only able to use about half of that. And the projections by the end of this decade for AI data centers are going to consume a huge percentage of that if we don't build more energy. So the energy problem is very real. And in a way, energy, I believe in a world of abundance like we are, we're kind of hinting at. Energy does become the end state of capital, too, where, like, the end currency is likely wattage instead of dollars. And I think that's an important denomination because wattage can actually get you value. Wattage can be converted into anything. It could be converted into intelligence and therefore anything downstream of that. Whereas currency, I mean, it's. It's very ficky, or it's very, like, fickle. It can. It can be debased, it can be changed. But energy is energy, and we have a shortage of it, and we probably always will as we continue to scale these AI systems.

B (27:07)

I think what you alluded to is, like, when you have all four puzzle pieces, you have energy, you have energy, you have labor, you have capital, and you have intelligence. You don't need money anymore because those are the four things that you need to do anything that you want in the world you like. Capital has just been. Money has been basically just trying to coordinate resources. But if you own all the resources and you have access to all the resources, you don't actually need to coordinate them yourself because you have the intelligence to do so. But we are skipping ahead a little bit. I do. I keep. I keep wanting to. I want to drill down a little bit more on the energy thing. Is it true that there are data centers out there that have like Nvidia chips ready to go and they're just idle because they don't have power. I heard that like somewhere not terribly long ago. Is that true?

A (27:55)

There was a case where that's true. I'm not sure that still is, but that will be an impending problem, I would imagine.

B (28:00)

Does that mean, does that imply that we are producing more GPUs, we're manufacturing GPUs faster than we can produce energy.

A (28:07)

To power them currently it appears as if that is the current trend. I don't suspect that will continue to be true because we are, we are very much going to hit a chip wall in the next couple of years should there not be more fabs that come online. But in terms of the energy issue, it is true and it's, it's due to two things. One of it is just that the grid doesn't have a sufficient amount of energy to supply these data centers without ruining everything else. It's like these data centers are very power hungry. A single data center, I believe one of one of Xai's new colossus data centers consumes about as much electricity as San Francisco, the city. So it's a tremendous amount of energy density packed into one place and it does have a burden on the grid. The second part of this problem is actually building the data centers and getting the rights and the approvals and all of the other requirements needed to get the power plugged into this thing. They're meeting a lot of resistance through the cities that they build in because it's a big impact on whatever town or city they're being built in. It's a huge strain on the grid. They use a lot of resources to make a lot of noise. It's, it's very taxing on a city or state that it's placed in and they're having problems there too. So it, it is twofold. We're running up against the energy problem for sure. There will be dark GPUs because we just can't power them. But then there's also a world in which we can power them and we don't have gpu. So it's this very fragile balance between the resources here. And like when everyone likes to talk about a bubble and where it's going to form and how it's going to play out. And it's important to just kind of have your eye on all of the, the elements that are involved and down the whole stack, even things like RAM and memory are becoming a big bottleneck. So energy is important. It is challenging, particularly with all the legislation, particularly with the. An outdated grid that isn't built for data centers. And it's causing a lot of problems.

B (29:55)

Yeah, okay, so you pump more energy through an AI model, you get more intelligence. Also, if you pump energy through the last puzzle piece, labor, you also get more manufacturing. So these are the, this is how this relates to the other puzzle pieces as well. If we want to move not bits, but atoms over the last 20 years, the last two decades, human innovation has all happened in the world of bits. Like, we haven't really innovated. By contrast, in the world of atoms, very much like all of the innovation happened behind screens. Like, if you wanted to go find the future over the last 20 years, you had to go into your phone, you had to go look at your computer. Maybe that's because labor hasn't really been all that innovative. And the way that energy feeds into labor. Let's talk about that next. Let's talk about labor, because there are a few companies out there who are in the same way that the AI Labs, Anthropic, OpenAI, Google, XAI are commoditizing intelligence. There's a few companies out there who are commoditizing labor in the exact same way. Can you talk about that?

A (31:03)

Yes. And to your point about the world's changing slowly, there's this great example that I love where someone who was born in 1870 and lived to 1920, just in those 50 years, over that time, they saw the invention of electricity, the telephone, the automobile, the airplane. Like you, you were born and there was horse and buggies, and by the time you were 50, there was airplanes flying through the sky. And that was downstream of this like unbelievable era of manufacturing and industrializing and building net new things. Since then, we've stalled. We went to the moon like how many years ago? And we haven't been able to go back. There's been this like, very clear stalling in the world of atoms like you mentioned, in exchange for progress in the world of bits, where the Internet as, as an invention, as a creation, has changed the world as we know it, but the world itself hasn't really changed a whole lot outside and labor and the decreasing cost of labor is going to change that in a huge way. And I think that's the theme between all of these gauntlets, except for capital, is that there is deflationary effects happening. And as those deflationary effects happen, as the cost of labor, the cost of per kilowatt, the cost per piece of intelligence per token goes down, it unlocks this tremendous amount of abundance. And in the world of labor, in particular, humanoid robots, is the very clear displacement of. Of that value capture. And with the advent of these humanoid robots at scale with the intelligence that we spoke about, that pillar built into them, they are able to basically capitalize, just revolutionize the economy in a way that, that offsets a lot of the labor that humans have for a significantly less cost, which therefore uncaps the upside, because the really, like, the GDP of a country is really just like the. The amount of the output of a person times the amount of people. And that's like how much output you're able to create, how much value you're able to create. And if you replace the person element with a robotic element, that works 24 7, that works without making any mistakes, that has no patience, that doesn't talk back, that is just doing a job, executing an outcome, it essentially uncaps what labor markets are capable of, and it allows you to change the world around us. Because labor is so cheap and people have gotten lazy. We got a good life. It's been very easy to sit back and scroll on those timelines that we talked about that were generated to optimize pleasure. And it's this really easy trap that you get caught into, which we have. And it's probably led to a significant decline in terms of our actual innovation in the physical world, Especially when you.

B (33:28)

Combine intelligence and labor, like blue collar and white collar. Do you mean, like, all of the human jobs out there? Not to get dystopian? I don't really think I want to care to, like, say that, like, all humans are just going to become unnecessary. That's a different podcast episode. What this episode is about is, like, we are literally building robots this year. There are going to be robots that walk among us this year. We have already been working on intelligence for four years, and that race isn't stopping anytime soon. If only it's getting faster. You put those two pieces, those puzzle pieces together, Intelligent robots, that's the complete labor force. That's the atlas that holds up the world's gdp. And what if you had a labor force that was. You didn't have to feed, you didn't have to have bathroom breaks, you didn't have to pay for health care. Ignoring the dystopian stuff. Again, separate episode. Fundamentally, the GDP that comes out for the profits of corporations will just go through the roof because the costs will go down. Intelligence, the cost of intelligence going down, the cost of labor is going down, and you have a fleet of robots that can work 24 7, 365. We can just do things at that point. We can do anything at that point.

