Chinese AI Just Made History

In this episode of Motley Fool Hidden Gems Investing, Motley Fool contributors Jon Quast, Matt Frankel, and Rachel Warren discuss:

• How the World Cup drove adoption of prediction markets.
• The difference between investing and gambling.
• How China’s Kimi K3 model could disrupt the AI space.
• Whether Nvidia stock could be a hidden beneficiary.
• Mailbag: The outlook for digital advertising.

To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. When you're ready to invest, check out this top 10 list of stocks to buy.

A full transcript is below.

This podcast was recorded on July 20, 2026.

Jon Quast: Chinese AI just made history. You're listening to Motley Fool Hidden Gems Investing. Welcome to Motley Fool Hidden Gems Investing. I'm your host today, Jon Quast, and I am joined by Foolish contributors Matt Frankel and Rachel Warren. Today on the show, we have multiple topics. We're going to be talking about that lead Chinese AI. We're also going to take a question from the mailbag regarding digital advertising.

But first, we want to talk about what happened yesterday. Millions of soccer fans around the world watched Spain defeat Argentina in the World Cup final. I think that we were all just moved throughout the tournament, as many people from around the world visited North America and shared their experiences online. That was so much fun. But one of the things that maybe we didn't hear about was how much the World Cup has really propelled adoption for the predictions markets. Kalshi specifically said that they got 3 million new users during the World Cup. Clearly, that is pushing this whole space forward. Rachel, I want you to talk about where we're at competitively in the prediction market space because you have companies such as DraftKings and FanDuel out there, but you also have Meta looking to get in on this space. What can you tell us about how this market is growing and how these companies want to profit from it?

Rachael Warren: Trading activity that we saw around the World Cup final with Spain's victory over Argentina, that was one of many examples we've seen that sort of are serving as proof of concept for sports event contracts, which if you're not familiar, these essentially treat match outcomes like peer-to-peer financial derivatives rather than traditional sport wagers. Kalshi, which you mentioned, Jon, they cleared about $1.9 billion in trading volume on the final match alone to understand exactly how this works and where it differs from, say, traditional gambling, so traditional gambling tends to involve an individual wagering directly against a bookmaker, for example, who profits from their losses. Event contracts like these operate as an exchange where peers trade financial derivatives against each other, and then the platform collects a flat transaction fee. Kalshi, for example. Now, because these contracts are legally classified as commodities, they actually fall under the jurisdiction of the Commodity Futures Trading Commission or the CFTC instead of state gaming boards.

That's a very important distinction because it essentially allows these prediction markets to bypass the state-by-state licensing laws and heavy gaming taxes that the traditional sportsbooks have been forced to navigate. Obviously, there are some vulnerabilities in these business models; you tend to see trading volumes and even liquidity plummet on some of these cultural events wind down. But you're seeing a lot of the big tech and legacy sportsbook players deploy their own opposing strategies to try to capture and retain the user engagement that they're seeing these platforms like Kalshi and others capitalize on. Talked about recently how Meta Platforms, they're entering the space with their internal application at the code named Arena. Is essentially an AI-driven non-monetary framework. Because of that, they're able to bypass really strict financial compliance rules and capture engagement data from their billions of users and avoid a lot of the regulatory friction.

You've got the traditional players like DraftKings and FanDuel which you also mentioned, Jon, they're dealing with severe margin compression right now. They're launching their own low fee event contract products to try to really protect those embedded customer bases from churning to those lower cost financial platforms like the Kalshi of the world. We're seeing this towards event contracts, if you will. That's the term very much this asset-light exchange model. This is a market that's expected to approach $1 trillion by the end of the decade. There's a lot happening in this space and a lot to watch, whether or not you participate in it.

