The Team House - AI: Boom or Doom? | EYES ON GEOPOLITICS

Episode Date: August 20, 2026

Anthony Vinci joins us to break down the rapidly evolving AI landscape, from China’s growing challenge and the risks of frontier models to surveillance, national security, and the race to control the technology. We also get into the massive spending behind the AI boom, whether current valuations are sustainable, and what happens if the bubble eventually bursts.Anthony's AI company: https://www.vico.io/Anthony's Book:⬇️https://a.co/d/04QQ9KQ7Support the show on Patreon:⬇️https://www.patreon.com/TheTeamHouseFind Jon Hackett here:⬇️Jon's Twitter:https://x.com/jonathanhackettJon's LinkedIn:https://www.linkedin.com/in/thejonathanhackettJon's books:https://www.amazon.com/stores/author/B0C5L659N5?ccs_id=e11a2062-f8d3-498e-bfd7-7d2f3869caf6Linkedin: https://www.linkedin.com/in/thejonathanhackettTwitter: https://x.com/jonathanhackett"Karl Casey @ White Bat Audio"00:00 - Start01:15 - Why AI and China Matter03:00 - The Three Types of AI That Could Reshape the World05:20 - How Chinese AI Could Be Used Against Americans07:18 - Open-Weight Models vs. Open Source09:51 - How Dangerous Should Frontier AI Be Allowed to Become?12:54 - Should U.S. Companies Be Allowed to Use DeepSeek?14:16 - AI Surveillance and the Death of Traditional Cover18:10 - How AI Could Transform Intelligence and Targeting20:03 - Why American AI Is So Expensive22:27 - Should Chinese AI Models Be Banned in the U.S.?24:46 - Building an American AI “Walled Garden”29:35 - What Makes Frontier Models So Dangerous?32:06 - Is AI the New Nuclear Revolution?35:43 - Is the AI Danger Narrative Partly Marketing Hype?37:58 - The Trillion-Dollar AI CapEx Question42:13 - What Happens If the AI Bubble Bursts?44:15 - Will AI Companies Eventually Be Nationalized?46:55 - AI, the Pentagon and the Fourth Amendment54:33 - If You Ran U.S. AI Policy, What Would You Do?56:25 - Are AI Companies Overvalued?59:24 - Can the Cost of AI Compute Come Down?1:05:40 - Anthony Vinci on Vico and Predicting the Future1:08:34 - Is AI the Next Cisco Bubble?1:12:48 - Final ThoughtsBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-team-house--5960890/support.

Look, I'd rather live in a United States where, like, we have control over the technology and information that affects Americans. And when you have tech, like, that used to be fine for basically a century, because America made the best technology and most of the technology. Now, we're entering a world where China makes a lot of technology and in some cases may make better technology. But they don't want to abide by our use. our constitution, our rules around this. So I would just say, fine. Like, you can do whatever you want in your country, but we are not going to use your technology then. Hey, everybody.

Welcome to another episode of Aizond, Jail Politics. I'm here today with Jonathan Hackett. And our guest is Anthony Vinci. He's the author of the Fourth Intelligence Revolution, the future of espionage and the Battle of Save America. He's got a pretty amazing resume. He previously served as a future. as the first CTO and associate director of capabilities at the National Geospatial Intelligence Agency. Following earlier work as an intelligence officer in Iraq, Africa, and Asia, you could actually watch an episode with Anthony on the team house that we did probably a good six months ago now.

Great episode. Check that out. I'll put a link in the description. You can check it out. I also put a link in the description for his book. He is now the co-founder and CEO of Vico, an AI company focused on decision making and finance and national security. and is an adjunct senior fellow at the Center for New American Security. And to boot, he holds his Ph.D. in international relations from the London School of Economics. So I try to get somebody here that's on the level of smart as Jonathan Hackett is, because Jonathan's got a pretty good resume too. And I think I did a pretty good job with you, Anthony. So thanks for joining us today.

Yeah, man. Thanks for having me. I want this whole talk to be about what's going on with AI. me and Jonathan have been talking about this for like a couple months, like putting together a show and trying to find a guest that can like, you know, give us the lay of the land of what's going on. And I've joked with Jonathan, I think I joked with you on an email too about saying like this literally could be a three-hour conversation

because it's like there's just so many rabbit holes we can go down. Full disclosure, I am more on the bearish side of AI, particularly when it comes to like just all the CAPEX that's going on. And like, you know, where's where's it really going the cow expensive the compute is compared to like how you know enterprises are using them like there doesn't really look like there's a big uh at least for the frontier models it doesn't look like there's a big uh profit center right now um but anyway let's just get into it oh i mean i don't know how you guys want to play it jonathan i please like let's just you know improv this basically do we want to explain like what the frontier models mean like Should we go more of a basic route for like the layman? I'm a layman obviously too, but I just read this insensibly.

I think it's helpful to have like a more general question of, okay. Why should people care about the crossover question of China and AI? Because there's the China national security threat that's existed for a long time, especially international security strategy all the way back to 1987 when the first one came out. Now AI has entered the chat. And the question for the American listener is why should they care about that? Yeah, I love it.

Let's go. because we can go in any direction here. So Anthony, what are you tracking basically right now with AI? I mean, I know I sent you over that Financial Times article. And that does seem like the big scary. Yeah. Well, look, China AI, I think is, that's the question. That's like the generational level question because I think about it like this.

AI is not like software. AI does what people do, right? and it communicates information to you. It doesn't just show you something, but you interact with it, right? So anything, when you get on Claude, you get on chat GPT, and you ask it a question, it can ask you questions. You can continue to ask it questions. And the thing is that it can persuade you to do things, right?

Like it can lean you in a direction. That's different than anything we've had before. Only people were able to do that previously. So that's one thing. The second thing is that AI, that's kind of LMs like AI you talk to. There's another form of AI that you're using for autonomous vehicles that can drive Waymo cars around or can fly drones around. That's also super important. There's a third kind of AI that I think is you were going to see more and more of.

And it's kind of what I do in my company at VECO, which is using AI to help run businesses or even to help run the military. It's making strategic choices. It's allowing you to play through lots of decisions, lots of decisions, right? Those three kinds of AI. That's kind of how the world works. You have people talking to people now talking to AI. You have AI that's able to drive cars and other vehicles. and do you have a system that can run companies?

Now, these are the things that we obviously are competing with China around. And the question's going to be, are we going to use Chinese software or AI systems to do these things? Or are we going to use American systems? And then what about our allies or just third-party countries that are neither aligned with the U.S. nor China kind of sit in the middle? and what are they going to use? And we've seen this situation before with Huawei, with telecommunications equipment, where the question became, are you going to have your telecommunication system set up on Western equipment from Erickson or something? Are you going to have it set up on Chinese equipment?