A (34:45)

There's two compounding effects here that are both exponential. One is the. I mean, the exponential decrease in cost per labor per intelligence, but then also the output per unit of labor. The output per humanoid versus human is so far higher at such a lower cost that you're getting these double exponentials at once. And it creates this very vertical growth in terms of how much value you're able to create. And what we're starting to see now is the first part of that in this world of bits in this digital cyberspace, through these AI intelligence systems that exist on your computer behind your screen. And the automating of these workflows is, is becoming. It's getting to a point where people are getting laid off. Companies are changing because the needs are changing because these AIs are so effective at reaching verifiable outcomes. So long as you can verify the outcome of your knowledge work on a computer, you can train an AI to do it effectively first and then perfectly at the end state that continues out to the physical world where you combine these two. You merge the intelligent part with the physical part. You give the intelligence a physical manifestation that is as capable as a human. And when you deploy these at scale, you, you create this new unlock and Jevons paradox where you. What do you do now that you have all this labor? Well, you have all these cool new problems that you could set it to solve. And there's so much abundance that comes from it, because there is no task that is too difficult or too laborious or too intellectually complex that a robot can't do for a few pennies per. Per hour per minute, whatever the cost is going to be that a human otherwise wouldn't be able to. So the unlocks that we'll see from that are going to be huge.

B (36:15)

There's the meme out there that like, the United States just sucks at manufacturing and also, like infrastructure too. Like, you go, there was that video that was rocketing around Twitter not terribly long ago of like this Chinese laborers built a bridge in like a weekend. And they like, they shut down this highway, they demolished it, they built it up, and then they built a bridge, poured the concrete, and then it was done in a weekend, and they probably had to let the concrete dry a little bit longer, but like, whatever. And then cars were dry driving over it in a very short amount of time. That's, that's about regulations. But nonetheless the idea is that, like, what if you had a fleet of robots who you could just set on a task to go do things. And all you need in order to do that is you need the robots, you need the energy to power them, and you need the intelligence to make them smart. And there are companies working on all three of those things. And I also have the capital to be able to finance that. And so, like, when we talk about shaping the future of the world, these feedback loops become very, very powerful when we can start to just literally do whatever we want. And there are certain companies that are closer to this outcome than others.

A (37:27)

Yeah, big time. I mean, a company like Tesla is. They just canceled their Model S and X production lines in exchange for creating more humanoid robots this year, so they can get to a million of those.

B (37:36)

They traded cars for robots.

A (37:37)

They traded cars for robots. And they're going to continue to go down this automation trajectory because it is by far the most profitable, most effective towards this world of abundance. And it makes sense that at the limit, basically all labor will be done through some sort of artificial intelligence system and some sort of robotic vessel for it. Because it, again, it's just at the limit. It is so far superior. A company with a series of verifiable outcomes, like we mentioned, say accounting, for example, that has a hundred humans and a hundred AIs is obviously going to beat by a hundred AIs. But even the company with 99 AIs and one human is going to be beat by the company that has a hundred AIs, because that one human is the loss function. It's, it makes mistakes, it gets tired, it's not sure if there is even a single human in the loop through a lot of these things. It becomes a disadvantage because the AI machines, the humanoid robots, are so far superior or they will soon be so far superior. And it begs the question, is like, what. What happens to us then? And I don't think this is. It is a period of change. It is a big transition period for sure, but the backside of it doesn't have to be the doomer take. It's like my, my favorite example going back to the social media feeds, is that their social media feeds are a real thing. Like there are things called influencers as a profession where you can say things and travel the world and make videos and you can create content because people have so much abundant time and capital to spend consuming your content and then buying into the things that you were selling on behalf of other companies. And that is this luxury industry that we have created that couldn't have existed even 30 years ago because we just didn't have that. We didn't have the free time, we didn't have the abundant capital. And the same thing is true for a lot of other things that we see. Like F1 is another example that I love the racing league. I watched the movie from Apple earlier this year and it's this huge event that is a multi billion dollar industry that employs tens of thousands of people, that attracts millions of people per year, but it doesn't actually contribute much to society. Like it's, it's entertaining. It's like sports. A lot of these things are. They're not directly contributing to the forward progression of, I guess, humankind, but they're fun and they give people purpose and there's going to be a lot more opportunities for that as the need for this labor continues to decrease and we have more abundance of free time and free capital as just normal people to enjoy it and spend it in different subcategories.

B (39:55)

Yeah, I think like we've alluded to just like this dystopian future that I think people are very afraid of when like AI takes all of our jobs, all the, all the white collar jobs and then robots take all the blue collar jobs and then, and then what is left of the human spirit. I think that's a fine fear to have. At the same time, like I will not be psyoped into believing that when labor and intelligence are free that my life gets worse somehow. Like I don't. Like I. We can talk about the, the, the long term, who owns what, where all the capital ends up. But like if labor and intelligence and energy are all free, we can literally build stuff for free. And like, I don't know, it does. It's weird to that people think that that's going to like produce like a negative output to society and.

A (40:44)

No, it's difficult to imagine a world where we have this abundance and you aren't in a better place than you are today. It's like people born today, even among the poorest people born today, are in a far better position than the wealthiest people were a hundred years ago. And that continues to happen as we progress forward.

B (40:59)

Hey, Bankless nation, it's David. If you're hearing this, that's because you are listening to the free Bankless podcast feed. Did you know that there is a premium Bankless RSS feed? The premium feed has extra interviews that I do for my own personal research and just deeper questions that I want answered about the crypto industry. Industry questions that I want to answer so I can be more informed as an investor both at Bankless Ventures and also just in my own personal portfolio too. Also, there are no ads, which means if you listen to the premium feed instead of the free feed, you'll get about 20 hours of your life back every year because you choose to support Bankless directly. So if you're interested in getting extra content all while skipping the ads, or you just appreciate what we do here and want us to keep doing it, we'd appreciate it if you signed up for Bankless Premium and there is a link in the Show Notes to get started. Cheers to a good 2026 what if you could trade gold, Forex and global markets with the same tools and speed that you use for crypto? That's exactly what Bitget Tradfi unlocks. After strong beta demand, including over $100 million in single day gold trading volume, Bitget Tradfi is now live for all users. Inside of your existing Bitget account. You can trade 79 instruments across Forex, precious metals, indices and commodities all settled directly in usdt. No platform switching and no fiat conversions. This is Bitget's universal exchange vision in action. Crypto and traditional finance side by side. You get deep liquidity, low slippage and leverage up to 500x, letting you apply crypto strategies to macro markets. New to Tradfi. Start with Gold. The Gold USD pair is liquid, macro driven and a familiar natural bridge between crypto and traditional markets. Try trading Gold on bitget now@bitget.com click the link in the Show Notes for more information. This is not financial advice. Okay Josh, those are the four puzzle pieces. Intelligence, Energy, Capital, labor and the idea here, that's my my investment thesis for my own financial portfolio is whichever company gets all four just wins the game. And this is going to happen probably in our lifetime. Like we're probably going to solve these things. We're going to solve energy, we're going to solve intelligence, we're going to solve labor, and then, and then that makes capital irrelevant. And so I'm calling this like the event horizon of capitalism. It's just like when a company reaches a point where its growth on all four of these things just becomes like self reinforced, reinforcing and just structurally irreversible. They win the monopoly board. And there are some companies I want to talk to you about because I think there are some that are closer than others. We talked about Google, but maybe let's just trace over it again. Google has in my mind intelligence and capital it has Google Gemini and it's being able to. And it also has the data very important, which is not necessarily what any other AI lab has. It has far more data and connectivity to everyone on the Internet than any other AI labs. So it has intelligence in a way that other AI labs don't. And it also has the capital. So Google to me feels very well positioned to have a very strong grasp on two of the four Thanos jewels. What do you think about that?

