The Pomp Podcast - The AI Boom Is Bigger Than Anyone Thinks | Dan Ives

Episode Date: October 1, 2026

Dan Ives is a Partner and Senior Managing Director at Yorkville Ives. In this conversation, we break down where value is building in the AI trade, Dario's warnings about AI, regulatory capture, and whether OpenAI and Anthropic are in more trouble than people realize. We also discuss the White House AI meeting, sovereign AI, the US vs China race, and his new Ives Ultra Fund.=======================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you’re rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! =======================Lava is a global platform for bitcoin financial services. Spend with Lava Card and earn up to 5% back in bitcoin with every purchase— all with no annual fee, no FX fees, and zero spread. Plus you can borrow against your bitcoin at the lowest rates, earn yield on cash, and move fiat or stablecoins globally. Get started at ⁠https://www.lava.xyz/POMP⁠=======================This episode is brought to you by Investor Health — clinician-prescribed protocols for weight, metabolism, energy, and longevity, delivered to your door in 48–72 hours. No office visits, no referrals. Plans start at $149/mo. Learn more at ⁠http://www.InvestorHealth.com/pomp⁠. Investor Health is a telehealth platform, not a medical provider. Compounded medications are not FDA-approved. Individual results may vary and treatment requires evaluation by a licensed provider.=======================0:00 - Intro1:12 - Where's the value in the AI trade?2:32 - Dario's AI warning & regulatory capture5:15 - Are OpenAI & Anthropic in trouble?11:04 - Trump's White House AI meeting13:51 - Open source vs closed source AI15:32 - Token price war & the Anthropic IPO22:33 - How to invest in the AI trade25:04 - Personal AI agents & consumer AI26:31 - Why tech is ignoring macro headwinds30:36 - The Ives Ultra AI Fund33:21 - Data, sovereign AI & the future of work

My name is Siyah, and I live in the most beautiful place on Earth. Seven months ago, I blew up my life, and a lot has shifted since then. Everyone is moving forward. I'm still working on that. And that's me. Welcome to Ice Cove. Where are the penguins? That's Antarctica. We're the other one. North of North. Stream all episodes, available on CBC Gem.

For somebody myself, it's covered tech my whole career. Three and a half million air miles, so many times, like in Taiwan, in Korea, you see them building fabs at 18 hours a day with one bathroom break. Then I land in Newark airport. There's a fist fight to Dunkin' Donuts. And you wonder why we're 17 to math. Now, for the first time, U.S. is ahead of China when it comes to tech. You don't want that to end. What's going on, guys?

Today we've got Dan Ives on the podcast. Dan is the partner and senior managing director at Yorkville Ives, and he's here to talk all about the AI trade. We talk about the sectors that he's interested in, the sectors where he thinks values going to accrue, and maybe some areas where you should be cautious. We talk about the private AI model labs, where is pressure coming from, or is AI actually going to kill us all? What happened at the White House meeting? And then we even get into what's going on with all the personal systems that have been coming to the market. Dan's got some very unique thoughts on the AI trade, and I think that if you watch this, it's going to make you a smarter investor in the market. And then Dan finally finishes up and he talks about the Ives Ultra Fund. It's a brand new fund that it's brought to market.

It trades under the ticker Ivy AI. And I think people are going to be very interested to see how they can hold a public stock and get exposure to the leading private AI companies. Here's my latest conversation with Dan Ives. All right, Dan, AI trade obviously was super hot earlier this year, then got a little cooling off in the summer. But it feels like it's starting to come back here a little bit. And we have the private companies that are knocking on the door of going public and

anthropic, open AI. But the public stocks, where do you see value through the end of the year? How are you thinking about the AI trade today? Yeah. Look, I think the demand, I think starting last quarter, that's where it changed. Because the monetization you saw specifically with Microsoft and the other hyperscalers, I think that was an inflection point quarter. I think now Lava is around the second, third, fourth derivatives.