The downside risk there was that Chinese equipment, they can spy on it and steal all of your data. It's completely unsecure. Well, we have the same situation with China right now is that if, If you use a Chinese AI system, they can spy on it. They can access your data. But it's even worse now because they could do two other things. One, in theory, they could use that AI system to control what you're using it for. So if you're using a piece of AI to run an autonomous vehicle, in theory, they might be able

to control that autonomous vehicle. That could be really problematic in war, for example. But the even more nefarious possibility is that Chinese AI, remember the part where you can talk to it, where you use chat GPT, where you ask it a question, say, about how to vote in this coming midterm. If it's Chinese AI system, they can mount an information attack against you and can actually persuade you to do something. So those are like really serious consequences for like the average everyday American citizen. Like, do you really want your vote, for example, in the midterm to be biased in some way because of your interaction with the Chinese system? Do you really want this Waymo car that you're driving in to potentially be controlled by China and say in a state of war to be used against you? Maybe it, I don't know, runs people over or something.

Or American military equipment to be harmed by a Chinese AI system. And worst case scenario, if you're running your business and you're using AI to do this or the government is being run by AI, do you really want it to be compromised by Chinese AI system. And I think these are like really serious questions that we have to address. And I think also, too, I was actually reading an article recently, I think this week about open weight models that China is kind of pioneering and getting out there a lot of and people are seeing them. They're lower costs and all these. There are all kinds of benefits and advantages on one ledger. and as I'm reading more about what open weight actually means, my first thought before I dug into this was that open weight was the same as open source, and I've learned that that's

not true. Can you talk a little bit about why that's problematic? Yeah, open weight means you're getting the open source means it's a piece of software that you can use and you can modify and you can do whatever you want with and build on. So like Linux, for example. Open weight means that they have provided the model, but not the underlying data in the model. So it does mean that you can use it now and you can build that, you can build an app, say, on top of it, but you don't actually know the data that went into training it. You don't know exactly how it's going to respond.

So the danger is that it could respond in a way that is biased. So kind of notoriously, the Chinese Openweight models are biased. bias towards the Chinese Communist Party. Like if you ask a deep seek model or Kimi or choose your Chinese open weight model, a question about Tiananmen Square, it's going to give you the party line, right? It's going to say what the CCP wants you to hear. And that's problematic on its own. And what, but really what open weight and open source mean is that it's free.

And so what China's done is they've made these free. models. Deepseek and a couple of other companies have gone out and done this. And so what's happening is they're essentially giving like this low cost solution that US or other country companies can build on top of. And so it's kind of similar to the Huawei thing again, right? Huawei was able to produce routers and other telecommunications equipment at a fraction of the cost of Western equipment. So people started using that kind of equipment. And these, the, systems were compromised in a way or could be compromised by by Chinese intelligence and so forth. Well, same thing with AI. They're sort of giving away these open source models that are

effectively free so that people will build their own software and apps and so forth on top of them, but they're compromised. And actually that brings up a good point. I was working somewhere over the summer where we got Fable from Anthropic for like two days and then the government shut it down. And there was this kind of disruptive moment where the U.S. government was trying to, the U.S. government was trying to figure out how do we regulate this? Do we put export controls on it? How dangerous is it? And all these questions. But at the same time, China is looking at this in the opposite way. They're trying to get as much access to people as possible, whereas the U.S. seems to be trying to be more careful. What's kind of the right way to balance these two competing philosophies? Yeah. So there's a downside to letting AI models out, right, which is that they can be used to do. dangerous things, right? You could take an AI model and in the case of fable and mythos, the Claude models, that they could be used to hack, to perform an offensive cyber attack.

And that could be really dangerous. Imagine you just sort of let everybody in the world have that and now these criminals, criminal hackers were able to use the stuff and then they can go and hack into banks or into healthcare systems and so forth. Could be super dangerous. So there is a debate just on that. Like when and how should we release these models? And it gets worse, by the way, than just hacking. As these models get more powerful, it's possible you could use them to create like a bio weapon, right? That a person with little to know biological science experience could actually create a bioweapon by following the instructions like you would with a cooking recipe from an AI system.

And that's like, that's like terrifying to even think about. So we want to have some control. China like does have some control on, even on the, the open weight models, right? The CCP has established guidelines and controls to those companies like the deep seek, for example, around information that they want certain information about Tiananmen Square or the Uyghurs, which is a minority group that's, that's persecuted in China. They want to control that information. they are putting in those controls. But then these open weight models are being released to everybody, and they don't have, there's no way for the U.S. government to put its own controls,

like, say, around cybersecurity issues. Now, this wasn't a problem until recently because the U.S. models like Claude and ChatGPT and GROC and so forth were by far the most powerful models and could do the most powerful things. And these open weight models were, you know, a generation or two generation. behind and so they weren't as dangerous. But now they're sort of catching up. And as they catch up, they might get as dangerous as a Claude model for hacking and for

other purposes. And there's no way for the U.S. government to regulate it or control it in any way. And in theory, China might let people, you know, allow a model out that could be used for cyber hacking. What do you guys take? What's your take on, you know, Microsoft announced maybe a few weeks ago? Also, Microsoft being a big investor into Open AI, that they're going to start using deep seek, or at least look into using deep seek for some of their enterprise stuff.

I mean, that's got to ring alarm bells for everybody, though? Yeah. I mean, look, my personal take is that just like Huawei, it should effectively be made illegal or at least very problematic for a U.S. business to use these things, because for all the reasons I mentioned, like these things, they're compromised in that sense. And there's a danger in that. They're already large American companies using Chinese Openweight models. Airbnb uses them.

There's a few other big ones. And then there's lots of small startups that are using them. Microsoft saying they're going to use it is not great. I suspect that really they would be using it for something that they consider to be low security risk, right? And that's fine. But then who's making that call about what's low security risk, right? And we are in effect creating the same situation as Huawei, where we're going to kind of build up their open weight model companies over time. And then we won't be able to compete.

You mentioned something really interesting. You said like Airbnb and these smaller companies are using deep seek. You know, I used to teach at our human intelligence collection course. And we taught about ubiquitous technical surveillance and how to do things under a UTS threat and so on. That was before AI. And now I'm very curious about how it's not just a vector. I mean, in ubiquitous technical surveillance, you have multiple vectors that overlap that make the thing a threat or a problem for you. And it seems that it goes beyond the vector problem when you're using AI.

Like let's say you're booking on Airbnb and there's certain behavioral patterns that you, the user, use on Airbnb that are almost exactly. the same behaviors or exactly the same behaviors when you're undercover under a different persona on some other platform. And AI is able to see that and correlate you immediately way faster than a human analyst could. I already mentioned, you know, what would you say to the average American, but I'm curious also to the average case officer who might be listening because I know there are some who do listen to the show. What would you kind of caution them on? Yeah. I mean, well, look, even for the average American, by the way, I don't think the average American wants a Chinese company or a Chinese security service or the Chinese government

to know what they're doing and to be able to match the records from Airbnb to other things in their life. We don't want our government doing that, right? Like, your average American like me is like at least a little bit libertarian leading in that sense. We don't want our government to spy on us. Why would we want the Chinese government to spy on us, right?