A (43:58)

Yes, and in a way they're, they're well positioned for energy too, because while they cannot generate the energy, they have very efficient ways of extracting intelligence from it. And that's mostly due to the hardware chips that they've built. The, they have These, they're called TPUs. They're tensor processing units. And one of the advantages going back to the advantages of Google is the just sheer intelligence of the humans that work there, of the actual people and researchers that have worked there. And again, they invented the transformer, but they also invented this TPU, realizing and understanding that AIs were going to be trained to using a very different set of math than traditional GPUs are good at. So when Nvidia makes a GPU, it's a general purpose processing unit. It's the same GPU that can play video games, that is training AI with a Google tpu. It is far more efficient because it is good at the specific type of math required to train these models. So Google has this TPU and they're able to get a lot more compute per watt out of their AI models than a traditional company. So while they aren't actually generating the energy, they are far more efficient at extracting it and decreasing that cost per token through energy. So I think they're uniquely equipped across the board. We talked about the data monopoly that they have, we talked about the capital efficiency that they have, and just the raw human intelligence that's capable of pushing this forward. And this hasn't been the case up until maybe mid 2024. Google was actually having a really difficult time productizing this. And while they had all of the pieces, they couldn't actually generate a, a good consumer product. Larry and Sergey came back to the company, particularly Sergey, and he kind of turned the ship around. And now they are shipping at a velocity that's, that's unbelievably impressive. And a downstream effect of the capital that they have is, is their ability to give people time and space to do research to unlock these novel breakthroughs. And Google DeepMind is a really Great example of that. Because Google acquired DeepMind a very long time ago and let them just exist in this weird place that was not really connected with Google. They were just like, hey, they protected them.

B (45:57)

They protected them from like Zuck trying to buy them out and shelve them in a capitalistic package or anyone else trying. They just like the, as I understand it, the DeepMind people were just like dude, I just want to like research.

A (46:09)

Just want to research.

B (46:10)

And Google's like, great, here's money, don't let anyone else buy you, here's money to go do research. And then they just bought themselves time. And when it came time for them to take the DeepMind research off the shelf and put it into the Google stack, they had that optionality available to them because they had capital.

A (46:28)

Yeah, they bought an option and because they had the balance sheet to do that, they could afford to put that much capital on, out on loan for however many years it took until demis and the DeepMind team now run Google's AI intelligence division and it runs basically all of Google's AI kind of eating the in house Google brain team that was existing. So they have this, this really unique opportunity across the board to do it and for the first time in a long time they're, they're acting on it and they're releasing the products and they're building the hardware and they're controlling this full vertically integrated stack that is required to win at scale. And it's very difficult to make a case that Google won't be, if not the first, among the very first to cross this event horizon threshold. There's just no one better equipped.

B (47:09)

Yeah, what about Nvidia? Where would you classify Nvidia? Because I suppose if we're putting data, like, if Google has like an almost monopoly on data in the intelligence category, I suppose you could also put Nvidia there because it has like a somewhat monopoly on chip production and you need, you need chips to have intelligence. Like in order to get intelligence you need energy, you need data, you need chips, and you need the model itself. Right. So maybe, maybe Nvidia belongs in the intelligence category.

A (47:38)

Nvidia certainly belongs in the intelligence category. But it's going to be difficult to defend that moat and it's going to be difficult to grow at a scale that a company like Google will. Because I mean again to the point about the TPUs, Google has their own AI training chips and it is very advantageous to have your own because you own the whole stack. So they can squeeze out extra margins, they could optimize the software for it in a way that you can't with Nvidia chips. Now Nvidia is a huge company with a tremendous amount of upside, but all of the market forces are working against it. Companies like Apple with M series chips that they prove that you could build a chip that works better. Google is building their chips. Tesla is about to build a Terrafab. A lot of companies are trying to in house their chips. Even OpenAI and Anthropic are working with other companies to try to develop their own because there's such an advantage of owning the entire stack. And for the few companies that can't afford to do this, that don't have their own custom fabs or that can't actually build these things, Nvidia is going to be there for them. And Nvidia will be the sole supplier of, if not training then inference compute. And that's a huge market. But it's not this untapped, uncapped upside that a company like Google can actually reach.

B (48:46)

Yeah. So I think if we're saying whichever company wins this race to get over this capitalistic event horizon, they are going to be building their own chips, it's.

A (48:56)

Most likely also because they could do that at scale. And the vertical integration, the scale, it all leads to a successful winning game.

B (49:05)

Right. Okay, let's talk about Tesla. Where do you see Tesla in this race?

A (49:10)

Okay, Tesla, I call me biased, but Tesla is the clear winner to me.

B (49:15)

In terms for the listener, Josh is.

A (49:17)

A huge Tesla moon boy, but rightfully so. And I have, listen, this is not, this is, this is like I have, I can explain why. And Tesla is good at something that no other company is and that's, that's manufacturing at scale with net new products. If you look at a company like Google or you look at a company like Apple, who probably creates some of the most consumer products of any company in the world through these handsets, like the iPhones and the pixels and the androids, they're very good at building small and specific things. Like Google was able to pivot to building these pixel buds where you get earphones and you get these small consumer product devices. But to manufacture large complicated things at scale is a tremendously difficult problem. And in order to offset that labor pillar, you must do this, you must create some sort of robot, some sort of physical embodiment of this intelligence.

B (50:12)

I suppose the difference that you just described, the difference between Google's hardware and Apple's hardware is it's bit oriented hardware, it's Internet oriented. Hardware where Tesla is atom oriented hardware. I think that's kind of the emphasis you're making.

A (50:28)

That's right, yeah. It's a great way to put it is yet Tesla creates products for real world infrastructure and productivity. It's like the, the cyber cab is going to displace all of the lost productivity that people experience every day through driving and traffic. That's a huge unlock. And not only that, the cyber, the.

