Thank you so much, Gary. And now I'd like to call up Dr. Ken Lynn. Ken is Senior Vice President of CP Group, which is a very big company from Thailand. And Ken is also an adjunct research scholar at Columbia University School of International Public Affairs, my old school, so happy about that. And Ken is going to engage in the dialogue with Gary.
You're so kind. You say a large company. It's like a massive company. It's a massive company.
It's a massive company. It's got more 7-Elevens than anybody in the world, I think.
Thank you. Thank you. I got a second. Hello, hello. Okay, that's fine. Thank you, Gary, for reducing my workload. Yeah, now we only have like 20 minutes left.
That's good. Yeah. So let's go straight forward. As we know, you are a heavyweight in the financial markets, well known for your strict regulation of Bitcoin and crypto, and some even say you are the one person that the entire crypto industry both respects and also fears. But don't worry, I'm not going to ask you how many Bitcoin you hold. It will be an afternoon only. For the first question: what do you think are the investment opportunities in the AI era?
The answer to your first question is zero. I don't own any Bitcoin. There you go, you know. But look, the investment opportunities, I truly believe AI has been and will continue to be a transformative technology. I stress it's not new with just GenAI and OpenAI and so forth. I think how to commercialize it is a really interesting thing.
I think you can automate a lot. There's a lot of value proposition to automating call centers and customer engagement and document review and so much, yes. But I think the really exciting, interesting thing is into the meat of it in finance. I would say in the meat of investing and trading and the like. Here's the tricky piece, though. If you're in asset management, the key thing you want to do is beat the market. There's a word people use in the markets: it's called alpha. Beta is called just the index. So how do you create alpha? How do you create something if somebody else is also using AI? And what I say to students also, I say, now think of this: if you don't use AI at all, maybe you're the slow deer. There's an expression: you don't want to be the slow deer. You don't want to have negative alpha. So you might actually find there's this toolkit. This toolkit that I had up here at AI is you just need the toolkit to stay even to get your index, or you might say, "I should not be in active management at all, I should just be elsewhere."
But I think there's definitely great value proposition. For finance, a lot of finance is not JPMorgan or BlackRock. So for finance, a lot of finance also needs to have outside service providers, and there's a lot of value proposition to be that shop that helps do the RAG models—the retrieval-augmented generation—orchestration, data cleanup, and so forth. Anything that you can do to service other than the really biggest ones. If you're not $500 billion or a trillion dollar sort of market cap finance, if you're not Bank of America, JPMorgan, Blackstone, and so forth, you're really buying a lot of outside services and vendors as well. And so service this incredible—there is, you know, some people call it a bubble, whatever you want to call it—there is a huge C-suite investor imperative to be spending money on AI. So maybe what you are is you're the service providers soaking up some of that. Hopefully they get value out of it, but that's what I think.
That's great. Beyond AI, in the next 5 to 10 years, what kind of sectors or technologies do you expect to drive growth in the US market, especially the stock market?
What's going to drive growth in the US? I'm not giving investment advice here. My lawyers would tell me this is not investment advice. I think that we have a stock market right now that's riding a lot of AI momentum. And so it's really about how you position yourself in that. If you think that AI momentum is commercially justified—look, the US stock market is trading at a 31 trailing price-earnings ratio right now. The US stock market is 225% of our gross domestic product. You know, $30 trillion of GDP, $66-$67 trillion of stock market value. Great companies, but you know, part of it is just how do you position yourself because there's some risk there. What sectors? I truly do think AI is transformative. The sectors that you want to be invested in are the ones that aren't overvalued, that somebody doesn't realize, "That's the sector that's going to get transformed by AI. That's the company that's going to get transformed by AI," that might not even be talking about it on their earnings call.
Great. Just as you mentioned, every company is investing very heavily in the AI industry. But there are still a lot of companies from very traditional industries, just like us—we raise 12 million pigs a year, hundreds of millions of chickens a year. So we are real farmers from Thailand. Do you have any advice for us?
Look, I think from your perspective, you've built a terrific, really remarkable business of retail and the 7-Elevens and the chicken farming and so forth. It's still customer engagement. You want to meet the customers where they want to be met, if it's human to human or whether there's ways that you can present yourself online that they can buy those chickens or buy the goods in 7-Eleven. Obviously, probably Alice could give you more advice than I could on this, but it's really how you engage with the customers where they want to be engaged. But it's also about inventory control. I mean, it's mundane things: your growing cycle, and you know, Ed Lorenz predicted the weather in chaos theory, the Lorenz attractors, but it's like trying to predict a little bit about that, too. But I would always be looking over your shoulder. I'd be looking over your left and right shoulder and say, "Wait a minute. Who's using AI in a transformative way that's going to disrupt me?" Because I don't want to be that one that's disrupted by somebody else. And so you'll probably overspend a little bit just on AI to make sure that you're—and I would let some people be entrepreneurial and be internal disruptors, even if they kind of offend some of your internal orthodoxy.