Jon Quast: Matt, I wanted to bring this topic to the table today because of a Kalshi study that came out fairly recently, and it really bothered me personally. According to the study that Kalshi released, 89% of people say that buying stocks or mutual funds isn't gambling. That's fine. But the majority of the people in the study also felt like predicting on the outcome of events, like what we're talking about, such as Spain versus Argentina, predicting the outcome. Most people also view that as not gambling. That's such an interesting thing. For most people out there, according to this study, they would view it fundamentally the same investing $100 in the stock market and betting $100 on the outcome of an event, such as Spain winning. What I want to talk about here with you is, what do you think about that? Is it fundamentally the same thing, or is it different? Because I think for some people, the idea is I have to research the two teams that are involved in the game, so there's an element that I don't know the future, but I've researched to make an educated opinion about the outcome of the event. For some people, that's no different than investing in a stock.

Matt Frankel: I understand why people might feel that way. I understand the appeal of the projection markets, especially after watching that game. One hundred and fifteen minutes with no scoring. You need a way to make it interesting. I understand why people feel that way, but at the same time, the key difference is whether the underlying asset you're talking about is expected to compound in value over time, rather than just settle in a binary zero-sum matter. Buying a share of a business, it gives you a claim that hopefully, not always, but hopefully will grow earnings, they'll reinvest capital, they'll create value for you over time. Even if you're wrong about the next quarter, your investment goes on. On the other hand, the stock market, it's a positive-sum game. Economic growth, productivity, innovation, reinvestment, they can all make everybody richer over time, and over the past, they have.

On the other hand, a prediction market, it's a peer-to-peer market. It's a zero-sum game. For every dollar someone won betting on Spain, excuse me, predicting on Spain, someone lost it on Argentina. No new value was created there. If anything, value was lost because Robinhood and Kalshi take their cut. Money just moved around sideways. The general rule here is, if you can lose 100% of your money, because of a single expected event that an event that's going to happen one way or the other. You're speculating, not investing, regardless of what Robinhood or Kalshi might call. That's true in the stock market, as well, if you buy an out-of-the-money call option. It's a binary event. It's the same idea here. Yes, they are securities in that sense, but they're dependent on one binary outcome event. That's the really big difference between buying a stock and predicting on the outcome of an event.

Jon Quast: To anyone listening, there is some entertainment value, perhaps in the prediction markets, and certainly we wouldn't want to tell anyone out there that you should definitely avoid it at all costs. Maybe there's a case where you can use it responsibly. But I think for me, it's really important to remember that we are talking about two fundamentally different things and to keep those separate in our minds. In one category, we're investing for the future, another category, we're maybe playing around with a little bit of money. That could be OK, but they are different things. Keep that in mind. Well, come up after the break. We're gonna talk about how China is disrupting the AI market. You're listening to Motley Fool Hidden Gems Investing.

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Jon Quast: Welcome back to Motley Fool Hidden Gems Investing. In the last week, something massive has happened in the AI world. According to ana.ai, a model called Kimi K3 has jumped to the top spot among AI models. It's ahead of Anthropic's Claude Fable 5. It's ahead of OpenAI's GPT -5.6. Rumors are that it is three times cheaper to run than other models. That claim alone right there is absolutely astounding. Rachel, here's my question: Does this change the game in AI? Because from my perspective, if businesses can use a cheaper and better model out of China, then of course, they were going to adopt it, and if they adopt this model, then that means that they're moving away from other models, and maybe that impacts the economics of some of the top AI providers in the game right now.

Rachael Warren: I'm not going to downplay the fact that we're seeing immense technological and AI advances coming out of China. We've seen a lot of really impressive models rolled out in recent months. But I do think it's an oversimplification to look at the launch of Kimi K3 and say that that might defeat the likes of OpenAI and the Silicon Valley-backed players. There's a few reasons for that. I think a lot of the focus has been on the fact that the blueprint behind Kimi K3 is essentially free, but there's also very much the physical laws of economics and computing, you know, hardware is still the key bottleneck here, right, not the software. Kimi K3 is an absolute data monster with 2.8 trillion parameters. The fact that Moonshot AI, which launched this model, they had to freeze new user sign-ups just 48 hours after launching because their servers literally hit a physical limit. I think it continues to prove that the computing power behind all of these models that we're seeing continues to be a finite, scarce resource.