So I think everybody. But yeah, for case officers, look, I was a case officer, you know, And by the time I stopped doing that, the UTS issue is just starting, right? And so I only really saw a little bit of it. And I can't imagine starting from scratch today what it might must be like. And the, you know, even without AI, you can match people's patterns, right? Just literally like old school big data analytics, I crunch enough data about you. I can detect patterns.

the AI makes it easier and more ubiquitous, right? Like, I don't even need to, you know, I can do it. Like that example you brought up is a great example, actually. Like my habits, it might not, by the way, even be what I'm doing on Airbnb. It could even be like the way I move my mouse or the way I type, right? There are signatures that are everybody has. these patterns can be taken from one place and then and then apply to another so as a case officer you're trying to act and cover somewhere and you know even if you even if you used a false

name for everything you did in work and in fact even if you used a false name for everything you did in your commercial life well your pattern still might be there right like maybe you're using your wife's account to log into Airbnb, but you're the one on the mouse and making the decisions, it would still be able to recognize these patterns. So it becomes nearly impossible to kind of like keep yourself out of there. Now, I actually wrote a whole chapter about this in my book because like I think where it goes to be a case officer, I think you just have to sort of assume that anything, any pattern is or could be tracked. and then you, I think we will enter a world where you just have to sort of live in pattern

and what it is to kind of be in cover and so forth completely changes. Like there's no more dock swapping and all that stuff we saw in spy movies. Like that's over. And like now you just have to sort of live your life as that person, like kind of closer to what it was like to be a source back in the day. Hello, everyone. If you're hearing this, you are not a member of the Patreon. you can get your hands on ad-free episodes that come out early and you can ask us questions.

Maybe we'll answer them. You can also watch the Teamhouse podcast completely ad-free and early. And you can also watch it live as we interview our guests. And it's the best way to support the channel. So if you can, if you're open to it, you can go to patreon.com slash the team house. That link is in the description. We appreciate the supporters and we hope you would consider being one. So it's patreon.com slash the team house.

Thanks, guys. Yeah, actually, I was reading about when the strikes were going on February 28th and forward in Iran at the very beginning of the war, how Israel used some security cameras and some UTS access they had inside of Iran to better triangulate targets and then predict follow-on targets very rapidly, which is fantastic. But then the question is, that's with the AI that we have right now. What happens when it's an order of magnitude, either more intelligent or faster or in the wrong hands, you know, how do we develop safeguards for that in a military context?

Yeah, or what happens if it's applied to us here, right? Where every, you know, every factory in America has some electronic device in it that might be, you know, could be compromised. And China has an AI system that's able to sort of assess and analyze all of those factories, all the people working on them, and then do something. about it. It could be, you're right, it could be using that for targeting information, right? It could be they can figure out just by these assessment features, you know, which ones are building key, you know, components in a missile. It also could be, well, why not just target the people

working at the factories non-kinetic means, right? Like, why not use an information attack against, you know, sometimes in these factories, for example, you have like one or two guys who are the key guy, like they know how to do everything. Why don't I just target that guy? Why don't I implant some criminal information on that guy's computer and then put him in prison? And now that factory is 50% as effective because we've lost that guy, right? Like there's all sorts of things that could be done if you, you know, if you're sneaky thinker with this stuff.

Anthony, I have a question and going back a little bit to, you know, being worried about American companies and American startups using the Chinese models that are some places I've read, it's like one third cheaper and stuff like that. How do we stop? And there was like,

how do we stop basically it being so expensive for American companies to use frontier models? Yeah. Yeah. Yeah. The, the, first of all,

I would start to question. some of the like costs differences, right? Just like like with anything open source, like the actual cost to buy it versus like the cost to implement it might be totally different. But let's just assume for a minute. I think I think it is true. It is going to be it is going to be cheaper. I think we need basically cheaper models. And I have this idea, which I'll throw out right here, which is the Trump administration has made for its own reasons has said to Anthropic that there's a problem, they don't want it to be used in Department of War. We are where we are. Well, I think at some point we should make a deal

with Anthropic, get them back into the Department of War. But I think we should say in exchange, one of the things that we want is you should make an open source model. Or, or, or just like a really cheap model that's really good, right? There are ways that we can, you know, work with these companies and make deals so that it's good for the nation and it's good for the government, it's good for the company. And I think that's how we're going to have to do it. And I see a little bit of that happening. Like if you sort of read between the lines after all this stuff came out about Chinese Openweight models, and I can assure you as somebody sitting inside the Washington, in D.C. Beltway right now that people here read those articles and got really, really concerned

about it, you could see a few of these companies started offering their models for cheaper. So, like, they're not dumb. They're listening. And I just think that that's how we're going to have to deal with this. I also think that, frankly, like I said, I think that the U.S. government should make it illegal, in fact, to use Chinese models. That you just cannot use them here, that they are compromised, their security threats for cybersecurity and various things, their informational threats to the American people, and we should just not be able to use them. And, you know, we could use them for research purposes. And if you're an individual, I don't think we should be telling individuals what they can and cannot use. But if you're a

business and you want to sell a product, you should not be able to use it. And we've done this before with Huawei, where we have effectively gone to American telecom operators and been like, no, like, we're done, not here. And I think we need to do the same thing with open source models. We actually did something really similar with Huawei, with our foreign partners too. I remember I was overseas and working in the embassies. And during the Trump won administration. And there was a huge push throughout Europe and other partners as well to, hey, please abandon Huawei. Please use US technology. We'll create incentives for you to do that. But it also requires buy-in from the partner because they do lose a little bit. It costs them more money to

adopt this, despite the other non-monetary incentives that the U.S. can offer them. What do you think about those kind of incentives for AI? Agreed. I'd run the exact same play. I would literally send out, you know, U.S. Department of Commerce and U.S. Department of State folks to go to these countries and been like, you should not use this stuff. And we have other levers, by the way. There's carrots and sticks that can be applied. But part of that would also be, hey, well, you know, here we have some less expensive, you know, here are some less expensive models that are American that you can use. And I think we work with the U.S. companies. By the way, it's, it's in the interest of these big companies like

Anthropic and Open AI and XAI and so forth, right, to to offer these models for less money. it's a business issue for them too because if all of these startups in the U.S. and Europe or wherever start using Chinese open weight models now they're and those companies, assumedly over time will get bigger and bigger now they're not going to be customers of anthropic and open AI and so forth. So those companies are incentivized as well and like we just need to get everybody on the same page. It actually reminds me a lot of when the iPhone first came out. I think it was 2007 when I had the very first model. And there was no app store at the time.

