Why Kevin Carter thinks China is winning the AI race

0:00I'm Ashton Addison from the Cryptocoin Show and today we're joined with by Kevin Carter, founder and CIO of EMQQ Global and EMX ETF. Kevin has been building in the emerging markets index funds since 2014 and just in the last month his team has launched many new funds uh the China AI uh ETF and as of this week uh the China AI ETF is under AIC uh a broader bet under the whole AI

0:27stack. Uh there's a lot to discuss between uh western AI, Chinese AI, and where we're all at. It's moving so fast and uh you're the man that has some of the insights that I would love to dive into today. So thank you so much for taking the time, Kevin. >> Sure. Glad to be here. >> Yeah. So most people in AI or investing uh in in the West, they're looking at

0:50AI. They're trying to find where's where's the perfect place to be investing? you know, are we buying uh the the picks and shovels? Uh are we investing in the models? Are we looking at Nvidia for for chips? Uh data centers, power companies. Uh it's all exploding and some are higher upside, higher risk than others. Um, and I think as we are in this exponentially fast

1:16growth piece, um, there's a bit of noise and I think that's going to fade out over the next couple years and we'll see some clear winners in where the most uh, asymmetrical upside was. What's your take on where the money is right now in AI? >> Well, right now the money is is going into the infrastructure. And if you you know the best way to think about AI is

1:42the five layer stack and as you know the the bottom layer is power the second layer is chips the third layer is the infrastructure data centers and and those first three layers that's really the platform on which AI runs we had power before AI we had chips before AI we had data centers before AI but it's that fourth layer the magic layer as Jensen calls it the model layer that

2:06requires all of that capital expenditure And so it's that picks and shovels layer. And right now, you know, and and not just now, but over the last couple years, there's been anxiety about the the scale of the spending. And the hyperscalers have basically deployed all of their free cash flow towards building data centers. And there's a, you know, rightfully a lot of concern about

2:30whether that's going to pay off. But on the flip side of that, you have companies in Asia and in Taiwan, in Korea in particular, that the mag three of AI, TSMC, Heinix, and Samsung. And and they're they're making a lot of money. I mean, if you look at the earnings of those three companies between this year and next year, it's expected to be about $965 billion of

2:54profit. So, >> wow. the picks and shovels are at least in a you know profitability uh lens that they're the ones you know making all the money off of that spend. Mhm. >> So that that's a clear place the money is is being made and the models it's not clear any of the models >> anywhere are making money yet but >> that's one of the trillion dollar questions

3:15>> definitely and that's an interesting point because it seems like from an enduser perspective right now you know people are paying $100 $200 and they're getting PhD level inference and and coding for a month and I feel like this should be worth you know I should be paying tens of thousands for this how is the company uh not you know going bankrupt and so how do you how do you

3:40actually see that playing out in the the cost of uh tokens and the AI companies doing the modeling you know h how can they stay profitable in the long run and how will that work out >> sure well as you know one of the funds that we in fact the first fund that we launched uh uh as part of EMX ETF was the China AI tigers TGRZ which tracks the Chinese model So the again the the

4:05large language models, the models, the labs, whatever, whatever you want to call them, the US and China are the only real players. I mean they are the players. And in the United States we of course have open AI with Chat GPT, we have anthropic with Claude, Google with Gemini, we have other players. Musk has uh you know a strong offering as well. Um but most or indeed uh nearly all of

4:29our models are closed models. Now on the other side, you have the China models and you have DeepSeek, the one that most people know because it's the one that sort of rattled the cage on the US AI story when it launched, >> you know, 20 months ago in January of 2025. There was already a lot of anxiety about all the capex and Deepseek said, "Well, we made the same thing for $6.5

4:52million." And that really freaked people out. And I think Nvidia dropped 35%. And you know it started to question whether we needed to deploy that much money. But beyond deepseek which has continued to you know push the envelope you have the so-called AI tigers of China. Now these are six China AI companies all of which have come out of the Shining University computer science

5:18lab. This is a leading science lab in the world likely and uh those include Z.AI AI, which has gone public and it's part of the Tigers. That's Miniax, which went public in in January as well. So, those are the only two publicly traded large language models today. >> Um, and then you have Kimmy and the Moonshot or Moonshot and the Kimmy K3 model uh as well, which a lot of people

5:45know about. That was sort of the second deepseek moment. And the China models have a lot of advantages. They are uh openw weight and can be downloaded and run on premises so you don't have to, >> you know, log in and pay those expensive inference fees. You can customize them for your own use. And they're increasingly just as good and getting better. Um catching up with our models