And, of course, memory stocks were there. But I think you're seeing across infrastructure with Dell, with Cisco, I think with cybersecurity stocks, you're starting to see a play out. Look, take a step back. We're less than 15% through what the spending trend is going to be the next three to four years. It's $4 to $5 trillion. For every dollar capbacks, there's a $5.6 multiplier across the rest of tech. So I think we're going to go through these sort of ebbs and flows, the regulatory capture, the Dario essay.

I mean, some of these things will continue to sort of get in the way to some extent in the near term of the trade. But I just continue to believe we are in the early days of what's going to be a multi-year tech bull market. And the first time in 30 years, U.S. is ahead of China when it comes tech. When you see Dario come out and basically say, hey, we think that there's a 5% chance or 10% chance

of AI killing us all, we must slow down and kind of all of these calls for essentially like, hey, government, regulate me harder. I've never heard a business that is serious talk this way. What's your general read? Are they sincere in this? Are they just trying to use it to slow down their competitors so they can catch up or what's going on?

I mean, 1910, like, I, we can't go down this car route. We have to stay horse and buggy. These cars kill you. I'm just saying it's technology always goes ahead to regulatory, and I think some of it is I'll call regulatory capture. Like, you go to the top floor and then you pull the ladder up. So I think there's some of that going on. And I think that's also why you had to have

that sort of all-hands-on meeting with Trump at the White House because you have to get everyone on the same page because the reality is going into a midterm election cycle you know talk like that and mean you have talked about as a four

I think a lot of the tech industry they created the PR nightmare the black eye that now they're contending with but it's it's an arms race and if we slow down China accelerates that's not a debate

so that's why every time like in terms of like the politicians and the Bellway many you know do you want people that are still using BlackBerry's and Flipfoams to ultimately be the ones that are, you know, the direction of innovation in this country. And I think that, look, it's not going to slow down. And I think you saw how stocks reacted. I think if you go back, like over the weekend, the bears that have called 10 of the last two downturns, they're like, oh, my, because remember the bulls are

usually watching football hanging out with their family, the bears in Saturday. That's usually where it peaks out. But then the reality is that you saw what Jensen talked about. what Nadella talked about, what Karp talks about in terms of sovereignty. That's more what I view is like a very sort of middle of the row of view. And that's my opinion. This is not slowing down anytime soon. What I found interesting was, you know, right after the call for the slowdown or pacing or whatever the hell they were saying, Zuck came out and Zuck did not talk about slowing down.

Zuck talked about, hey, it's our job to release products that are safe. And my general framework, but I want to hear if you agree with this or not, is the companies that are losing money that have negative cash flow, they're the ones calling for the slowdown. The companies that are profitable, like the Facebooks, the Googles, et cetera, I don't hear them calling for a slowdown at all. And it almost feels like depending on whether you can fund this with non-dilutive capital or not is ultimately determining which side of the regulatory capture argument you're on. Yeah, so regulatory cap, so I agree on the regulatory capture, but maybe like a different end. I view it as those leading the F1 race, Anthropic Open AI, you don't want others to catch up to you. The way that that could ultimately be called throwing sand in the gears.

But do you think that they're leading? I don't even think there's a question that they're... Oh, I think I disagree. All right, go ahead. Good, good. It's good to disagree. I know. I want to hear about this. When it comes to pure models and what they're doing on the enterprise, I think Anthropic and Open AI have had the create

I've had the queer lead. Do I believe that there's a gap narrowing versus meta, versus Google, versus others? Yeah, because, but see, I view it as the value chain is going to be in the data. The models over time will become more commoditized. So I don't become as focused on open source models what happened in China.

What Muse is done is actually just a positive for overall AI. So I view it differently rather than like the raising capital component. I view it more like you're way ahead in the race. Others are starting to catch up. I could argue like the Dario essay, that was 20% of that add to meta stock. Because Zuck looks at that and be like,

okay, you're gonna go right lane 55 miles minivan with the bumbers thing and saying your kid was an honor student in third grade. I'll go in the left lane, Ferrari, and we'll gain share. And that's essentially what Zuck's done. So I think that the, the private large lab models aren't way more trouble than people realize. And I'll give you two maybe examples. First is, my belief is that token consumption leads revenue.