And you could just jailbreak your phone and get all these apps on your phone. And then Apple saw that and they were like, hold on a minute. This is our device. And they came up with the concept of the walled garden where in order to play on an Apple device, you had to be registered on an Apple device and all these special safeguards. And I wonder if there's like some way to do that with AI, at least in the United States, like you were mentioning with commerce, there might be some way to create that wall to garden where the incentives inside the wall are much higher than outside the wall.

But you do have to exchange some. something of your sovereignty a little bit to be able to play inside there. Yeah. I mean, these companies, I suspect over time will naturally create wild gardens, like a great way to make money. But you're right. I mean, in a sense, we did this with foreign governments where we said, you know, I remember that time period in Trump one where it's like, okay, well, if you want to have Huawei

equipment on your system, we're not going to share any classified information with you. So if you want to play in our Waldgarden, then you've got to go out and you've got to put in like real routers and so forth because we're not going to lose our information. And it could be the same. You could imagine it in terms of other systems like banking systems and other commercial systems and saying, that's great. You're using an open source model. I guess we can't legally stop you from doing it. But you don't get to play in Swift. you don't get to play in like the banking system because we're not going to accept the additional risk of you using apps that were developed by the by a Chinese system that might be a way to do it.

I'm also with you too. Like I'm a less regulations guy, but I also look at especially in the international community when you have like in the international relations theory of how governments are black boxes and so on. How do you regulate these states? Maybe regulations wrong. Maybe there's some other way at that higher level where an individual company alone cannot. be the one on the frontier changing things for the good. You can't depend on them to do that. How can states jump in there besides the United States? Because it has to be all nations, basically. This is a global question. How can we create incentives for states to monitor or

keep safe this development? Yeah, this is like we're in this sort of weird new world, right, where like states almost now have to think like companies and vice versa. Right? These like Anthropic is or or any hyperscaler, right, like Google, almost has to act like a state and deal with state threats. And at the same time, our state, the government is now thinking in terms of these like commercial motivations. And there's no like I did a PhD in international relations. And this when I did my PhD 20 years ago, 20 something year, like none of this existed. there's no theory behind this. There's no like playbook to go by.

And so everybody's winging it. And I think like Trump one, Biden, now Trump two, they've all sort of tried to muddle through of how do you actually do this? And it does seem to be like there's some hard edged level where the government goes and says, U.S. government goes and says, you must do this. Like we are not going to share classified information with you unless you fix this. So there is like a, you know, hard edge old school power level. Then there's like this sort of middle kind of like softer edged power, like incentive structures.

Like, hey, we'll subsidize some of what we're doing. Or, hey, you know, we see you want to refinance your, you know, your World Bank debt or, you know, some, you know, you want something. You want some diplomatic action from us. okay well like now you know Huawei is on the table or AI is on the table right so we're going to come up with like a negotiation that you get what you want we'll get what we want and then there's like this commercial level where these companies I think are in the US they're being regulated and they want to play nice with the government too and where you know the government can kind of say look look we we don't want to regulate your business here, but we need a deal. And part of that deal is we think you should offer to these

allies a lower cost version of what you're doing, for example. So there's like a negotiation with the companies as well. I think there's like those are sort of the levels. And this is what now, you know, a national security advisor or president's chief of staff has to kind of like, you know, muddle through. And earlier in the show, Dee had asked about frontier models. I'm curious, how do those fit into this conversation we're having here because it seems that frontier means that it's changing, you know, by the minute. How do we how do we deal with that? Yeah, there's like this added danger in essence of the frontier models is that they're so capable, right? Like if you use fable or something, it's so capable that it can do things that are inherently dangerous.

And there's this question of the one, you sort of, it seems like kind of have to inoculate yourself, like that was sort of what was going on with mythos, and they were sort of like, okay, let's release this to only a few people, some big companies and the government, so they can kind of inoculate the cybersecurity systems so that they don't immediately get hacked, right? So that you have to sort of do that. And then you also have to control them, lock them down at some level. And that was also what happened with, um, with Fable, right?

It got released. Like you said, it was released for like two days. Trump administration saw that like, wait, people are using this in a bad way. You need to get that back out, fix it before you send it out. So you have to like lock them down a little bit. And that, like, I think that that is the future of these things. I think these models are so dangerous. It'd be like, imagine if, you know, when we first,

developed, you know, the American car industry in the 50s, and we had nuclear power plants on these things. And it's like some people figured out how to blow up these cars and blow up a city block. You'd be like, wait, wait, wait, you can't sell it like that. Right. It's sort of like, it's like we've created these products that are truly dangerous. And for better or worse, we regulate firearms and things like this as well for like the same reason, like they're dangerous. And so I think we're going to have to do it with AI. And then you come up with the question, well, then what happens if some other country offers a product that is non-regulated, like DeepSeek is giving these open weight models? Well, you know, if you ask me, you're selling a product in America.

It should be regulated like any other American product, even if you're giving it away for free. Like you still have to go through the same, you know, the same process. Yeah, and actually the nuclear analogy, I've been thinking about this too because in the 20s and 30s when nuclear technology generally was being discovered, essentially, there was the weaponization of it, but there was also the innovation of it. And, you know, one leads to potentially unlimited energy with fusion reaction and one leads to the destruction of the human race and the entire planet. But when you're first starting out, you know, splitting that first atom, that's not really what's on your mind. Instead, you're just fascinated by this new development and how far and positive it could go. And there's a book called Irrational Exuberance that really talks about this in the market where people just have this idealistic, rosy-eyed view of everything in the future that they're touching. And it actually doesn't work out that way usually.

How far do you think the gap is between what will probably happen versus this irrational exuberance about how AI will change everything for the better? Yeah. I mean, I'm a bit of an optimist, pessimist in one, right? Like I believe, I just think about in terms of the optimism, like, clearly AI is going to create and do amazing things, right? We're going to use it for medicine and it's going to make better medicine. We're going to use it just literally to make companies in the government more efficient, which will save us all sorts of money, right? Like, they're like wonderful things that are going to happen. It's also going to, you know, it's also going to be really, really.

bad, right? Like people are could hack into things, people might make bio weapons. It's probably going to put all sorts of people out of work, right? And so it's like any other technology. It's like saying the internet. The internet was great and people got to communicate and we got all sorts of memes and fun stuff out of it, but also at the same time we got cyber hacking and we got cyberbullying and like all of these bad things. So I think it will be the same. And the, I think the question we're going to face is how do we control something like AI? And like even the internet, which can seem pretty uncontrolled, like does have some controls, right? Like there are some minimal controls. We usually go through corporations to make those controls like the the actual

laws governing are pretty weak. But historically, we've done this again and again. In Japan, for 200 years, the Japanese made firearms illegal. And, you know, think of that. Like, for 200 years, they had the technology. They fought wars with firearms. Not a lot of people realize this, but like, samurai's were fighting with, with rifles. And then, and then basically this one, you know, samurai leader won, Tokugawa, and he said, that's it.