6:09and they cost a tenth or even less the price. And and because of that, you're seeing them get used and not just used in China, they're getting used in the United States. Airbnb >> is built on chi Alibaba's model. Uh cursor which was acquired by SpaceX was built using China models. So the China models have actually passed the US models in terms of token use in the last

6:32several months and and I think that that's going to continue. >> Yeah. Well, I think uh at least end users in the west would be happy to be to be paying less and the fact that you can not have to pay the inference fees. You can download it. I feel like the blockchain industry and the crypto sector, these guys, they want more open-source models that you can own more

6:56or you can download, but maybe they just it's always been that matter of convenience. And I feel like they get caught up and be like, let's just use chatbt and give it all our information and and pay more because that's what other people around me are doing. I don't know if that's the the right way people should be going about it. Well, I mean certainly there is a

7:17convenience factor and and you know there there's going to continue to be use cases for both models, but you again as we saw earlier in this year when the token maxing you know became a a thing and then you know within two months when the bills started to show up then they started to do token minning and uh you know and when when the bills came and so

7:39>> um you're going to see a lot more open models and and you're already seeing that the open models are are be getting used more. You can use the china open models at you know AWS and and at Microsoft so that the host the clouding the host uh companies are are making them available. Deepseek even I think is available at Microsoft and >> and the moonshot people are working on

8:03revenue share deals with all three of our major cloud companies. So it's it's really early in this in the in the model race and of course >> there's been a lot of noise. I mean, you know, you you said there's been a lot of noise, but there's been an incredible amount of noise in the last five days with the, you know, the the push by by Daario and Sam to to get regulated and

8:26then Trump, of course, you know, responding it's a hoax. And so, it's it's a pretty heated moment right now. And with Sheis and Ping coming to visit next week, I I think we'll see more fireworks uh in the next couple weeks. >> Definitely. I think we're going to be seeing a lot of headlines about China AI and that's why this this conversation is is very timely and there there was also

8:50uh you know uh an announcement of some sort from the leading like government bodies in the US putting out a advisory for the the Chinese models saying there was distillation whether they were basing it off the American models or you know there's I just putting out a warning but you know the government loves to put out warning warnings. Um what what are your

9:13thoughts on should people in the west be cautious about these China AI models and and from what aspect of that? >> I don't think there's any reason to or need to be cautious on these China models anymore than any other uh providers models. Um in in terms of the question of distillation, I mean look the the you know the entire AI industry is based on distillation. I mean they

9:39distilled everything off the internet and and >> by the way they've been sued by lots of people whose whose IP was you know stolen or distilled. Um and distillation is also a common practice amongst our our labs and uh I don't you know I can't speak to the veracity of some of the claims of distillation but I don't think it's I don't think it's a long-term

10:04issue. >> Yeah. No, I agree. And it, you know, you can put it out, you can see the warnings and and you can then take a look at the west western models and yeah, they're based off of scraping our information off the internet and also the information that we're freely giving them. You know, when we check the terms and conditions box um that they're learning from whatever we say to make

10:26themselves smarter and uh building their own models, you know, build the frontier is in a recursive uh build, so it keeps building from itself. And there's been discussion around that recently that that is part of the the issue that it's moving too fast because of the the recursive uh training. What are your thoughts on that? >> Well, I think that it's um it's good

10:51that again there's just so so much happening in AI so quickly. It's hard for anyone to really keep their their arms around. But I think that the move that that basically started last week. I mean, you had the the guy that quit and said, "We're going to everyone's going to die in five years and no one no one's taking it seriously." And people had done that before, but for whatever

11:12reason last week, it did sort of jar, you know, the the main players in this, Daario, Sam, and and Elon to to agree that we really should have some procedure to to to, you know, um review at least the the models before they're released. And this makes a lot of sense. Um, you you also had on top of that, you know, the

11:39uh Daario calling for government regulation to slow down and they got they got pushed back pretty hard by the president and and by Sachs and uh and they basically said, "Look, do it yourselves. Figure it out." And Elon had been calling for this previously. And and you know, the idea is look, all of these guys are in their tuttle, right? They're doing their thing. they have

12:01their models, they're they, you know, you just get locked into something and sometimes it's good to have a fresh set of expert eyes come in and review and look. It's like proofreading, you know, if you're writing a book or something, right? It's good to have other people come and take a look at it and, you know, give you a reality check. So I think that those efforts seem to be

12:20moving very quickly and I think that's a a good place to to at least try to minimize uh you know risk associated with things like like uh recursive alerting. Um and and importantly you also saw Elon Musk in you know has been saying you we need China to be involved with this as well >> right the Chinese models also need to participate in this sort of industry