B (50:46)

Cyber Cab, Tesla network, that's going to displace Uber, Lyft, all ride sharing maybe because Tesla just produces its own cars. And now transportation is essentially at the cost of Tesla, which is free because they have batteries and energy and stuff. Is that kind of what you're talking about?

A (51:04)

Yeah, but like why stop there? Why not UPS and FedEx and the Postal service? Like so many things get transferred, so many things move like so many people and boxes and packages and information gets moved through the physical world. And if you decrease the cost per kilometer to a price that is so far lower than any price that a human could do it for, it becomes economically unviable to go with any other product and service. And there's no company better suited to do this because they have proven that they could roll these things out at scale than Tesla and they're hyper optimized on getting that cost per km down because it allows you to displace transportation like there. You will not need to ever drive a car in the future. But also someone born today will never need to own a car because it'll be economically inefficient because the cost to use this service is so low. And that's just in terms of transportation. And then the humanoid element is what they're pivoting to this year. They're going to start with a million and then they're going to ramp up to 10 million, 100 million, a billion. And the idea is to have multiple humanoid robots per human because they will be so cheap, so abundant and so easy to manufacture. And there eventually reaches a world where there's this like self propagating machine where the machine builds the machine. But the, the labor thing gets offset so much by these humanoid robots, by these cyber cabs at scale. And there's no other company on earth that has proven they can build complex products like this that impact the real world other than Tesla and perhaps some companies out of China, which seems like a real threat. But Tesla, in terms of just American companies that we can invest in today, they are by far the winner in this physical manufacturing race.

B (52:37)

So we talked about why Google has the advantage over Anthropic or OpenAI, it's because they have capital they can scale. Like Google can stumble and recover. But if OpenAI stumbles, like if it invests a billion dollars into building a social network that no one uses, that's almost like catastrophic for them because they just invested so much into that. I think we can extend that same idea to humanoid robots. There are other robot startups out there and you know, Tesla is one of them. But Tesla's not a startup. Tesla has a publicly traded multi trillion dollar company. And so the robot startups, I don't know, maybe you could, you could name a few, might stumble and fail because they are walking on a razor edge because they are a startup. But that's not what Tesla is. Tesla is a profitable company, right?

A (53:27)

Yeah. So a figure in a way is kind of like the Rivian to Tesla. Uh, it's like the rip figure is the, the alternative to Tesla when it comes to Tesla. Yeah, it's like the all. Yeah, exactly. So like what Rivian is to the cars, figure is to the humanoids, the Optimus program. And the problem with figure is that, well, one, they are having a difficult time with the actual autonomy because they don't have the data set of tens of millions of these miles driven with these cars. And then two, they don't actually have the manufacturing capabilities at scale to do this. And an underrated part of this equation is actually the founder is Elon, is the team that is building this. There is no one in the world who's, who's accomplished so many impossible missions and succeeded at scale when it comes to manufacturing, and it's just this remarkably difficult challenge to do. So not only is figure out a disadvantage when it comes to capital, when it comes to manufacturing capability, when it comes to actual like raw intelligence, but they're also at a disadvantage of experience. They've never done anything like this before. And there were many moments in time in which Tesla was weeks away from bankruptcy in 2017, 2018, when it came to building the Model 3 production line. And for someone to build humanoid robots at the scale required to get the cost per humanoid down to a required level, it's going to be this unbelievably difficult uphill task where if you do make a mistake, if, if you have a single glut in your supply chain that prevents you from getting a single motor that, from this third party company in Taiwan that's not shipping that day, the entire production line stops. And Tesla's realized this and they've created a, a battery, a cathode plant in the United States, the first one, and they've created a refinery in the United States. The cutting edge of this because they realize the existential threat that is supply chains, particularly international. And a company like Figure just doesn't have the resources and capital to spread their wings out that far and actually make sure that they have the redundancies needed to build this at scale successfully.

B (55:20)

Now that's not to say that like Figure won't be an incredibly successful startup. Same thing with OpenAI. Right? I mean granted, OpenAI is like rumored to go public at a trillion dollars and so that might be a little bit rich for my blood. But like Figure, for example, its last valuation in September of 2025, $39 billion compared to like what, what's, what's the Tesla market cap?

A (55:43)

1.3 trillion today, 1.3 trillion.

B (55:45)

And, but so like the idea that we're talking about is like this race to fill out the Thanos gauntlet. But you also have to, we also have to understand, listeners also have to understand that the market prices things and these companies are being priced according to their race towards the Thanos gauntlet of capitalism. And so it's not to say that like Figure is a bad investment, but it's just like Figure is, is so far away from finishing its Thanos gauntlet, that's not even in consideration. Like we're talking about these companies that are like working on monopolizing basically everything about capitalism. So I kind of want to just throw that corollary in there.

A (56:23)

Yeah, that's correct. This is in no way degrading towards the companies who are doing great work. Figure is an amazing company building very difficult things and solving complex challenges. It's just there are levels and Tesla is just at a different level in this game of reaching that capitalistic end game goal.

B (56:39)

The end game of capitalism. Yeah, yeah. Let's talk about SpaceX because something interesting happened today actually right as we started recording, there was a rumor that went out. Elon Musk, SpaceX is in talks to merge with Xai before their IPO, which is inherent, incredibly relevant to this conversation. So when we, when we talk about the, the game of risk that is being played between some of these companies very far along on this race. Where do you see SpaceX?

A (57:06)

And ironically just in Tesla's earnings report yesterday they made a large investment in X AI. So there is going to be a convergence happening between the three of these companies.

B (57:15)

Okay, wait, hold on. There's this rumor that came out today that I just said SpaceX in talks to merge with XAI before IPO. And you're just saying that Tesla has bought a bunch of XAI shares.

A (57:25)

It's just an OS report this week. Yes.

B (57:28)

Okay, so there's already a three way convergence happening here.

A (57:31)

It's slowly starting to happen and it makes a lot of sense. So if you look at what each company is good at, XAI is exceptional at intelligence, Tesla is exceptional at manufacturing, and SpaceX owns a monopoly on low Earth orbit and beyond.

B (57:45)

SpaceX is like about to maybe hasn't quite go actually maybe. How far along is it on its monopoly?

A (57:51)

So it has the Falcon Heavy and the Falcon 9 program is successful. They're launching satellites on behalf of private customers. They're launching the Starlink satellites into outer space. There is a successful constellation, there is launches almost every day now. I think they launch over 500. It's just like an outrageous amount of payload going into outer orbit. But the problem is it's just, it's not enough to make it cost effective at the scale we need to move a lot of this intelligence into outer space. And that's enabled through the Starship program, which isn't fully up and running. It's still a work in progress. The starships are still going through test launch, they're still exploding, but they're getting close. And the, the expectation is that by the end of this year the Starship program will be working and it will be able to send a lot of this payload, some of it will be AI Data Training center into orbit and particularly into low Earth orbit where now we have Starlink, that Apple is rumored to be partnering with SpaceX, where all the cell phones on Earth get access to Starlink space satellites. So the perfect handset is one that I always dreamed of, which has unlimited battery and unlimited connection, where no matter where you go in the world, you have no dead zones. And SpaceX enables that to happen at scale for everyone in the world. It brings everyone online through this basically nation state resistance network that exists out in low Earth orbit in outer space.