Amazing. And I remember you also told us only four companies put $300 billion into AI CapEx, like Amazon, Google, Microsoft, and Meta. Do you think those very large companies are becoming monopolies in the AI industry?
Well, look, here's what I think about it. Those companies have remarkable balance sheets and remarkable cash flows, so they can so to speak afford the spend. They're not borrowing money. It's not like a debt-induced—I'm saying if this is a bubble, I didn't say it was, for the record, but if this were a bubble, it's very different than some of the others. In the mid-19th century, there was a huge bubble about railroads in both the UK and the US, but it was on the backs of borrowed money and debt-induced bubbles, which is what we had in the US in the housing bubble that went into '08. And we exported our problems to many of your countries. We did, we did. We should own up to it. Debt-induced bubbles are different. There may be some risk in the data center world, and some remarkable companies, the really innovative, creative companies like CoreWeave and others, they've done some really remarkable things, but I'd be sort of looking under the hood about the debt side of it.
Where do you think the opportunities lie for new startups?
Wait, opportunities for startups?
Well, I think there's tremendous opportunities for startups, and many of you go off—I mean, some of you already have them and everything like that. I'm going to mention two. One is service providing. If you're really good at tech and you're really good at APIs or you're really good at math and everything, being that service provider to finance. Even the biggest incumbents are outsourcing a bunch of stuff, but all the middle tier and all the small tier, the small hedge fund, the small fintech company, they need those service providers. I think there's tremendous—I have friends that have stood up things and they already have nice annual run rates just on providing RAG services or orchestration.
In finance itself, in core finance, I think it's in that middle big bucket. I don't want to take anything away from Alice and everything about the customer side and so forth; it's huge. But what interests me, and I think—just take Alibaba. Six years ago, Alibaba was commercializing, monetizing their data off of all of their merchant customers—the 100,000 or million merchant customers, the numbers are astounding—and figuring out how to lend money to them using AI. This is six and seven years ago: how to use AI to commercialize that. I think that there's something out there. Somebody's going to create a nice little private credit shop to lend to small and medium-sized enterprises. Lending. Now, there's a data problem: where do I get the right data? I don't have Alibaba's data, and Amazon's not going to sell me their data maybe. But I just think there's a lot of opportunity. I would be worried if I was a regional or commercial bank in the US. Like, what's my—I used to know my customer base better than anybody else, but maybe I don't know them that well if data and AI analysis—there is a little bit of—so much of this is—I don't think it's that hard. You had a bunch of panelists say figure out what the gap is, what the problem is. I agree with that. But I think in finance it's often, "All right, I see what the problem is. I see the wide spreads, the wide margins that the banks are charging." I mean the huge margins in Brazil, huge wide margins down in Brazil. That's why it's very fintech-rich, because fintech figures out a way to get in those margins. But it's the data side: how do I get some data that might be proprietary, legally get it?
Regarding the risk of data, because there are a lot of misinformation and deepfakes posing new risks for this industry, how should regulators respond to those challenges?
Look, it's a challenge. One, it's a challenge in the commercial world, in the market world, the regulatory world: fraud, manipulation, and so forth. But AI is not new; it's a new tool for the threat actors to do. That's why I was kind of having fun with that one slide. That's how I thought about it when I was at the Securities and Exchange Commission. But as people in the commercial space, somebody could use it against you, too. They could pretend to be you personally, or your business, or your gaming app, or this app. They can try to do that. And I certainly had it when we were at the SEC. I mean, there was one time somebody put up a deepfake about the Pentagon blowing up, the US Defense Department, now called the War Department, and the market then moves. That's a real problem, obviously, that deepfake. So from a regulatory point of view, I don't think it's a new challenge, but the threat actors have new tools and those new tools can propagate so fast. But I would note—I was not alive then—if anybody wants to go back to something that scared the public and propagated, go back to the late '20s, early '30s: a radio broadcast that there was a landing of aliens in the US. This is a very famous episode that was put on, and people got really scared and jarred and everything.
On your last page, I remember you mentioned AI and geopolitics, because now—
Oh, geopolitics, yes. And also AI competition between countries, especially China and the US. It now feels like an arms race. How do you see the US coordinating with those countries, especially Europe and China?