Even when that software blueprint, if you will, is free, running it safely at scale can be really difficult. It can be really expensive. I think we are still seeing a lot of the CTOs are still going to want to pay a reliable, secure subscription fee to the likes of anthropic or others to handle that key infrastructure challenge. Yes, we're seeing that a lot of the raw AI intelligence is becoming a cheap commodity. I think that will be increasingly so in the years ahead, but the Cloud infrastructure required to run it. Not so. I think that that could change through the years. But a lot of the business models, I think, for these closed providers like OpenAI, like Anthropic are safe because they're really selling those stable ecosystems that make that software usable for big businesses, and that's not something that's going to change anytime soon. That being said, I think there are a wide range of useful models out there. I think democratizing the space is important, but I do think it's important to understand that this is not going to just disrupt the dynamic of OpenAI and Anthropic overnight.

Matt Frankel: One thing that I would add is that having a capable AI model is one thing. Having a cheaper AI model is one thing. But having enterprises trusting in your product is another thing altogether. Cheaper inference for tasks, it doesn't automatically hurt companies like OpenAI and Anthropic. The highest value cases for AI need more than just raw text generation. The selling points are how these ecosystems are safety tested. They're reliable. They have other key features that enterprise clients want, like how Rachel described, selling the ecosystem. The bottom line, I don't think this changes the game. For OpenAI, Anthropic, and all the other ones. Having a capable but capacity-constrained rival, it really underscores just how the hyperscalers that have these large pipelines of compute that keep growing still have the clear advantage in this space.

Jon Quast: That's an interesting point to bring up here. Both of you have alluded to it already, but let's just make it explicit. Kimi actually had to pause new subscribers. It had basically when the news came out, that it was now the top model, and some of the people started coming out saying, hey, look at what we're doing and look at what it's costing us compared to the other models. There was such a surge in subscriber demand that the GPUs from Kimi could not keep up. They actually had to say, listen, we can't actually even take new subscribers right now. We're going to have to hit the pause button. We're going to invest in compute so that we can meet all this demand that we're seeing. That's a really interesting thing to think about. But what I got to thinking about in this was Nvidia, and I know we're the hidden gems steam, and I know that Nvidia is either the largest or second largest stock in the world, depending on the moment. But it trades at just 22 times forward earnings. That's actually cheap. Just last week, it started shipping H200 chips to China, which isn't really in the calculus right now. Now you have a Chinese model saying, hey, we're going to actually need to invest more in compute Nvidia just now starting to ship to China. Can we shift here to Nvidia stock for a second and say, Is there a case that Nvidia stock is actually a good buy right now?

Rachael Warren: I think that Nvidia looks like a really strong buy right now for a variety of reasons. Going back to this bottleneck that is obviously affecting players across the industry, but forced Kimi K3 to freeze subscriptions. That key pain point is where we're seeing that global backlog of guaranteed revenue for Nvidia come from. Companies trading at just about 22 times forward earnings last I checked. I would say, personally, I think the market's priced in a lot of AI fatigue, the geopolitical risk. I do think it's a really healthy entry point into a company that's still healthfully growing its data center revenue. It's interesting. That newly approved shipment of H200 chips to China. I do think there's a nice regional tailwind there. Nvidia’s broader growth engine is still the insatiable demand from the Western Cloud giants that are racing to host these huge, multi-trillion-parameter models. I think, if anything, we're seeing that Nvidia is continuing to dominate the market as tollbooth for the entire AI industry. I don't think that's going to change anytime soon, and it is operating off an incredibly robust financial foundation, really profitable, cash-producing business, which I think also very much lends itself to being a good buy for long-term shareholders.