12:46group and >> and that's why this this summit that's coming up >> uh a week from tomorrow with with the president and and Xiinping this could be one of the most important summits in in modern history I mean there's a lot going on >> a lot of people are framing this as a as a race as a battle between AI and China. And I I think that's the wrong way to

13:10think about it. I mean, this is a wave, right? Nobody nobody won electricity, right? It's we all won. So I think that uh if the US and China because we ultimately we were the two main superpowers to start with and we are clearly the two AI superpowers >> and I think it's very important that we have some uh alignment and and safety uh considerations

13:38um and and some sort of apparatus put in place uh so as things continue we can you know better keep our arms around Yeah, it's a great point, Kevin. And to that about limiting the recursive models and and people considering it a battle between the US and China, part of the thought was that if we do limit it, then China's models are going to get ahead

14:03and and to your point there about everyone wins when there's electricity. Do you think that that's an issue uh with China models getting ahead or does it matter whose models are better? Well, they they here's what I would say. First of all, I think that the reality is and one of one of my heroes is this man Nunda Nilakani who's one of the founders of of Infosys, China's or India's

14:28largest tech company. And as he has said for a long time now, we don't need the models to get any better for 10 years like for for the vast majority of things that AI can do, it's already good enough. And it's more about figuring out for companies to figure out how to use it, right? They don't need the the latest version of of of you know, claude or the latest version of OpenAI's models

14:54to do almost all of the practical things that need to be done. So there will continue to be this race or you know just drive to improve models, improve efficiency. That's one of the other things that the China models have become is a lot more efficient largely because they were forced to because they didn't have access to the, >> you know, Nvidia's leading chips. And so

15:16they've been very um uh uh crafty in in terms of finding ways to tweak the models and and and the and the hardware so that they can compete. And it it it very well may be that China models will catch up with ours. I mean, they're pretty darn close now. Mhm. >> Uh I know last or a couple of months ago someone tweeted to Elon about when would the China models catch up and his

15:45response was first quarter of 2027 and the founder of Z.AI responded probably sooner. So [laughter] look, China's got more AI patents by a lot. They have more AI scientists. A lot of the leading scientists in the US labs are from China. >> China leads in almost every leading technology. So uh and you know even Jensen Wong has stated that he thought

16:14China was going to win AI. Now he got um booed basically by the media after that and Nvidia had to put out a press release. But you know China's very capable and I and again I don't I don't think we should think of it as a race. >> Yeah. But I think that China's very likely to end up leading in AI as they lead in almost everything technology at this point

16:40>> other than >> other than EUV >> um the extreme ultraviolet lithography which is what makes you know TSMC and and Nvidia H you know C um that's the the real machine that powers the the advanced chips which comes from the ASML in the Netherlands. >> Yeah, I'd love to jump back into the ETF and sort of the China AI models that are

17:08in there. You know, we've mentioned and and people understand on from the end user, it's it's much cheaper uh much much cheaper and the production of the models was at a fraction of the cost as we saw with with the Deep Seek uh you know 6 million versus hundreds of millions. I don't know what the exact amount it had cost OpenAI at the time, but when you compare those numbers, how

17:31much people are paying versus how much it costs them to make, what does the profitability look like for investing in these companies versus investing in the US companies, which you know, we we've seen people in San Francisco are dying to get equity in some of these private companies, you know, selling their uh San Francisco Bay house to to get anthropic stock. Um but

17:52in terms of the profitability and long-term profitability importantly also how does that look like for the models in the ETF? >> Sure. Well, so the the the the Tigers ETF, TGRZ, which is the China's models, which right now there's three holdings in this. It's a very narrow group of companies. It's a very volatile group and and they're not profitable and

18:15they're and they're they have just like our labs, they have a lot of revenue growth. um they think they can you know find a way to profitability but but right now it remains a big question mark. So these are you know amongst the riskiest investments you can make right now or especially are these China models. Um and again the the volatility you know reflects that. Um

18:37now we also have AIC which is the China full stack ETF. So that's not just the models that's where you get um power. So, CL um contemporary ampric which is a leading battery company in the world um in the on the chip side you know everyone knows Nvidia and Intel but they probably don't know high they probably don't know Montage Technologies they probably don't

19:02know you know the the China's leading chip companies that China has its own group of companies that are competing with Nvidia now and AMD um two of those four companies were founded by Nvidia's China head and AMD's China head. So they're, you know, they come with good pedigree. [snorts] Uh you have optics uh makers which China leads the world in optics. You've got Eoptolink

19:26for example, Inolite the other leader. Um and then the models which we talked about and and then finally you get to the application layer and that's really the the most important layer is how do we take all this other stuff and create value with it and that's where everyone's early, right? you have only a few sort of AI native um apps, cursor for example, that