So if token consumption starts ramping aggressively, revenue follows. I believe that the revenue has been plateauing inside of these large language models, anthropic in particular, mainly because the general intelligence approach is not nearly as valuable or large as people originally thought. Because I think the original thought process was you're going to create the smartest model possible and then everyone is going to use it for everything. Now what's happening, though, is people are saying, wait a second, I want to own my own intelligence.

Sovereign AI. I want to have applied AI for this specific use case. And maybe I use them to get started because it's easy for me to build some software, plug them in. But if you think, look at what we do with Sylvia. We started off 100% as a chat GPT wrapper. Over time, we said, well, rather than use chat GPT, let's switch over to Claude. It seems to be better.

Our monthly compute expense went from zero to hundreds of thousands of dollars. We were one of the fastest month-over-month growing customers I think that Anthropic had. Great. They loved us. Then we said, wait a minute, why are we using, from an architecture standpoint, model to do certain things? So there was literally a point where you would refresh the page on Sylvia and you'd hit the model. Like, let's stop doing that, right? So you started to get smarter about, like, when do we hit the model?

how do we hit the model? But then over time it eventually became, why don't we just train our own models? Why don't we build our own harness? Why don't we go and actually have the sovereignty? So we're not having to use somebody else's intelligence. We can also, though, make it custom. So now we get better performance. We get better accuracy. We get lower cost and we get less latency. So we're not going to give up on using them. We're still use them for plenty of stuff. But the token consumption that they have from us versus what we're doing ourselves is shifting. And so, on like a per-customer basis, it seems like a lot of companies are saying, hey, I'm not going to go to zero with them, but actually I'm going to use them less and less

as I build my own stuff. And to me, that feels like a massive headwind that not a lot of people are talking about. So I think on some early adopt, no doubt, look, sovereign AI and carp talks about it, Jenzin talks about it as well. Like that, that's the Golden Goose.

It's about companies now they've gotten their arms around, okay, that data we ultimately want to maintain and we don't want models coming into that data to replicate our business and ultimately put us out of business. I think the difference is that when you look, look, 4% of companies have gone down the AI path just in the US today.

Only 4%. 4%. Wow. So that's the difference on that. So in other words, if we were at 50% and that can something, then I'd agree. So you think there's a lot of runway to go. We're still in the zero to one phase

of just AI adoption in general. It's only the people who are on kind of the frontier, they're the ones who are starting to adopt sovereign AI, but that might be 0.1% penetration. And that's why so many CIOs that I talk to, okay, the ones that are very advanced, exactly where you are,

and that's where like a sovereign AI, you talk about like what Pallantier, Nvidia, some of the things even, you know, I think some of the infrastructure players are looking at. But when you think like, look, Europe, they're building blockbuster videos. You know, you think about what's happening in India, they're trying to figure,

out do they go US, China, Middle East, very skewed toward US tack in terms of what we've seen there. So it's a two horrid rates between US and China. When you think about why we're so bullish, it's about the numbers. Europe, eventually they're gonna, you know, once through the red tape, they'll ultimately embrace AI, Middle East. And then think about you're gonna get to another 60, 70%

of enterprises that go after AI and adopt. That's still on the come. And then thinking about on the consumer side, That's just starting now with Apple, finally actually having AI. You see what meta is doing as well in terms of Mews. So my view is like, we still have another two, three years of just massive growth. And I think that's something that investors are still underestimating the scale and scope of. Now, when you see all these leaders come together in Washington, D.C., they meet with the president.

Whether people like him or not, one thing I think everyone should agree on is that he's good at brand. And he says, this artificial intelligence name sucks. I want to name it super intelligence. What are you going to call it? Look, I mean, we still call it AI. But the point is like, forget the name thing. Trump basically had to get everyone in a room. You're like, look, what's going on?