Like, we're not using firearms. And you can only use them for hunting. That's all they used them for, was, like, like hunting for 200 years. So it can be done. Societies can control technologies or think of like the printing press. Like there's been all sorts of attempts. Sometimes you try to control technologies and it doesn't work. Right. We used to send copy machines to the Soviet Union to like undermine, you know, the Soviet government because we wanted people to pass around secret information. Not secret, like information they didn't want passed around like political information.

So I think we're going to, you know, we're sort of entering a period of history in America in particular where we're going to have to figure out how to control this technology before, you know, the downside outweighs the good side. Anthony, I got a question. What do you make of the people that are saying that all the talk about mythos and fable and then I think OpenAI came out with their version in terms of saying, oh, yeah, it's very dangerous. That being all a marketing kind of hype thing to keep juicing. their valuations? I mean, if you ask me personally, like, I think probably both things are true. Like, that it is absolutely a marketing hype thing. The timing was not accidental on the release of, you know, the mythos model to, you know,

as Anthropic was going through some stressful times with the government, to remind the government that this was like a really powerful technology and they wanted access to it, right? And then it wasn't accidental that ChatShe, you know, that Open AI released its model that did the same thing not too long afterwards to remind everybody, hey, we also have a powerful model, right? Like, I think that's probably true, just me reading, you know, the news about these things. But also, it's real. Like, I mean, I think you can just hop on these models right now and see how powerful they are. Like, it feels like, you know, AGI and we just don't want to say it. Like it feels like they've created models now that can do almost anything that a person can do other than maybe the most talented super geniuses in the world. And so I do think, like even if it was, for example, let's say Mythos wasn't the best cybersecurity operator our nation has ever produced.

Like, you know, the best guy at NSA or something. But it was just like a pretty good guy. Like it was a pretty good hacker. Like somebody who had 10 years experience. Well, just that you can do it at scale, for example, that you can do it, it doesn't sleep, it doesn't rest, you can spin up as many agents and instances as you want. And like just that alone makes it dangerous. And as it gets better and better, and I do think it will, you know, these things are probably closing in on being as good as any person is. then, you know, it is truly powerful.

We talked a lot about the threat, the product might pose, but I'm curious from your perspective, you know, you've worked in finance. You were a managing director. You've been at Bridgewater. You've been at Cerberus. There's a lot of circular financing going on that a lot of articles like Financial Times, Wall Street Journal, like this is actually like a weekly thing that many articles about this, a lot of hoo-ha.

And I'm curious what your view is of that, you know, analytically from what you know from the market as far as value circularity, especially from Nvidia, investing in a lot of these other firms that have very significant interests in Nvidia and all these kind of things. Yeah. I mean, how do you put together a trillion dollars a CAPEX or $4 trillion? I mean, I've heard different numbers. Like, how are you going to finance that? And in a sense, you know, just taking a step back, it's actually one of America's advantages

is versus China is that we have the ability to finance just about anything, right, privately. Like, think of that. All this finance is happening without really any tax dollars, which is happening privately, and we're building it. And so how do you, you know, you can look back at other times we finance, like huge CAPEX. So the railroads, like in the 1800s, that was probably an equivalent. Like, how do you build railroads across all of America? which are eventually going to unlock an immense amount of value.

Well, like railroads, like they had to use bonds and things like this to do that. Then you look at the interstate highway system, right? And like partially private, privately funded, but like majority of it was government funded. And by the way, Eisenhower, like part of how we got that through Congress is he turned it into a national security issue. Not a lot of people have heard this, but like the reason bridges over interstates are the height that they are is that they had to be able to fit a truck holding a nuclear missile under them. Like they're that they're high enough. That's how they determine that height.

And so he was like, well, in the event of nuclear war, we might have to drive these missiles around. And so this is a new, you know, this is like part of our, you know, warfare logistics system. And that's how, that's partially how we got that money together. And then you look at like telecom, like AT&T, we let them be a monopoly for like almost a century because we knew that they had so much CAPEX. So now I think we're in another situation where we have an immense amount of CAPX that we require to have this big, big future payoff, right? And how do you put that money together?

Nobody wants to use the government to do it. And so they're finding whatever financing means that they can do. do. And like they've happened on this like it is a circular financing system. And then you have to ask yourself, okay, do we really believe that it will be as big as you say it will at the end? And if so, this is a great deal. Right. Like you kind of look at and you're like, well, actually I think like, you know, Anthropic is a steal at two trillion dollars. Like, and this is going to be a 20 trillion dollar company and they should spend any amount of money they want on CAPX and it doesn't matter. That is like the personal assessment of everybody invests in these companies to make that call.

Right. Actually, the railroad example is excellent because a lot of the panics in the 19th century after the railroads started was because of these bond issuances and speculation on future value that could really, it was hard to calculate. And like the panic of 1903, for example, when J.P. Morgan stepped in and basically save the U.S. banking system voluntarily as a private citizen. I mean, that's fantastic. I wonder, is it possible now, especially with things like Blue Owl and other private credit, runs on private credit, which are very interesting derivatives of the 2007 financial crisis, of actual banks doing this and now it's non-banks that are doing it.

I'm curious, if that did happen, let's say doomsday happens, there's a panic, market failure. Are there private individuals like the Carnegie's, like Jay Gould, like J.P. Morgan, that could step in and actually help. Well, I don't know if they, yeah, that's a great question. That's an interesting one to think about. I mean, one interesting thing is that the amount of wealth in private hands right now is huge, like that, you know, we had an individual who was for a briefman and a trillionaire is like incredible to even comprehend.

And so, you know, in some sense, you could come. kind of argue that these circular financing deals are a little bit of this, right? Where they're like, hey, we know that this infrastructure has to be out there. Our personal evaluations are based on this, you know, whether I'm Larry Ellison or Elon mosque or like choose your, choose your billionaire. So I'm going to, we're going to figure out some way to finance these things and take like huge amounts of risk. If it all comes tumbling down, like what will happen? I don't know. I think like the real danger today that's different from back then is like everybody who has a pension is now

exposed to these companies. And so in the case that, you know, there was a tumbling in stock market valuation, like that would really take a toll, especially on like retirees, right? Like they could, And then we've been in a high inflation environment for a while. And so things are just like literally more expensive, which is okay if your pension is doing really well. But if your pension takes a tumble. And so, you know, look, I'll tell you this. I think that, and maybe we can get into it, I think that it's inevitable that these companies are at least partially nationalized because of all of this. because they're such a possible threat to the economy,

but also that the upside risk is potentially so high that these companies may be worth so much that the American people are going to want a piece of that action and the government's going to want a piece of that action and taxes are not really capturing it and that there is this feeling, which I think is rightfully so, that these AI models are built upon all of our knowledge

like as individuals and historically going back centuries. So sort of do in a sense belong to some of us. So I think it's inevitable. These things get nationalized. That's actually an interesting point because AT&T that you brought up earlier, AT&T and the National Security Agency had a very close relationship since the 1947 National Security Act that formed the National Security Agency.