19:51has been acquired, but there's no great example yet of of of an application company. And one could argue that it's the applications, the super apps of China like Tencent and its WeChat app that will ultimately win at the application layer, as may Apple here in the US at some point. Mhm. Yeah. We'll see how that plays out with uh Apple and Google. I feel like they've they've been

20:18a little bit behind compared to uh some of the, you know, the the the two main ones uh in the US. Um and I don't know uh how the China uh US race will fit into that, but uh I'm eager to see, you know, they really own the devices that everyone is using. H how will they take back the control of uh on the AI front? >> Yeah. Well, ultimately, you know, you

20:46need distribution and if you've got the billion people holding a device that you made and runs on your software, that's a pretty good h head start. That's another reason why Tencent I think remains very interesting. It's got one and a half billion people. Tencent's main uh business is WeChat, which is like the Facebook of China and other parts of the

21:05world. and and so they have a great and they're already deploying it. I mean they, you know, we talked about this before, but the QClaw, which is their um OpenClaw agent, is is available to all one and a half billion people on the app now. So um but we're I think we're we're still pretty early in that application layer. >> And of the the AI models, you know, Deep

21:29Seek and Moonshot, the these are also still earlier stage private companies from what I understand. Does does the future of the ETF profitability or where you see it depend at all on how quickly these companies grow and if they go public? >> Well, so um right now you could say the three leading labs in China are Deepseek, Z.ai and Moonshot. And uh Z.AI

21:57is public. It's the largest holding in TGRZ. Um Moonshot is an interesting story. Moonshot was actually founded by a quantitative hedge fund that happened to have a lot of um Nvidia chips for their for their money management business. Um the founder was a sort of a a math prodigy from China who who wanted to become a quantitative hedge fund and he did that very successfully. But they

22:22never took any outside funding until just a couple months ago. They raised $7 billion and the founder put in three billion of his own money. So his hedge fund's obviously doing pretty good. So, they are moving towards an IPO which should happen in the early 2027. >> And then Moonshot and the Kimmy app, they may go public this year. They've already, I think, started to file in for

22:44a Hong Kong IPO. Um, and so um we'll add those uh as they IPO. We may also u we'll the fund has the ability to invest up to 15% in private preIPO companies. And so as the fund scales up, we'll look and see if that's an opportunity we can find as well. >> That's exciting. And what do you think are the the thoughts of, you know, US

23:11investors uh maybe not ones that are specifically focused on AI, but branching out into more alternative investments like like the China models? Do you you know do you think they is there a sense of nationalism or misunderstanding that um maybe there's upside but it's scary territory to invest uh in these models that are competing with the US. >> I think that people in the United States

23:40in particular a lot of them have biases against China. The one thing I've learned investing in emerging markets because I you know we don't just invest in China, we invest in India and [clears throat] Brazil and you know any emerging or frontier market is is part of our universe. It just so happens in the case of AI there's really only two players. It's the US and and

24:01and China and then Taiwan and Korea which are emerging markets are are making hardware but they're not really in the the real you know part of the story. Um but but the one the the thing is most people have never been to China, right? They they've they've seen headlines, they hear stories because it's communist, people assume, oh, it's, you know, it has all this oppressive

24:24elements. And I I think people would be stunned if they went to China. I mean, I tell people, especially if they're young and mo, you know, don't have a a family and a dog or a cat, you know, to kind of hold them down. It's not hard to get to China, and it's quite cheap when you get there. And it's amazing. It's a really the most advanced country in in many

24:45many ways. I mean, this is a terrible analogy, but you know, if the aliens decided they finally wanted to land on the on the planet and >> talk to the leaders and they sort of scoped out, you know, which country just looking at the cities, it's pretty clear they'd probably go to Chongqing or Shanghai >> because I mean, these are uh incredible places. So I I I recognize that there's

25:08a um fear level that people have with China, but I think a lot of it's unfounded myself. >> Mhm. Definitely. Yeah, I have been I spoke at a blockchain conference there nearing 10 years ago now uh in Beijing. So I did get the chance to experience it, but I know it's so big that was just one dot on the map. So, have you personally, you know, as you're talking

25:34about China, visited the the companies or the warehouses and and talked to them and and do you think that's an important factor for building this fund and and presenting it to us investors? >> We haven't met with all of the companies, but I have spent lots of time on the ground in China over the last 20 years since I got involved. Um um and uh you know for most of the last