And because going into a midterm election cycle, if you continue to be dystopian, talk negative, you know, about like what this could do to mankind, guess what? more data centers get shut down. It's becoming a huge, I think it's become a huge debate no matter what the town, what the state, what the city is. It's very important that you get everyone on the same page

because every data center that gets shut down, China wins. And that is, I think, the most important part of where we are. You need more self-regulation rather than public, private, beltway talking points grandstanding type stuff because I think that would be the most negative thing my whole view is like for somebody myself it's Carver Tech my whole career three and a half million air miles so many times like in Taiwan in Korea you see them building fabs 18 hours a day with one bathroom break then I land the Newark airport there's a fist fight the Dunkin Donuts and you wonder why we're 17th the math

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Archpublic.com. Do you worry about America pursuing a closed source model versus China pursuing a open-weight open-source model, or do you think that actually American open source needs to become much more prevalent? And I think that's what NVIDIA is done. I mean, you go out to the hugging acquisition. I mean, that, because generally, Jensen understands better than anyone. Forget it. Like, he does feel like the biggest adult in the room by far. It's not even a question.

He is the adult in the room. I actually think the two that understand that the most are Jensen and Karp. Interesting. Because they understand, just forget the, because everyone focus on the models. They have a much more, I think, global view because of, I think, in terms of Poundier,

what they ultimately work with, in terms of enterprise, but specifically government. I think Jensen has the most global view. Jensen understands open source you need, just based on cost. Think about it. Let's say phones, going back 2007 and 2008, let's say Apple priced the phones

double where they were in 2007, 2008. Would you have 1.5 billion iPhone today? No. You have to make sure, tokenization costs, the pricing, open source. That's why I think Muse also, just as a side note, is very important. And that's why, like, I think the most important person that has the best perspective is Invidian.

He continues to sort of be the calming force. Even when did the All In podcast, you know, right after the Dario essay, Sobopra on the weekend, and there was, like, such an important time for the market. Well, so this goes back to these large language models, right? I think everyone now has seen this chart where all of the token prices, they're pushing out on the frontier in terms of their intelligence,

but they're coming down in price. And so you have this essentially a price war occurring. So if you go back to, well, what is the revenue of a model lab? It is token price times token consumption equals revenue. So if you have consumption per customer dropping and you have token price dropping, it just feels like there's massive pressure. So then the question becomes anthropic was supposed to go public this year. Open AI was and then came out and said they're not going to.

Do you think we get the anthropic IPO before the end of the year? You think so? Yeah, I think that's like, I'd be shocked if that doesn't happen. And then... Well, we've seen take ORA ring. Those guys, they claim they were 4X oversubscribed. They claim, you know, all of these great metrics

going into the IPO. And then the night of the night before, they basically pull it. I don't know what happened there, right? But it does feel like... And they blamed, by the way, market conditions, which is kind of like a nonsense thing, right? But fine. I couldn't get to the dinner because of traffic.

Yeah, yeah. We should definitely do it again. So, do you feel... like anthropic, same thing, is like maybe it's not an anthropic problem, but they just say, look at the market and say there's too much here going into a midterm, let's not go out. I just think after the midterm it happened. Look, to me, it's one. First, I think also when it comes like public, it's always hard to compare because we like this IPO got pushed or that anthropic is a whole different game. Just because globally, and I think we saw this with SpaceX as well,

the appetite to understand what the trajectory looks like. Look, do they have unique risk factors, like mankind? You know, of course. But I do think we're going into a golden age for AI. We're going into a golden age where many of the private companies ultimately will be public. And I think that's healthy. Because for the overall tech trade,

anthropic and open AI being public is good. It's not bad. I think actually, and I think that, that's ultimately where it's going. SpaceX, Open AI Anthropic being public, are actually very good for the market. I agree. I just think that when I talk with people,

there is this blind belief, these are amazing companies. And when I push on specifically people who aren't like analysts, why do you think they're a good company? They start talking about the quality of the product. And maybe my word of caution to people is just like, a good product doesn't equal a good company. You can have a good product in a good company. It is undeniable.