B (59:06)

Okay, what about the energy equation? A part of space, because I mentioned AI data centers, because this is relevant to energy here.

A (59:13)

Yes. And the convergence between the three, which I didn't finish my thought, which was AI or Xai runs the intelligence, Tesla makes the chips, SpaceX launches them into outer space. So the chips that are going to be trained to build AGI are going to be Tesla chips and the XAI is going to be the orchestrator of that. The AI Data center in space thing is a new novelty. It's. This is a new thing that has kind of come online in the last few months because it's only recently been made possible through the Starship program, hopefully working. And the idea is that you need a certain amount of energy in space in order to offset the costs. Enough so that it's more lucrative to, to train data centers in space than it is on the ground. With Starlink at scale, if they launch about 10,000 of these rockets per year, the cost per kilogram gets lower than it does to send AI space and AI data centers into orbit than it does to run them on the ground. And it solves a lot of problems. One of them is the cooling issue, because when you're on the ground, not only do you have to deal with the permitting and you have to deal with the energy, but you also have to deal with the cooling. There's a tremendous amount of liquid cooling that goes on. There's coolers, there's fans. It takes up about 20 to 25% of the footprint of these data centers. Well, it turns out space is a vacuum. And in the absence of sun, if you just put a little umbrella over these chips, it's fairly easy to cool. You just radiate the heat off into space. And the maintenance doesn't really, it's not really a factor because there's not, there's no moving parts, there's not a lot of water running through.

B (60:40)

The temperature fluctuation is the number one degrading force on chips.

A (60:44)

Yes, absolutely. If it's too hot or if it's too cold, they don't work as well. Space, you can control that very easily just by blocking the sun. The energy problem gets solved through things like sun synchronous orbit, which basically means when you launch a satellite into space, you match the orbit of the sun. So it's always perpetually right in the sun's rays.

B (61:01)

Right. You have a solar panel that is all 24, 7, 365 pointed at the sun.

A (61:05)

Exactly. And when it is outer space, it is, I think it's seven to eight times more efficient than it is on Earth because you remove the atmospheric part of the equation.

B (61:15)

So energy, does that mean that the sun is seven to eight times more intense in the in space? I think that's what that means, yes.

A (61:22)

Because when you measure the ozone layer protects us here, but without it, you are just getting blasted by some. The UV is like a thousand there or something. I didn't know that. Yeah, the UV index is very high in space because there is nothing protecting you from it. So you would get a pretty bad sunburn if you were standing in space for a couple of minutes, but pretty.

B (61:37)

Sick if you're a solar panel.

A (61:38)

Pretty sick if you're a solar panel. And that is what they're planning to launch up there at scale. So the interesting thing about SpaceX is because of all of the companies on Earth, this is probably the most challenging engineering problem is getting a rapidly reusable skyscraper to go up and down every day. And airlines launch about or they not launch, but they fly about 100,000 planes per year. If SpaceX can do 1/10 of that, then the AI data center and space thing makes sense. And if it makes sense in the same way that it becomes a no brainer to take an autonomous car versus a human driven car, then all of that AI training goes into outer space. And that kind of absolves us of a lot of the burden of the energy tax that we have to pay to run these data centers on space and the actual footprint and a lot of the pain points that come from space. And it unlocks this whole new industry. There is no outer limit to the type of value you could extract from getting into orbit. And SpaceX is the only one uniquely equipped to do this.

B (62:30)

I think the idea of an AI data center in space is so incredibly sci fi it takes a while to wrap your head around. To this day I still ask the questions like, but like, I don't know, what about like nuclear reactors here on Earth? What about fusion and fission? Aren't we trying to unlock energy? Far more abundant energy than like, you know, solar is cool dude. And like sure, 7x more powerful solar also great, but like nuclear man, like why is that the answer?

A (63:00)

Well, we do have nuclear at scale. In fact it consumes 99% of the mass in our little universe here, which is a sun. And the sun is just incredibly abundant and it is available and it is free and it produces far more energy than this Earth is capable of actually using. I think we capture 1 or 0.0705% of the Sun's rays on Earth. And it's such a small percentage, but it accounts for so much energy. And nuclear is great. Nuclear is fun. It is. It'll work great for local AI training clusters, local AI inference, but at scale and we're talking about like really high limits. You really want the sun because there's more of it than there is anything else. So on Earth you're going to have inference which is the, the AI in which latency matters. So when you need to query an AI model to give you an answer quickly, you want to have that AI on Earth and that can be powered by nuclear. That's great. It might be solar, it might be nuclear, and nuclear has a very long road ahead of it to get here. But if it does, that would be awesome. A lot of the training very compute heavy. A lot the very energy heavy stuff that should be moved to outer space, that will all be solar because it's so abundant and so much easier than it is to produce nuclear energy. And it seems like so long as these scaling laws continue to be maintained, where you put energy in, you get intelligence out, there is no upper bound to the amount of energy you need. And you don't want that burden being held on Earth. You want to kind of defer that off into space. You want to do all of that hard training there's. And to build and capture as much of this energy as you can to give us higher intelligence and beam it back down to Earth and improve the quality of life that we have down here.

B (64:38)

Okay, so what I'm kind of hearing you saying is like, there's some sort of like, logical conclusion of just like if we want max energy, you got to go to space.

A (64:47)

Mm, yeah, that's it. Because we'll reach a limit at some point here on Earth where we will just have more demands than we will be able to supply. And you think about what does the world look like when you have to charge 2 billion humanoid batteries? That's a lot of energy. Like our grids are not equipped to support that.

B (65:04)

So how do we charge them in space?

A (65:06)

We'll charge them in space through solar. They don't get sunburn.

B (65:08)

Yeah, but then how do we get the batteries?

A (65:10)

We'll hopefully have enough materials to refine it here. If not, set up a base on the moon. The moon has 18 the gravity of Earth. You set up a little maglev thing. You get it? I think it's 2500 meters per second is the launch speed. And you send it right back to Earth. All the materials that we need.

B (65:24)

Okay. So we're developing supply chains in space. So we need that to work, right?

A (65:30)

Yes, there will be a limit. I'm not sure where that is here on Earth, just in terms of the scale. If we actually do continue to expand at this rate, that we will start to need intercontinental or I guess interplanetary resources.

B (65:43)

Right, right, right, right. That seems far away.

A (65:45)

Very far away. Okay, we're getting sci fi. But we are at the early steps of the sci fi future. Like now it's possible in a world in which it previously was not. And I think that zero to one moment that just happened is the exciting.