Matt Frankel: I agree with Rachel that Nvidia, by most valuation metrics, looks very cheap, considering you said 23 times forward earnings, that growth rate that it keeps posting, and the H200 to China, it's a real growth lever and could be a serious near term hail wind for it. But I don't own Nvidia in my portfolio, not directly anyway. I have plenty of exposure through ETFs, and there are a few reasons for it. First, things like comparing that PE of 22 to the massive growth rate assumes that the growth is going to continue. That's what the whole basis for comparison is. It's not a realistic growth rate to maintain forever, for any company, not just one of the largest in the world. Second, Nvidia has a lot of customer concentration. They sell to hundreds of thousands of customers, but a lot of their revenue comes from the big hyperscalers. The hyperscalers themselves are starting to make in-house chips, a lot of times with the stated goal of reducing dependence on Nvidia, so long term, who knows what that's going to mean. Then the China approval, it's a policy decision, and as we've seen many times, policy decisions can be reversed and put back on and reversed and put back on several times. I'm not saying that Nvidia is not a great investment or a great business. I couldn't fault anybody for buying Nvidia right now, but it's not a risk-free investment, and it's important to put the attractive valuation into context before you buy.

Jon Quast: It's hard to argue with that, Matt. Thank you for always reminding us to think soberly about the stocks that we invest in. I'll definitely keep that in mind, but I am eyeing the video right here myself personally. After the break, we're going to take a question from our mailbag about digital advertising. You're listening to Motley Fool Hidden Gems Investing.

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Jon Quast: Welcome back to Motley Fool Hidden Gems Investing. One quick note, we want to make you part of the conversation. If you have a stock or investing question for anyone on this show, you can send those into podcast at fool.com. Our preference is that you keep them short, keep them Foolish, and remember that we can't give personalized investing advice, so generalized questions are better. But if you have a question for us, send those in at podcast at fool.com, podcast at fool.com. This question today we did like, and it goes like this. Some of the largest companies, Alphabet and Meta, make money mostly from advertising. Has that come from them taking market share of the advertising industry from newspapers and television, or has the total amount of advertising as a share of the U.S. economy grown a lot in recent years? Rachel, let's start with you here because this is a really interesting question. Alphabet and Meta are indeed advertising powerhouses. Combined, you're looking at a $6 trillion market cap. Just how big are the digital advertising businesses for these two massive companies?

Rachael Warren: It's really interesting because obviously this is what we know Alphabet and Meta for, but I don't think we often talk a lot about how that came to be. These are companies that combined generated hundreds of billions of dollars in revenue from ads in 2025 alone. Alphabet and Meta control about half of the entire global advertising market. For Alphabet, advertising accounts for about 70% of its total business, give or take, in a particular year. Meta relies on advertising for about 98% of its entire revenue. Now, what's interesting as you think about where all of this business came from, and you go back a few decades, it was sort of a mix of a few different factors. I very much, of course, drawing off a growth from legacy media, but also very much expanding the total economic pie, if you will.

If you look back over the last couple of decades, we have seen digital platforms carve out a lot of the local newspapers and television by offering these very highly precise data-driven targeting solutions that traditional media just couldn't match. The total amount of advertising as a share of the economy has also grown significantly because platforms like Alphabet and Meta also invented a brand new marketplace. They lowered the financial barrier to entry. Alphabet and Meta, yes, they obviously work with these huge brands, but they also allowed millions of small and medium-sized enterprises who could have never afforded multimillion-dollar TV commercial, for example, or a major print campaign. They allowed those players to buy these highly targeted hyperlocal ads, and that’s also been really critical to the growth of those businesses over the last few decades.

Jon Quast: Well, certainly, the targeting capabilities of digital advertising have changed the game in advertising. It's no longer just a billboard on the highway that you have to count on whoever drives past it and looking at it and making a decision off of that. Now we can actually target online with intent, all of that. It certainly changed the game. But, Matt, my question here for you is, did this actually increase the pie, or is it just that the pie shifted to digital channels?