26:03um including still today our primary focus has been on the emerging market internet sector right I mean I I launched the first China technology ETF in 2010 with >> which has a ticker CQQ so that was my first launch of a a emerging markets tech focused product and that was in 2010 so 16 years ago So um um but but starting around uh 11 years ago you know

26:33what I realized was all the things that were happening in China with Alibaba and Tencent those things were starting to spread. So >> I launched EMQQ which is our our sort of flagship fund which does emerging markets internet. I launched that to capture things like Marcato Libé, the Amazon.com of South America, >> um, companies like C Limited in Southeast Asia. So, I've been focused on

26:59that, you know, the technology in emerging markets from the time it basically started before there were smartphones basically. Mhm. >> So um I uh but I haven't made a trip specifically to go and visit a lot of these hardware companies which are part of the uh the EMX portfolios the the AI focused portfolios. Mhm. What are some of your thoughts or predictions on uh how not that there's a

27:30a race, but you know the AI race moving into 2027 and you sort of referenced that that one tweet uh from the Z.AI and Elon Musk, but are there any other thoughts and predictions on on how the models will evolve in in each of the countries by next summer? Well, I mean, one thing that is just incredible about this AI thing as compared to say the internet.com thing,

28:00the the speed and um breadth of developments, it it's staggering. I mean, consider this. A year ago, if you asked almost anybody, a open AI was winning, right? that that was the US model that was going to you know was the leader and then now less than 12 months later every people are saying well

28:27anthropic's worth twice as much as opening some some people have said that and >> but but consider this one of the main reasons Anthropic has leapt ahead is the coding product which wasn't even a plan it was a product that one of the engineers made for his own use. >> Mhm. >> In his spare time and a couple of his buddies borrowed it or wanted to use it

28:52and all of a sudden it's the biggest one of the biggest parts of the company. And that started that's been this calendar year >> that that happened. So trying to predict where it's going to be, you know, a year from now is is quite difficult. Like I guess I would I would [snorts] probably pretty safe to say we'll have more US open models, >> right? We're already seeing

29:17>> that. I guess that's one prediction I would make that there will be uh more um open models and I think there's going to be lots of other smaller models and more use case specific models but um uh as as you know as we've touched on it's everything's just happening so fast in fact Disab and he's now the chairman the deep mind

29:49part of Google. um he was interviewed a a couple of months ago and after he gave a talk actually and then they had a Q&A afterwards and the first question was what advice would you give to a college graduate right that's coming into this AI world and he said the same thing everybody says he said I would learn how to use all the different models I would

30:12become the best at prompting I would just make myself really good at using AI now that was a pretty standard question but then he made the following comment. He said, "You know, I don't even know what's going on because I have a job. I can't keep up with the models that have already come out, let alone the five or 10 new things that are going to come out

30:33today." So, everybody's sort of in this whirlwind and it's it's hard to make predictions because things are going so quickly. >> Definitely, I agree. And there's going to be a lot. We just don't know what they're going to stumble upon. uh and and then that's going to take off and that will be the thing like you said about about the coding product um and uh

30:58with the so with the the fund what's the best way for people to learn more about the the fund and and access it for for US investors. >> Sure. Well, uh EMX ETF is the the website. That's EM is in emerging markets X and then ETF and then uh you'll see the AIC which is the full stack China. So it's a 24 company you know top to bottom portfolio of Chinese

31:29AI companies and then the Tigers TGRZ you'll find and again that's just the the currently three leading companies in the model space. Um >> that sounds great. Well I'm I'm definitely going to be looking into it and following it. Uh it's there there's an opportunity that you know I feel like a lot of US investors that are dying to get into US AI companies that are

31:53already a trillion dollar valuation. Um and there there's other opportunities outside of this country also that are not at a trillion dollars yet and they have potential upside. uh and I think you know whether it's nationalism or misunderstanding of of other cultures and what's going on in other parts of the world uh might limit people from having uh potential bigger uh returns

32:18elsewhere or at least better diversification of their portfolio. So, I really appreciate your uh your insights into the the global uh AI growth and what we're seeing outside of the US. And I feel like not enough people are paying attention to this yet. >> Well, it it's not going away. [laughter] >> That's for sure. Well, thank you so much, Kevin, for taking the time. I will

32:43leave I'll leave a link to the to the to the platform and and all of the other ETF information as well and for EMQQ Global in the show notes below. And would love to follow up in the near future. Uh there will be much more to talk about in in the next AI uh with updates. you know, you we could be back next week and and there be hours to talk about, but um when there's more on on

33:08the Tigers ETF, I think that's a a great uh part to to follow as these other China AI companies grow and see how those ETFs evolve. So, congrats on on the launch of that and looking forward to following up in the near future. >> All right. Thanks, Ashton.