B (65:58)

Part here, I suppose. While it seems far away, I don't know what far away means to you. 2040, 2050.

A (66:06)

It's tough to put a timeline on things because I remember even last year there was this huge debate about the AGI in 2027. That was the biggest thing is the essay was published. People were really fighting for both sides. And now we're sitting here in the beginning of 2026 and almost everyone is saying, well, if we're not getting AGI in 2027, then there's no way we're not getting it in 2028. It is happening far faster than we thought. So it's really difficult to understand the timelines because again, we're one novel breakthrough away from a huge improvement. If one algorithmic improvement gives us 10 times the efficiency of the existing chipset when it comes to training and inference, then suddenly our AIs get 10 times better for 110 the cost. And that could happen in a matter of weeks. So we're really at the burden of these large breakthroughs. And depending on how quick they happen, you can see the world change fairly quickly.

B (66:52)

And I suppose, like, while the idea of supply chains in space seems so foreign and so distant and so, so sci fi SpaceX is IPOing this year, dude. Like, that feels tangible to me. And I think that that is going to make people like wake up to like the tam of space being like turn expressed in financial markets here on Earth.

A (67:15)

Big time. Yeah. I mean, they're aiming for a $1.5 trillion IPO. They're looking to raise $50 billion. This is the largest amount of money ever raised. This is the highest market cap of any IPO that will ever, that has ever launched in history. And the reasoning is, because it's going to power this next generation of, of expansion of innovation and manufacturing and productivity of the human earth or like on planet Earth, because for the first time ever, we're able to access this new marketplace. We're able to expand outwards among the stars and extract value from that. And there's a whole new layer of value that will be built on top of that. One of them is through the Internet. Rebuilding the Internet in space is pretty cool. Starlink has made a ton of money. And as they sign these deals with Apple and Samsung and the rumor is that the 18 Pro will get a chip that actually supports Starlink direct to cell. The whole world will start to become users of SpaceX and Starlink. And then after that they start to put more satellites into space. They start to create the data centers. They get a starship program going to the moon, they get a starship program going to Mars. It starts to become this really fun interplanetary adventure that does actually accrue value back to the main Earth. So the mission of Mars is a fun novelty. It is a cool human goal, but there is practical value being built and that's what you're seeing in Starlink and this unbelievably high valuation. The world is waking up to the sci fi future that actually is here. Like it's time. We haven't had a lot of change and progress in this physical world, but that is changing.

B (68:37)

Yeah. The number of say Starlink comes and blankets the Earth, which doesn't seem that far away. Seems like it's actually kind of already.

A (68:44)

Here and it's pretty much here.

B (68:46)

So you're telling me in the future there's going to be an iPhone model that connects to Starlink and that's where I get my data from?

A (68:53)

Yes, in the same way that it works right now with sos. So if you have an iPhone and you have no service, it is partnered with Global Star, I believe is a satellite provider where you can actually get a text message out through a satellite network. It takes a while. It. There's not a lot of data throughput. Starlink is going to do that, but at speeds that are comparable to LTE and 5G and that's.

B (69:13)

You have to be able to like. So I'm inside right now, so are you. There's a roof over my head. Will I be able to do. Will I be able to have service inside?

A (69:21)

It depends on the bands. I'm not entirely sure how that works. I know it could penetrate through some surfaces. I'm not sure what these Starlink V3 satellites are capable of or what the BEAST 4 satellites will be capable of. But the certainly if you are outside, most likely if you are not under brick roofs. And then I assume there is a future iteration of this where it will work even underground, which should be, or maybe not underground, but through basically any structure that you're going to be in that you would get normal cellular service.

B (69:47)

Okay. The we. We. I want to go backwards and trace over this a little bit because like you said, some things that I want to pick up on. We. We talked about Tesla. You talked about all of the Transportation like Uber might be under threat, like UPS, FedEx, any DHL, any, you know, physical logistics under like potentially under threat from a very hard competitor to compete with, which is Tesla and autonomous driving vehicles that don't, you don't need to pay a driver. You can charge them at the Tesla charging stations. And, and with, you know, with energy being cheap, like that's a really hard thing to compete with. And so when we talk about like winning capitalism, you what you ultimately see is like a lot, a lot of companies just can't compete with the scale of what some of these companies are going to produce. When we talked about Starlink and providing data to people, any service provider like Verizon, sprint, AT&T, sprint, so Sprintstead, sprint AT&T, like any other service provider in any other country across the world all kind of just get gobbled up by, by Starlink and then therefore SpaceX. And so like part of this, like you got to make sure that you place your bets right according to have like effective exposure to the future comes with like not buying companies that are going to get gobbled up. And so I kind of expect there to be like a kind of a graveyard of companies because some of these companies are going to get 1, 2, 3, maybe 4 Thanos gauntlet jewels of capitalism. And, and they just displace the long tail of companies in this world. That's my intuition.

A (71:33)

Yeah, it's really difficult to compete. And this sad example that we saw, or there's a few examples actually one of, one of them is the company Groq Groq which was just acquired by Nvidia. They were on their way to success. They did have a very clear chip architecture that was faster and more superior when it comes to training and inference than Nvidia gpu. But Nvidia just bought them up because it's more lucrative to absorb that than it is to create it to yourself because time is such a constraint here. It is a race against time. And the premium of losing out on that time is so high that it made Sense to spend $20 billion to acquire this company to further your initiative. A company like that can afford to do that. A company that isn't the single largest company in the world can't afford to spend $20 billion to acquire some IP. They're going to have a very difficult time competing with the companies that can and that it kind of grows across the board where even in the world of software, Perplexity is a very popular AI company. They built a browser, they put their entire company on betting on a browser. Just today, Google Chrome added all of the functionality of Perplexity, but better because it's Gemini into the Google Chrome browser, which has billions of users. And it's just, it's very difficult to compete with because they have such a strong moat. They have so much capital to defeat you that unless you are actually winning by creating net new value that is that can't be replaced, it's going to be very difficult to win. And in the world of software, it becomes almost impossible where any sort of algorithmic breakthrough, any sort of software product can now just be emulated by AI in a day. And the real war is going to be fought in the world of atoms outside, in the real world, because physical things are difficult to move and they take time to move. And that is where you can build and develop a monopoly. And that's where you're starting to see companies like Tesla and SpaceX building these unbelievably strong monopolies. Because I mean, like you mentioned earlier, the United States isn't. We haven't been manufacturing much. So the companies that figure out how to do this at scale and to do it on this country's earth instead of doing so and outsourcing it, are really stand at a huge advantage relative to the others that care.

B (73:33)

I want to just kind of quickly go through a lightning round of companies that maybe get some honorable mentions. What about Amazon? Is Amazon in this race?