Matt Frankel: Well, first of all, don't count out billboard advertising. One of the companies that offers it, Out Front Media, has been doing great lately. I've said before, it's the one type of advertising you can't click away or turn the page from. You're literally forced to look at it, so it has some advantages. But to answer your question, it's both. The pie got bigger. Global ad spending as a percentage of GDP has risen significantly recently. The reason is a lot of what Rachel talked about because digital ads are generally more valuable to advertisers. They target better, and they're just more efficient. They took a lot of market share as TV and print ads have been declining for the past two decades or so, and understandably. Alphabet and Meta didn't just win the old pie. They baked some new pie, as well, and they became the pie's primary baker to use your pie analogy there.

Jon Quast: Here's a question for each of you. I want you both to weigh in here. Based on the fact that you're saying, Matt, that the pie actually did get a little bit bigger here, it did shift, but the pie also did get bigger. Does the digital advertising pie keep getting bigger from here, and if it does, does that benefit these top two players? Or is AI going to come in here now? Many of these AI companies are looking to get into the advertising game. Is AI going to come in here and shift the whole digital advertising market and shift who the winners are? Rachel, you're up first.

Rachael Warren: I think it's a combination of things. I absolutely think the pie will keep getting bigger, but I think that you're still going to see the top players dominate. AI is fundamentally rewriting how ad money is spent. It's shifting a lot of the winning growth to who controls the back-end consumer data. Now, of course, that means that we’re seeing the likes of Meta and Alphabet succeed immensely because they have these huge capital reserves required to build the AI-automated ad infrastructure that these businesses rely on to survive, but also they have all of the data to fuel that growth. There's been a lot of fear these companies would see their business models completely crushed, but in fact, the AI-driven targeting tools have actually triggered an advertising boom.

Now, one thing I'll note, AI is changing the landscape in terms of how search and discovery works. We're in a time where conversational AI search tools are compressing the traditional process of scanning links. We're seeing generic web traffic shrinking. We're seeing a real relocation of ad dollars towards those more high-intent channels with direct transactional data. You go back to the big players that we're talking about here. I do think, you'll see new AI start-ups will capture a piece of the conversational search market, but I think that we're still going to see, at least for the medium term, the Alphabets and Metas of the world remain the dominant winners because their ecosystems and platforms are very well insulated against AI disruption and also closest to where consumers are making buying decisions and leaving that data that grows that AI flywheel in the first place.

Matt Frankel: On the near and medium term, I agree with most of what Rachel just said, but I'd push back a little bit on that duopoly framing. Just a few things to add here. No. 1, don't count out Amazon. Amazon's ad business, it's still not the biggest part of their business. Obviously, they have AWS. They have their e-commerce revenue. It's rapidly becoming really a third major player in ads, and its ads sit a lot closer to the actual purchases you make than either Google or Facebook ads do. Not only that, many traditional retailers that have big ecommerce presence like Walmart, like Target, have also been quietly growing their own sponsored ad revenue. But the real wild card here is agentic AI when it comes to shopping. It has the potential, but it's not really guaranteed to ultimately disrupt the concept of a sponsored link entirely. The question of who gets paid when an AI agent clicks B, there's not really a clear answer there just yet. Who did the advertisement really go to? For a few reasons, I question whether alphabet and metas leads are going to be permanent, but directionally, Rachel's right.

Jon Quast: That is a huge implication here if sponsored ads are going to go the way of the dinosaur because there are a lot of platforms that rely on that, but I'm afraid we're going to have to hit that topic on another day because we're out of time.

As always, people on the program may have interest in the stocks they talk about, and The Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. All personal finance content follows Motley Fool editorial standards, and it is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. See our full advertising disclosure. Please check out our show notes. Thanks to our producer Kristi Waterworth and the rest of The Motley Fool team. For Matt, Rachel, and myself, thank you so much for listening to our show today, and we will talk to you again next time.

Jon Quast has no position in any of the stocks mentioned. Matt Frankel, CFP® has positions in Amazon. Rachel Warren has positions in Alphabet and Amazon. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Nvidia, Target, and Walmart. The Motley Fool recommends Flutter Entertainment Plc and Outfront Media. The Motley Fool has a disclosure policy.