The products are amazing. People love using them. But when you start to hear some of the data points that are coming out, you know, in terms of what's in the S-1, you look at some of the kind of trends. I just think there's way more headwind than maybe people think because you're dealing with a, you're dealing with an industry where, look at Jev, right, maybe as a good example. Like that wasn't on the chess board three weeks ago. All of a sudden, zero to $100 million run rate in, you know, the first week. and scaling, and I use our engineering team as maybe a pressure point for me.

So I go ask them, I say, hey, how many of our queries are routing through various models? All of a sudden, Jev now, it's not 50%, but they're starting to use it. And they're starting to put it in places where previously you couldn't use one of the frontier models because it was cost prohibitive.

And so you start to almost like, it's like death by thousand cuts it feels like, and we're going to get this huge fragmentation, which maybe to you should be. your point, that's why they're trying to pull the ladder up, is because that would solidify them as the centralized winners. Also, Anthropic and OpenA, they've been

very intelligent and smart, seeing around the corner building up the Enterprise Salesforce, going after a company. Because they recognized, I've been pretty early on, like, the consumer piece is not where they're going to monetize. They're going to monetize on the enterprise.

But then it goes back to, like, less than 5% of companies have gone down the AI path. Take a company just, given the amount of data they ingest, they start to go to AI, what that's going to do from an incremental business perspective for Anthropic, for OpenA, but for the overall industry, it speaks to...

Well, even meta, right? Muse for small business. They're all, you know, going that way. And that's a good example, like with meta, like everyone count them out. They're spending like 1980s rock stars. You're not seeing the actual, you know, return. When you have three and a half billion users,

you could be late that... Now what's happening in the stock. Apple, same thing, right? Apple, Barras, that stocks, it should be like $200, $250. They don't get it because it's about the install base, $1.5 billion iPhone, $2.5 billion iOS devices. You're now a toll collector

on the consumer AI highway. I just think whether you're bullish on Anthropic or Barrish or Open AI, take a step back. This AI trade is spreading, not just from memory to infrastructure, to allow even the traditional players, the HPs, the Dells, the Cisco, it's going to go to energy, it's going to go to infrastructure.

And I think that is a very key theme. And I just think a lot of investors that, you know, have missed really every transformational growth stock the last 25 years, it's very, I think it's a, it's a part of the market where you have to be able to look out two, three years, physical AI, global. what I believe is you couldn't be U.S. tech dominance and what that means for innovation in this country. And I just continue also believe the taking jobs away narrative, just like the SaaS apocalypse, I think, was way, way overdone.

And I think now you're starting to see some of that play out. More jobs would be created by AI than taken away over the next decade, in my view. Easy, easy. And look, we see this. Inside of our company, there are more agents. than humans. There are definitely jobs that we did not go hire for because the agents can do it, but because the agents are so productive, the company is growing faster than it would otherwise, which then leads to us being able to hire more people.

And innovation in this country used to be like, if you want to do a startup, you got to get seed funding, there's 20 million dirt. Now, because of the engineering horsepower that you could do, think about the innovation that now could happen in this country. And I just think it's a good, it goes about to like the White House meeting and big tech and where we are. Everyone recognizes like this is a movement in time. And it is just very important. Like you do not put the brakes on. You put the brakes on.