A (73:41)

Amazon's totally in this race in a unique way. Going back to the physical world, they have to be among one of the companies that moves the most atoms out of any other company on earth. They ship a tremendous amount of packages, they understand logistics, they have delivery and supply chain. That is incredibly important. I could see a world in which Amazon becomes the logistics engine of the world, where they become responsible for a lot of the transportation of goods and services, perhaps using something like a cyber cab, because they're not going to be able to build their own. But they are the facilitator, the logistics layer. And they're starting to use robots in the factories currently. They have a lot of automation happening in these narrow use robots where they'll have these tiny robots that are only good at lifting pallets up and moving pellets around a warehouse. In the, in the currently human run supply chain that they have, there's a huge amount of inefficiencies from those humans. And by adding robots, by adding artificial intelligence into that logistics layer, you can remove a lot of those inefficiencies and turn that into Profit and margin. And again, the increasing capital they're going to have from this, the huge amount of infrastructure that they have from this is going to be a huge advantage for a company like Amazon because they have such a broad reach in the physical world.

B (74:51)

What about Microsoft?

A (74:52)

Microsoft's a tough one. Microsoft. The best thing Microsoft has going for it is the fact that it owns half of OpenAI. And that's a difficult, It's a, it's a difficult place to be. In fact, I see a world in which, I mean this is a crazy take, But Microsoft's and AI, they and OpenAI kind of need each other. Microsoft's struggling. We kind of roasted it a little before with Microsoft Office where I haven't opened up a Microsoft Doc or a, like an Excel spreadsheet in forever because Google has replaced it. And in fact, XAI is working on a company called Macro Hard, which is the inverse of Microsoft, with the thesis that any piece of SaaS like software as a service that you can run on your computer is just a matter of prompting the model in the right way to get your own local version of that hyper specific to what you want. So a company like Microsoft that competes on these services, in a way it falls into that trap of being extractionary, right? Like it's, it's kind of just selling services to people without generating a lot of new value. It's a difficult thing to continue. Should they not go with the OpenAI route, the abundance route, like actually create net new value? They're in a tricky spot and I don't know if I would include Microsoft in that. They have a huge amount of capital. The capital pillar they are very, very strong on. They need to win on some of the other pillars. And if they could do it, if they could turn things around, they have a very real chance. But like Google in 2024, they're just not really using that capital efficiently.

B (76:14)

What about Facebook Meta?

A (76:17)

This brings me so much sadness. I'm deeply saddened by Meta and by Zuck because they, they had the intelligence, they had the labor, they have a huge labor force, they had the capital and they are just spending it in what seems like all the wrong ways. I think Meta probably spent more money on hiring employees and acquiring that labor than any other company on earth and they really don't have much to show for it. And it makes me sad. Like Meta is named Meta because of the metaverse, but there is no such thing currently. And that pivot happened many years ago.

B (76:51)

And they had a 2021, 2022 pivot, right?

A (76:54)

Yeah. And like, where is, where's the Metaverse, bro? There's no Metaverse, but there's a ton of spending and a full company pivot towards that. And they haven't yet proven that they're capable of delivering on something other than an incredibly addictive algorithmic feed and an amazing advertising engine that could sell ads better than anyone else. But again, in this world, I'm not sure that is as important. And all of the AI products that they've released have kind of fallen flat. They were supposed to release three open source models to the public, one of them, the largest one being Behemoth, which they failed to even ship. And all of the times that you come across their AI, perhaps like on the Instagram app or on WhatsApp or on Facebook, it's normally kind of like Siri, where you avoid that button, you don't really want to engage, you accidentally.

B (77:38)

Trigger it and you're like, go away.

A (77:39)

And you're annoyed because it's falling into that trap of being extractive of the users instead of actually creating net new value. So they're in a really difficult spot. And we saw that with hardware too. Again, hardware is this incredibly difficult problem. And they released them at Ray Ban displays and the displays are mediocre and the demos weren't good and no one actually uses these things because it's not a good product. And until they're able to prove that they can ship good hardware and good software in this next paradigm of AI, so far they're just a sink for money. That is retiring many, many very talented software engineers without having anything to show for it. Ouch.

B (78:12)

Ouch. Maybe one way to articulate, I think what you just said is, is when the world decided that it got too deep in the Internet and it wanted to pivot from bits back into atoms, Meta went even further into the Internet. And that was the incorrect trend for Meta's strategy.

A (78:33)

Well, perhaps it's not totally incorrect. Like, Meta reported earnings this week. Their stock is up big time. In fact, the stock is performing very well over the last six to 12 months. So people are liking what they're seeing. It's generating revenue, it's doing what they do best, it's selling ads really well. It's getting monthly users to be very like, locked into their platforms, but there is nothing net additive.

B (78:53)

And when you get into doing anything new, they're great, they're fantastically profitable. But are they going to def. Build and define the future? Not sure.

A (79:03)

No. And to your earlier point, like, they're still a great company, they're probably a great investment but they're not going to cross that threshold unless they make some seriously large changes very soon.

B (79:11)

Right. What about Apple?

A (79:13)

Oh, these are pulling out my heartstrings. Apple again these are just like the.

B (79:18)

Biggest companies and so I figured like by market cap it's gotta be the highest market cap. Companies that have to be almost, almost by definition the companies that are in.

A (79:26)

The race, they were in the race. They were producing the most amazing products ever. They had the iPhone, they had the ipod, they had the MacBook, they had the Mac, they had the M series chips, they have Vision Pro. These were all innovative new products. Even the airpods are amazing. But they're failing to build. On top of that in the world of AI they had an opportunity to turn the iPhone, which is the most popular consumer device like ever into a supercharged version, all knowing version, kind of what Google just did but for their own in house stack. And they failed to do that with Apple intelligence. And in the shadow of failing to do that they still couldn't figure it out in the following year. So they've just decided to partner with Google and Gemini to run Google's models on their hardware. And they haven't proven recently that they're able to actually create more valuable products in the future. What we're seeing over the last five, maybe even 10 years is a pivot towards services, towards things like Apple TV, towards iCloud, towards subscriptions which again they're extractive, they're profit generating engines that the market loves. But they're not creating net new value in this world of abundance. They're not creating new products that unlock new use cases and new potential and new productivity. It's very, it's a zero sum thing and that is very difficult when you're competing against a company like Google, like Tesla who is building bad ass engineering. They're creating AI at scale that is very impressive. Right on the frontier. It's, it's difficult to compete and they don't have the leadership right now to do that.

B (80:50)

Yeah, it seems like some of these companies like again not to talk shit about Apple but just like they're, they're profitable and they're increasing, they're doing their best to maximize their margins and great businesses. That's it. Yeah, that's, it's a great business, it's a great trad business but in terms of building this like post capitalism, post scarcity world of abundance where labor is free, energy is free, intelligence is free and then Therefore, you don't need capital anymore. Like, if that's the subject matter of this podcast, which it is, it's just like they're doing something else, which is just being a profitable business, which is great for them, but they're not going to own the future.