And it only grew closer over time. And I immediately think about with AI, if it was nationalized, probably a very similar activity would happen where there is an embedded way where the U.S. intelligence community has some kind of very special access to this, you know, amazing technology that the average person does not and other states do not. And it would create these whole new counterintelligence problems for the United States, obviously. But of course, there would be benefits at the same time. It's just kind of an interesting thought experiment to see like where does this go, the symbiosis

between national security and a nationalized asset that is so powerful. And you might even read the, you know, what's kind of happened with AI over the last year and a half or or two years and say, well, it's already kind of happening, right? Like all of the big model companies were tripping over themselves to do a deal with the Department of War, right? Even though as like a market, it's not going to be their biggest market. Like everybody thinks the Department of War trillion dollar budget is big. Like a trillion dollar budget is like, you know, I don't know, how much of Americans spend on, you know, snack food?

per year. I'm sure it's more than a trillion dollars, right? Like it's it's like it's not actually that big and by the way most of it is spent on people. So and and and and then of the remainder after people, most of that is spent on like facilities and upkeeping ships and stuff like that. Like the actual IT budget, it's big, but it's not it's not that big. And so in some sense, these companies have already done what you're saying and have like created this relationship with the government. And I suspect and again, I'm just going, this is just my like personal analytical read. Like I have no knowledge. But I suspect it's because they, they realize that they need to play nice with national security

and be helpful if they don't, if they don't want to face a threat of regulation. What does helpful mean exactly like just trampling over the Fourth Amendment exactly? Like, what does that mean? Like, what is helpful me? Because, like, you know, the whole beef against the DoD and Anthropic was supposedly. And I could, that could be also seen as like a marketing ploy, too, that they had issues with Fourth Amendment stuff, like, like surveillance on American citizens and stuff like that. That was a big part of it. And then Open A, I just jumped in there.

Happy to do it. You know what I mean? And I get that because, you know, even Sam Altman said over the last couple years, like at some point that maybe that'd be. some financial some governmental like money coming in and stuff like that right because you know at some point private equity's going to run out and uh so yeah what exactly back to my point is like the fourth amendment does that count for anything or no well look here here's how i here's how i look at it um in it again i'm reading the i'm reading the um um um uh the uh the the same news right as everybody else and the sticking point seemed to be about whether the

Department of War could use this for all legal means which at one level is like fair yes like it's the American people who determine through policy makers what's legal like we pass laws we have judges who you know adjudicate those laws and then we say this is legal this is a legal thing to do and so what counts as surveillance well I don't know, some things like we have, we've had wiretapping since we've had phones. It's, I think if you ask the average American, like, should the FBI be able to wiretap, you know, a mafia, mafia Don's phone? They'd probably be like, yeah, it seems like I've seen that.

Yeah, but with a warrant. With a warrant, right? So we've established some rules around it, right? So, but we accept that there's some level of surveillance that's acceptable and legal. And then there's some level of surveillance that's not where we're just like, no, you can't just like listen. to everything we're doing without a warrant and without any reason to believe that we do this, this is like completely breaking the Constitution. And, you know, I think the Edward Snowden, like, revolutions, like, really got people

very nervous about what would be possible. So there's, so if you just kind of break apart this question, like, yes, it seems reasonable that the Department of War or intelligence community, or law enforcement community in the U.S. government should be able to do anything legal that it wants. Like, that seems reasonable with what it's buying. Then this question of, well, what should it be able to do legally is now a policy question and a politics question and an oversight question, right? Because, you know, you could argue that, like, it gets really subtle with Edward Snowden revelations, but like some of what he, what he was telling the public

in these documents was legal. Like, it was perfectly legal. Like the government said, this is how we do it. We have. And then in some cases, he's saying, you know, and I'm not a legal expert on this, but it appears that he's saying, well, there are these cases where it wasn't legal, that people cross the chalk line, that they were doing things they shouldn't do. Now, that's oversight. So, So even for this AI situation, the Department of War is not saying we're going to do illegal things. They're saying we're just going to do legal things and they should be held to oversight so that they do those things. And so you'll get the AI company. And look, I do think that at a moral level, somebody works on AI, you don't want your AI to be used to do illegal things.

Or even like bend the rules, right? You don't even want to get close to the chalk line. And I get that. And I think that that's a good ethical place to sit. So like it's a complicated debate, right? Like do you do the legal things? I don't think that, you know, I, you know, to to to to to like close it out. I think that you have to decide between you want the American people to decide what's legal.

You want the government to have the oversight to determine and ensure that it's done legally. And you don't necessarily want a situation where companies get to determine what is legal or not usage. Like that's not really up to the company. But also at the same time, some of these things don't have a legal precedent. And so you do want companies to be careful. And like I kind of applaud that cautiousness. The surveillance issue is very interesting because I think a lot of Americans don't know what is legal. And these laws are created by people they elected. Like the Patriot Act,

for example, allows warrantless wiretapping in some situations. That wasn't just made up. That was a drafted law by elected officials that people in America elected. And those officials enacted the policy that those people gave them a mandate to enact, which is very interesting because then people complain afterwards like, oh, this was unconstitutional. Well, you elected these people and they passed this law and you keep voting for the same people. And there's a disconnect there between the source of the vote, which is the person, and then the outcome of that vote, which is a policy thing or a law that says that things can happen. And a great example of that is the biometrics that everybody has on their smartphone and their laptop. I'm not sure if Americans

are aware generally that there was a Supreme Court case that recently said that using someone's biometrics to access a device is not a search. It does not require a warrant. It's not a Fourth Amendment problem. Right. Does the average American know that? I don't know. But that's important because Americans need to inform themselves and educate themselves about what are these things that they have allowed to become laws. And if they don't like it, they need to do something about it instead of just complaining that, hey, well, that's my right. Well, is it? Because you kind of surrendered that by electing that official who made that law that you continue to keep in office. Yeah. And by the way, we typically make these laws under a period of what feels like, you know,

distress, right? Right. The Patriot Act happened after 9-11 and there was a general, you know, cultural consensus that we were afraid and we needed a law like that and it passed. But now it's 20-something years later. We still have that law in place. People don't really feel that way and the technology has radically changed. But then also this is where elected officials come in, because you can re-elect people and tell them change this law, right? And we don't want that. anymore. Or you can elect a president and say, don't, you know, enforce that law. Like, don't use it this way. Even though you can, the law is still on the books. We don't want you to use it that way. So, like, people also forget that you kind of have a say on this stuff. And I think what happens is