We will look back five, 10 years and I'll be like, how did China get so ahead of up? And I think it's just, it's a very, very sensitive, like whatever call it, like hot button topic. But I don't really see any gray terms of the direction that we have to go. So let's say, I'm an investor. I'm looking at the entire public markets, and I'm saying to myself, all right, there's a lot

here to unpack. I've got the MAG7. I've got the infrastructure. I've got all the data centers. I've got memory. I've got, you know, pure play AI. How do I think through allocating money, right? Is it put a certain percentage of my portfolio in AI overall or are these like different sectors,

but like the entire economy now is AI. And so, of course, you've got to, you know, have it throughout your portfolio. Just like, how are you talking about this? It's about second, third, fourth derivatives. Like, I continue to believe large cap tack is starting to flex its muscles again. You look like Nvidia is a good example. Like, those that continue to sort of defy or they think it's getting tired, it's not a shiny new object anymore, you could argue that that stock is way cheaper today than it was six to a month ago.

And you still haven't even gone into what's going to be the full wave of physical AI and where we're playing. are Asia checks show 13 to 1 demand demand supply 13 to 1 for chips in Asia that's also why like AMD if you look like what Lisa Suz done they're just starting in terms of them the chip size I just think you have to own chips you got to own the hypers

and I think you've seen specifically Microsoft Amazon Google like reinserting themselves because of the install base and it goes back to like less than 5% that have gone down the AI path as more head down that that's bullish for the hypers. The software, the SaaS apocalypse, I think, was a fictional narrative.

And I think there's a lot of these, if you look like from Salesforce to service now, of course, Palantir leading in, I think that's one that's almost going to become a category changer, especially as the free cash flow, ram significantly. Cybersecurity, another example.

Go back to like April. Cybersecurity is done, anthropics eating their lunch, look at crowd, strike, pal out, those Zscare, look at those stocks. Now look at it. And then I think you have to even go further out and look like infrastructure and energy.

My whole point is from an allocation perspective, you own the core names and winners and themes, but then you have to see where everything is heading. Like when, look at Tesla, like when are they actually going to start to now transition from that EV player to ultimately Robotaxis, autonomous, optimist. Once the transition happened, you've already missed it. Personal agents are all the rage now. You've got, you know, the Grockbox of the world who are kind of sort of personal agents,

but then you've got instinct, muse, et cetera. How does that impact the AI market? And those are a consumer. It seems like these businesses, at least instinct and Zoc, have both come out and said that they are not going to try to charge the consumer. They're going to find other ways to monetize. What do you just think about that as a sector

and how investors should think about that? I think that's going to be like, a whole other area of investing. Because my whole point is, like, you have to think about, like, the enterprise, then the consumer piece. Clearly, like, the infrastructure, if it was the goal rush, those, the picks and shovels, like, they're ultimately going to benefit on either side. But if you think about it on the consumer, we're just now starting the consumer AI revolution.

That's what I think Apple, the stock's doing what it's doing. And I think you start to see what I believe is going to almost be, like, a new category. that comes online. We're going to be talking about stocks 18, 24 months from now that we don't, we're not talking about today. But that's why it goes back to my view. Like you don't have equilibrium

to late 2028, early 2029 in terms of chips. And I think that's something, despite like 10-year oil, geopolitical, whatever the moment, the sort of, you know, the nervousness of the time, I think tech is going to continue to plow through and be the leader of this market. So that's interesting because the macro environment, almost everything is telling you,

hey, top or headwind, right? You have interest rates going up. You have oil, you know, 100 bucks or so. You've got 10 year over 5%. People are very nervous. Home prices are, you know, quote, quote, falling, all this stuff that if I wanted to paint you a very... Key-shaped economy.

Yeah, well, if I wanted to paint you just a very negative story, I can do it easily. But if I told you six months ago, we're sitting here, I know the new studio in that, but like before the new studio. And I said six months from now, oil 105, 110, 10-year 5.2, 5.3, I ran still going. I told you everything. And I said, okay, where do you think S&P and NASDAQ are? You probably would be off by 15% lower. I agree with that. Because it comes down. The market is telling you we're in a fourth industrial revolution.