A (81:26)

Yeah, in a way, everyone's kind of rolling down the same highway, and they were all going at the same speed. And then some companies decided to install, like, thrusters and jet packs on the back of them to move themselves faster, while the others are just happy just rolling down the road.

B (81:37)

They're doing great.

A (81:38)

Exactly. And they're great companies. Apple's a great company. Same with Meta. They're both fantastic businesses and that's why they grew so large. But their failure to deploy these resources in this new world of AI, intelligence, energy, labor, they're going to have a really difficult time scaling. Once we do cross that threshold, once we do get the general intelligence and this physically embodied AI systems at scale.

B (82:00)

I think we talked about all the big ones. I don't know if there's anyone out there. It's like, I don't really care to talk. I'm looking at the asset market cap. I don't really care about Saudi arco. That's oil. I don't care about Walmart or Berkshire or Hathaway. I think we kind of talked about all of them. If you had to place your bets, I feel like Google's a very strong contender.

A (82:17)

Very strong.

B (82:18)

I really like the synergy between Tesla, SpaceX and Xai. I don't know about anyone else.

A (82:27)

Those are the two favorites. And of those, even the Tesla SpaceX Xai Synergy is really, it can't be overstated how powerful that can become. It really is civilizational scale success, because when you think of the previous track record of building these very difficult things at scale. Take Xai, for example. Xai is less than three years old and they're sitting at the frontier of every single benchmark that exists in the world of AI and no time at all. And Jensen's going on podcasts, talking about how they built a data center in 22 days that would have taken a normal company 18 months. And that rate of acceleration is due to the leadership and the engineering talent that they have and that applied to the physical world through Tesla and cars and solar panels and batteries for storage of this energy. And then applied to the outer space with SpaceX, with transportation to orbit and the Starlink satellite constellation, they have this full stack where there is no asset required that they don't have. Those are the four pillars. They have the workforce and labor through Optimus, they have the capital through all this fundraising that they're doing and all of the products that they're shipping. They have the intelligence because they have more data and they have higher end AI models than anyone else. And they have the energy because they have solar, they have space, they have batteries that they're producing. They own all four of these. And there's no other company or convergence of companies in the world that currently has these four pillars in a like chokehold that Tesla does. And it's moving towards progressing in these four pillars faster than Tesla. It's just, it's not happening. And while Google stands to perhaps win on the intelligence pillar, Tesla and SpaceX and Xai have a chance to win on all four simultaneously. And that's very much what they're doing.

B (84:15)

Did we accidentally just make a Tesla bull case episode?

A (84:18)

I think we're just being honest here. Like just when you reason through the pillars that we described and you think about who is actually in the lead for each of these and how, based on their previous track record, based on what they're currently doing, and based on what they're saying they're going to do in the future, there really is no companies better than, than those. I mean four. It's tough to compete. It's really, it's a different ballgame. And I think a lot of these companies have grown to a scale that makes it very difficult to pivot without disappointing the right people. And some companies might not even be able to like, Google was not run by its founders and it was struggling a lot because of it. But when Sergey Brin came back, the founder who owns half of the company with Larry Page, they were able to make decisions that were risky enough that other CEOs who are liable to the shareholders, liable to the board of directors are not able to make. They could assume levels of risk that other companies won't and they can actually enforce their will on a company in a way that's very difficult for a lot of these companies that have existed peacefully, happily and very wealthily for the last 20 years are just not able to do.

B (85:22)

Yeah, I see it. And there's also has to be the benefit of, you know, I know he's a very controversial figure, but the one thing that you can say confidently about Elon Musk is that he is an incredible operator. He is potentially the best operator that we have ever seen walk this, walk this earth. He's just got the track record to prove it.

A (85:41)

And it's funny, I was watching, there's a great Peter Thiel interview that I was watching earlier today because he worked with elon closely at PayPal and him and David Sacks were writing a book about the PayPal mafia. And one of the chapters was about Elon, and it was about how he doesn't understand risk because he would always take so much risk and it didn't make sense. And he said, well, if SpaceX or Tesla had independently worked out, you could say that it was lucky. But when both of those things work out, both of these impossible missions work out at the scale that they have, there's something different in play. And it's really hard to overstate one, how difficult they are and two, how impressive the growth rates of those have been. Since they've succeeded, there is no slowing down the momentum. In fact, it's just moving faster because they're all converging on each other in terms of which resources the other company needs.

B (86:23)

Josh, I think this helps answer my question. I don't want to say that Tesla is the answer because with one corollary, maybe Tesla wins the race. And so it is the answer there. But the original question is how do I allocate capital in my portfolio to have exposure to the future? And the market is currently pricing Tesla at a specific valuation. The market's currently pricing Google at a specific valuation. I think the idea of the framework of like, which of these companies can access capital, energy, labor and intelligence for free is a good framework. And the market is pricing these companies against that framework because it seems to be in 2026, that end game of like the event horizon of having all four of those gauntlet jewels, the intelligence, energy, capital, labor, that's, I think that's the benchmark. That's how I'm going to like look at the market going forward. And the market is pricing Tesla at like $1.3 trillion on this race and it's pricing Google 4point something trillion dollars along this race. And so maybe, maybe I don't want listeners to listen to this and walk away saying like, dump it all in Tesla because the market's already priced that in. But I think this is the framework that I think is useful to me to understand how to invest to get exposure to the right outcome of the future.

A (87:47)

Yeah, it's like when you're evaluating companies and you look at their roadmap and you look at their accomplishments to date, are they likely to continue to make great products that are better than the ones today, that add more value to the world. And if the answer is yes, and if the answer is they have proven that they're capable of doing it, then there's a strong case to be made that they'll be more valuable tomorrow than they are today. And that when applied to these four pillars in particular, has an uncapped upside. So there's a lot of amazing companies that are going to do very, very well through this. A lot are going to get acquired, some are going to die. But the ones that really ascend, the ones that create an uncapped market cap, like the. The perceived ceiling right now is what, four and a half trillion dollars? But the ones that are able to break through the glass and actually create net new value for the world to increase the GDP to offset a lot of the debt that we're printing, those are going to be the ones that accelerate in either one of these four pillars or all these four pillars, because those are the ones that truly matter. As we enter a world of energy abundance, labor abundance, just abundance for everything, the deflated costs of it are going to really make a big difference on the world. And those four pillars are the ones definitely worth looking into.

B (88:53)

Well, Josh, I feel like this question is answered. I appreciate all of your help helping me get there, and thank you for coming on the show today.

A (89:00)

My pleasure. Thank you so much for having me. I really had a good time.

B (89:02)

Bankless nation. You guys know what to do. Crypto is risky. You can lose what you put in, but nonetheless, we are headed west. The future is abundant, and I would like to invest in the companies that make that future abundant. And so that is why we are here today. It's not for everyone, but we're glad you're with us on the bankless journey. Thanks a lot.

A (89:24)

Sa.