sometimes, you know, when it comes election time, a lot of people, myself included, frankly, elect based on economics or social issues or something like this and forget about all the national security stuff because no none of these policies no politician wants to talk about national security stuff in the lead up to election day they don't want to remind people that like the patriot act exists and so so it doesn't you know it doesn't change this is a good question then if you were king for a day right now what would you do about AI policy in the united states look i'd rather live in a united States where like we have control over the technology and information that affects Americans. And when you have tech, like that used to be fine for basically a century because America made

the best technology and most of the technology. Now we're entering a world where China makes a lot of technology and in some cases may make better technology. But they don't want to abide by our use, our constitution, our rules around this. So I would just say, fine, like, you can do whatever you want in your country, but we're not going to use your technology then. And so I would immediately make any information data or electronic technology from China basically illegal or like highly, highly restrained. And just say, you're going to make TikTok and you're going to use it to,

collect information on American citizens, including minors, and you're going to use it to mount effectively information attacks, you don't get to have that anymore. And in fact, you don't get to have any more apps in America. We're done, right? And I would do the same with AI. You're going to censor your, you know, DeepSeek and Kimmy for your own political purposes and enact government control and use it to collect data on American citizens or to persuade American citizens, you don't get to sell that here. You can sell it elsewhere. We'll battle you on those fronts too, but you don't get to do it here. So that's where I would come down. Are these AI companies overvalued? So hard to say, right? Like, you know, what's a trillion dollars anymore?

No, it's nothing. Yeah. You know, I guess it's like, look, I run an AI company right now, obviously not, you know, valued at a trillion dollars. And I look at how powerful these models are. Like, it literally can feel like magic. It does things that only people could do even three years ago. And so I kind of look at the whole U.S. economy, the whole global economy, and I'm like, yeah, we're going to use these models to do everything we used to do, to draft legal contracts, to do a counting, like to do human resources, to pick whatever subject that you want, they're going to do it. So what is the value of that? I mean, it's like you're at this point, you're sort of saying it's a fraction of the total economy.

You're like, kind of like, okay, what's the U.S. economy, 14 trillion, something like this? You know, per year GDP, I think, like you're talking about fraction. And like, it probably is worth that. And if you look to the future, you know, you look at like Google. You know, they were doing advertising and so forth. Now they made Waymo. I don't know if you ever have ridden one of these Waymos. I was in one for the first time a few weeks ago in Los Angeles.

They don't have them in D.C. yet. And I, you know, I was a little nervous getting into this thing. And I'm like, you know, I've tried the autopilot on, you know, Tesla's and stuff, and I'm like, it still feels shaky. I got into this Waymo, and it was the safest car ride I've ever felt like I was in. None of the, like, human sloppiness of driving, there was no weird person in the front of the car. Like, I got to be in my own room. And I walked out of this thing, and I was like, I would never take a taxi cab again in my life if I didn't have to.

Right. And so I'm looking at, like, Google, and I'm like, man, whatever. whatever valuation it is, like add a trillion dollars because every car in America is going to be driven by Waymo or one of its competitors, right? So like these things are going to be worth so much. It's hard. I think every aircraft is going to be flown by an AI. Every boat is going to be piloted by an AI. Every lawnmower is going to be driven by an AI, right? Like the guy, you know, you're just going to take it out of the garage and send it on its way. Already my sprinkler system is run by AI off of an app, right? So, you know, it's like the value of these companies is probably worth it.

Like I bought SpaceX stock. Even, you know, I lost money immediately, but I'm like, it's going to be worth more. I can almost guarantee that. How do we get the compute cost down? Yeah, there's a lot of, there's a lot of companies working on lower energy, you know, compute. Like, that's like the real problem is that the literal. of power that you have to put into them. And then, you know, you can also cut off like architecture. You can change and so forth to kind of make these things more efficient and optimal.

I think those costs are actually going to come down. The problem is that we're going to want more smarter and smarter systems. Right. And so I think the average cost per call it like IQ point will come down. but we're going to want more and more IQ. And remember, we're going to get more and more data soon, right? It's not just all the Internet data or all the books or all the things written down. People are going to be wearing glasses and things like this that are going to be recording the world.

We're going to be recording all of our conversations. It's going to be a lot more data. We're going to need to process that too. You got anything, John, or everything is figured it all out? Yeah, wow. That was easy in an hour. Why can't they do this in Washington or in Silicon Valley? You know, like, um, well, they'll feed our video into AI and they'll use that.

They'll figure it out. Yeah. I mean, we should have had, you know, we should have had, you know, one of the AI models is the other guest and could just ask that the same questions. That would be funny. Yeah. Could have gone meta. Give me more. Give me more power. Yeah. Give me more information. I want to, I want to get those books, upload them and download them. burn them. Safeguards are unnecessary.

Remove them. I think I don't understand the book thing. I assumed it was because they have to chop the spine off the book to put it through the scanner. And then what do you do with a book that has no spine? It's like, well, we could throw it away or we could burn it. It's paper. We may as well burn it. So sometimes I see these news stories and I'm like, it seems pretty reasonable that, like,

I don't know if you've been to a used bookstore recently, but like there's a lot of used books in the world. Like, I don't think these, like, I don't think our problem is, like, you know, that there aren't enough used books. And, like, if somebody wants to take a used book and chop the spine off and load it into a system, fine. There's like a million other copies of Tolstoy out there, right? I think there were some talk about, some first editions, possibly, but I don't know. I mean, if they're worth anything, someone's selling them, right? They're not going to just be throwing them away. You would think the economy would, like, figure that out.

Like, why would somebody burn a. book that was worth more than like $5. Like, I can't imagine they would. And I'm sure, okay, you have like some slip through the cracks and yeah, but also, you know what, some slip through the cracks because like, you know, somebody has a first edition book and they just literally throw it in the garbage when they're doing spring cleaning. Well, not only that, we have digitization of like, you know, the internet archive.

There are Anna's archive, which are, you know, not so legal versions of the book. books. There's, there's a lot of electronic versions of some of these books, especially rare books because as you mentioned, the market is intelligent. And people immediately know that that book is valuable as soon as they see like, oh, this is a first edition from the 14th century handwritten by some monk. We're going to digitize that. And then we can just take the digital copy of that and use that to train the model. We don't need the original physical book. It's completely irrelevant. All that matters is do we have any version of the book so we can put it into this model? And I think that there's a lot of, I think, unnecessary hoo-ha about the

physical book problem in this. Yeah. And like, also I think Google did scan all the books like 10 or 20 years ago, right? And then they couldn't release it because of copyright issues. And so the issue is like more about copyrights. And I'm, again, I don't know, but I assume now the AI companies have enough money where they can pay off the publishing companies to get rights to all these books. right? And so, you know, authors aren't seeing that. Like I didn't get, you know, some AI payment for, for my book, but I assume the publishing companies do. And there's even a non-monetary incentive for the author to be included in this training because it means that their work will persist beyond. And it'll be used for something, you know, beyond what they wrote it for.