The growth, I could argue the 10 years there because of the growth and because what are going to be ultimately more and more debt raises and because of the data center build down and because of what we're seeing from a CapEx perspective. So I just think investors,

you can, my whole career going back to late 90s, if I got caught up in like geopolitical, Europe's going bankrupt, the bottom line is like my career would not be where it is today. So I'm just, just saying it's very easy to get caught up in the bears, the catastrophist that have called

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See investor health.com. You recently priced a brand new financial product in the market. It is a special purpose investment fund, which is kind of like a SPAC, but it's an investment fund. It's $200 million raise. And my understanding is that you're going to take this, which is called the Ives Ultra Fund. IBAI. You're going to, the ticker's IVAI,

you're going to take it and go invest in the private market. So it's a publicly traded permanent capital vehicle that will have exposure to private companies. What are you going to look for to allocate the capital? And it's the first public company ever to invest in private AI tech companies. Look, for me, so many people around the world, whether it's retail, financial advisors,

as well, whoever amazed someone in an airport, how do you invest in private tech companies? Institutions is the big issue, right? There's SPDs, SPV2, SPV3. Boy, I stop at three. My whole view is to create a vehicle that you could own the leading private tech companies and give, instead just a small club outside Silicon Valley

that could own them, why can't people in the public, own these private tech companies. And that's what we're doing. I mean, it's gonna, you know, this is really kind of a Swiss Army knife approach to try and to identify what that portfolio looks like, whether some of them are bigger players or well-known today, to some that like, who could be the next Pallenteer?

Who could be the next model that ultimately drives this market? And that was really the origin doing it with partners Ed and Jeff Leathers. It was super exciting to do that, to do that because I just believe it's a new frontier. I think it's a very good idea. And also, I think that you are the right person

to go and find these private AI companies. And the blending of the public and private markets continues, right? Whether it's tokenization, whether it's funds like this, like we've seen this play out, and this just feels like another step in that direction. Well, it's like why, if someone's like you're in a private credit fund, why can you be in a private tech product where you own private AI tech?

Look, it comes down to, like, this is the new landscape. The reality is trillions of dollars are going to be spent in this sector. A lot of it's going to be spent on private companies that are leading it. And it's trying to identify that. And I think if you go back historically, it was a small group of people or companies that could buy these private companies. And I think it's just important where we are today to create a public vehicle that does that.

Yeah. It's very interesting also to see the private companies how fast they're growing. Like one of the companies, an investor, is called Micro One. And Micro One is data business. But the data business is, you know, scale AI is like a data labeling business.

These guys have some data labeling to them. But also they are going out and they're paying doctors and lawyers, et cetera, to go and actually create data for them to then go and sell through. They're now going to companies and they'll pay pretty large amounts of it. And I'll give you one that I'd never heard of before. Somebody emailed me this week and said,

hey, will you license us the podcast because they want the data? I don't know if we're going to do it. I have no clue if that even means. We haven't talked to them yet, whatever, but I was just like, oh, data is data. Like, there's going to be data all over the place that people are going to try to buy up

and use for all these different... Data is the new oil and gold. Like, why do you think Amazon put the gates up with Muse? Mm-hmm. Because the reality is that, and that's why sovereign AI is such an important dynamic, which you could say is negative for the model players, because companies are saying, okay, we want to have control of our data. We're going to do it in our walls.

And I think that's, see, different than the model players that are narrowing the gap, I actually think sovereign AI is more of the bigger debate. Why? Because companies are starting to get their sea legs. They're starting to understand like, okay, we got to go full AI. We need these strategic paths, but is it just giving it and outsourcing it to an... No way. There's no way that's going to happen.

So that's... So you go through evolutions, right? Like, it's no different than any technology. The technology, it's going to take time for these companies. time for these companies to recognize, like, trial and error, what's the best path? And I just think, like, that's going to create so many more opportunities for other companies to monetize. I don't think people understand. The sovereign AI thing, right, own your own intelligence, sovereign AI. What do you want to call? Again, I just know the thing that we have seen.

If we route a model, or a query to our models on our hardware versus go to the frontier models, the cost savings is about 97%. But the cost is not the reason to do it exclusively. It's actually the answers are more accurate. So what I always go back to, and to be honest, when we first started going down this path, we have some very smart AI engineers. And they were explaining to me what they thought was possible

and all stuff. And you kind of have in the back of your head, dude, there's no way a team of six, seven, eight engineers is going to be the trillion dollar company. And then they explained to me, well, let me show you how this works. And so today we've come out, we've shown. Sylvia is more accurate on tax, mortgage, credit cards,

you know, these personal finance topics. But it is less about how many engineers you have or anything. It's, are you general or are you, you know, applied AI? And then what is the data set that you're able to use to get to that level of accuracy, the reinforcement learning, all the eval rubrics, like all of these components. And I just started to realize, I was like, if we can pull this off, Dude, what is it going to happen when these large companies start realizing, why don't we just do it ourselves? And they have hundreds, thousands of engineers.

Like, this is going to completely change the way that people think about this technology being integrated into these companies. But it's a democratization of the technology. See, I don't view it as a net. See, I view it as... It's empowering for the company. This is not just a duopoly. If it was a... Let's just say this was just open AI and Anthropic.

And invidio was selling the chips. Like that as a bull case in this market, that's not bull. You need democracy. You need data sovereignty. And I actually think like this is actually like, like I said, it's third inning of this game because it's not those that say, oh, it's sixth, seventh inning. I mean, I go around the country so much,

I look in the data centers and I just think even if 10 to 15% get voted down, like, you're going to have 800,000 data centers built in the next 12, 18 months. Like, that is, that's building the hearts and lungs of what's going to be really a new economy that's building out in this country. It's 100% of a new economy. And I think that, I'll leave you with this. I recently was talking with some of the engineers.

And I said to him, I said, would it be offensive if I told you that I'm, I've now retrained myself over the last six months and I'm a software engineer? My entire career, I've been, you know, I was a product manager at Facebook and, like, understand product, I would never write in code. Right? Even if, you know, I was building a WordPress site, it was kind of like you're hacking it together. I'm not a software engine. I don't have a computer science degree, all this kind of stuff.

And for people who are non-technical who work with engineers, there's kind of like a bright line. Yes. You do not claim to do what they do because they are very special. They're the stars, you're the support staff, right? It's kind of the way I've always thought about it. But I said to him, I said, look, here's how I have started to think about this. And one of the engineers, probably one of our best engineers, said to me,

If I was doing an interview to hire a software engineer, one of the first questions I asked is, show me what you've built. And he's like, and you have all this stuff that you've built. So he's like, the lines are blurring. Now I'm not going to go actually put software engineer like in my Twitter bio, right? And you know, like bang my chest and become a software engineer now. But if that starts to become a skill that dummy me can use,

what happens when that permeates throughout society and throughout the economy and now all of a sudden productivity accelerates? But that's the whole, the whole, The whole point that the feds talked about is that no technology the last 100 years has been a net job detractor. It's about productivity enhancement. And I just think sometimes as you're going through the storm, the turbulence, you can't see the other side. Sometimes I think it's very easy to get caught up in narratives in this market. And I think that's some of the danger as an investor too when you get too caught up because I see it from an

I see it from CIA. I see it in Asia. I see it from a chip rip. When you see the innovate, you see physical AI that's ultimately coming. And that's why, like, when you have adults in the room, like Jensen, kind of navigating it, I think that you just continue sort of. That's the yellow brick road to the success. Yeah.

It's fascinating. Work with somebody to find you online. Yeah, so dives tech. And again, I don't block hardly anyone or LinkedIn. And, no, look, I appreciate. Look, this is just, it's an important time to sort of, you know, navigate the narratives in some of these white knuckle moments and make sure investors just don't get, you know, sort of caught up sometimes in these bears from the hibernation mood. I think you're doing a great job. I'm very excited about the fund.

IVEAI is the ticker, and we'll do this again. I'm going to convince you to start doing this weekly. Hey, I'm here for it. All right. We'll see everyone soon. Thanks.