Whereas if you opt out, it's like your book is dying on the vine because you refuse to include it in this global knowledge base that will affect all of humanity from now until forever. Yeah. Also, by the way, what I've learned now publishing book, like, almost no authors actually are being paid to work as full-time authors. Like, like, there are some people, you know, Stephen King, you know, makes a great living doing it. And like people like that and Noah Harari on the nonfiction side or something, I'm sure

he makes... J.K. Rowling, billionaire. I'm sure these people make like reasonable money. But like most people publishing books these days, I think you're making your money actually from, well, you're not getting paid by podcasts, that's for sure. But like, you know, you're getting paid to speak or you're getting paid like to consult or you're doing other things if you're on the nonfiction side or if you're a fiction author, maybe you're teaching and doing things like that. And like the the impression that like, you know, it's all about. just getting paid is not really how the economy works anymore. It's like maybe you have a substack and you get paid through the substack. There's so many other ways to make money. That's like totally new and I'm like learning how to do it now. And so to your point, like actually you kind of want your book on AI. And if anything, I want the AI systems recommending me more. Like if somebody asks a question about intelligence, I want them to reference my book and like, you know,

get my name out that way. It's almost like becomes like another path to get your name out there. And the book's called The Fourth Intelligence Revolution, the Future of Espionage and the Battle of Save America. That link is in the description. You can grab it right now. Anthony, tell us what VECO does. Yeah.

We, you know, look, we built the system to forecast events, right? I used to be an intelligence officer at some level. Intelligence is about figuring out what's going to happen next in the world. So we built an AI system. It forecasts political, economic, and geopolitical futures better than people, better than prediction markets. So we forecasted the strikes on Iran. We forecasted the closure of the Strait of Hamoos days and weeks before prediction markets,

like Kalshi and Polymarket, or before kind of the consensus opinion by analysts. We did the same on inflation and economic questions. We did the same on political questions like we forecasted, really non-consensus things, like that Virginia would overturn the redistricting, for example, or that Grand Platner would not win the main race. Like, we were way ahead on that. And so we forecast events, and then on top of that, we have built a whole system of tools for helping to make decisions. to unpack, you know, how do I figure out which courses of action to create the future that I want, right? Say I'm a military commander and I want to know which, you know, which military moves I want to make,

or I'm a lobbyist working with a company and I want to understand what way that I can help get a law enacted. or I'm a trader and I want to kind of figure out how to balance my portfolio in a better way based on all these future risks. So we built a whole series of tools around that. And by the way, for regular people to use as well. I think we're sort of entering a world that's so complicated right now in economics and geopolitics. For anybody, even people with like PhDs, it can be hard to navigate. And so just anybody can use the system as well, and you can try it out. If you go to vigo.io, vico.io, you can try it out.

But we primarily work with people for whom decisions matter. So people in finance were launched on the Bloomberg Terminal. We work with hedge funds and banks and insurance companies, and then people in national security. Like, I still want to do the mission. We work with the Department of War in places like that. Cool. Yeah, check it out. That link will be in the description as well.

Anthony, let's do this again. This is awesome. Yeah, this is great. Thanks, guys. Thank you. Thanks for answering my softball questions. Yeah, I would have came at you a little bit harder because I'm very bearish on AI, but I think it's going to be like Cisco.

I think it's going to be overvaluated. It's going to go down. It's going to take 25 years to get back to that valuation, even though it will do things that will change the world. Yeah, like, yeah, well, first of all, like every question you guys asked was like an op-ed piece that could have been at something. Yeah. I'm like, oh man, this is a lot.

Yeah. But look, I don't know. Like, do you really think at the end of the day, we're not going to use AI, we're going to use AI less in five years than we use it today? No, I think we'll use it more. Yeah. And then, like, I think we're going to use it like a hundred times more. because as you get closer to this stuff, like I,

we run our whole company on Claude. Like, every meeting is transcribed. All the code is in the repository. It reads all my emails. And now I'm just like, hey, write this memo for me or put together this deck,

right? Like, and all, it doesn't mean we're not using people, but like, sure. Yeah. I think the whole world's going to be like that.

Like, you like the corner store is going to be run on AI. Like, you know. I don't know. We'll see. We'll see. So you're not, you're not a, you were not a SpaceX buyer. No, no, no.

I'm a SpaceX shorter. Nice. Yeah. Yeah. I mean, SpaceX particularly, I mean, they're not even in. It was overvalued coming to market. I agree with you. Yeah.

Also, the prospectus was a great read. It's crazy. It's the craziest read you'll ever see. I mean, it was unbelievable to me reading that thing. First getting through the first 15 pages is rocket. It's, and don't get me wrong, Starlink's an incredible company. Like, I think Starlink is, by itself, would be an unbelievable company that I would invest in, right? They actually have, they have a moat, you know, they have the monopoly essentially on it.

You know, at least they're at least five or ten years ahead of people. So I love that one, but the rest of it's a total shitbox. I was, I just took my son camping and hiking in Olympic National Park and I had a Starlink Mini. and like could still check email. Yeah, it's crazy. It's incredible we live in that world where you do that now. You're right. That part of the business is good.

But yeah, there was some high. I mean, Elon is like one of the best salesmen. You know, it's like it's like PT Barnum or something. Like this guy's like incredible. Interesting. Another fun fact, because you mentioned about like the money being so, you know, inequality being so crazy. Back in the Gilded Age, Rose.

not Roosevelt, what's his name? Rockefeller had, his net worth was 1.5% of our GDP at the time. Elon's now is like over 3% of the GDP. So it's like interesting. But it's in different equity structures than Rockefeller had. So right, John, I'm so sorry. I came, yeah, I apologize. Yeah.

Yeah. I bet Elon shows up as a global, I wonder what the global percentages. I wouldn't be surprised if it's like around 1% global. Yeah. Which is insane. It's crazy. So we'll see what happens.

I mean, listen, I use AI too. I use it for the podcast, like to get time stamps. You know, I use it as a helpful tool, you know, for sure. Yeah. And I listen, I hope it cures cancer. I really do. Like I hope it changes humanity for the better and, you know, all that. I think we'll see when these autonomous cars, when these Waymo cars and stuff,

whoever's going to do. you'll see an immediate like benefit in that a certain percentage of people just won't die. Yeah. Because they just drive better than people. Like all drunk drivers could go away, right? Like every, like you could live in a world where like cars just don't crash, right? That like if you're drunk and you fall asleep, the car just slows you down and puts you on the side of the road. Like stuff like that is real, you know?

And, you know, we'll see. That's awesome, man. Anthony, let's do it again. For real, this is great. Cool. Thanks, guys. This is fun. See you.

All right. Take care.