US–China 'co-opetition' instead of a race

Every panel on AI and geopolitics seems to default to the same cliché: “the US–China race.” In this episode of Differential Understanding, I wanted to sit with someone who has actually lived inside DC, Silicon Valley, and the US–China tech corridor, and ask whether that framing still makes sense.

My guest is Kevin Xu, founder of Interconnected Capital – a global hedge fund focused on the picks and shovels of AI – and author of the Interconnected newsletter, which sits at the intersection of tech, business, and geopolitics. Kevin’s path runs from Obama campaign staffer and White House / Commerce Department comms to GitHub’s international expansion lead, and now to full-time investor–writer with a very explicit geopolitical lens.

We start with why he insists on “thinking in public” as an investor, and why he believes ideas soulocking in a vault. From there, we dive into his critique of the “race” narrative and his alternative concept of US–China co-opetition – a messy mix of competition, cooperation, and outright co-opting of each other’s models and research. That leads naturally into China’s open-source AI ecosystem, the Manus–Meta deal, and what he would need to see before feeling comfortable owning the upcoming MiniMax and Zhipu IPOs in Hong Kong.

In the second half, we zoom out to sovereign AI: why South Korea might be one of the few countries outside the US and China with a shot at true full-stack AI sovereignty; how to read OpenAI’s Stargate initiative as an explicit American export play; and why the Gulf – particularly the UAE – is emerging as an AI “swing vote”, combining abundant energy, sovereign wealth, and a 1.5 million-strong construction workforce into a potential global compute hub. We close with Kevin’s differentiated view on China: AI diffusion is far more visible there, but the economic impact is not necessarily greater, and Beijing may end up being the first government forced to confront AI’s social implications.

In today’s world, there’s no shortage of information. Knowledge is abundant, perspectives are everywhere. But true insight doesn’t come from access alone—it comes from differentiated understanding. It’s the ability to piece together scattered signals, cut through the noise and clutter, and form a clear, original perspective on a situation, a trend, a business, or a person. That’s what makes understanding powerful.

Every episode, I bring in a guest with a unique point of view on a critical matter, phenomenon, or business trend—someone who can help us see things differently.

For more information on the podcast series, see here.

Timestamps (chapters):

* 00:57 – From DC to GitHub to Interconnected Capital

* 02:39 – Why Kevin “thinks in public” and writes Interconnected

* 04:44 – US–China AI is not a “race”: co-opetition explained

* 09:27 – Open-source / open-weight AI as last bastion of global cooperation

* 12:14 – Capital flows, decoupling and why “capital finds a way”

* 15:36 – Manus x Meta: product quality, viral growth, rationality in AI

* 19:40 – MiniMax & Zhipu IPOs: revenue reality vs AI lab hype

* 24:39 – Can Chinese labs win the Global South with cheaper AI?

* 27:09 – Sovereign AI 101 and why South Korea looks uniquely powerful

* 32:03 – Stargate as de-facto US sovereign AI and export strategy

* 34:44 – Kevin’s trip to UAE: Gulf AI strategies and the “swing vote” thesis

* 40:06 – Sovereign funds, MGX, and attracting talent from Hong Kong & beyond

* 44:18 – Non-consensus bet: UAE Stargate as a global compute hub

* 46:57 – Differentiated views on China AI diffusion and economic impact

* 51:29 – Embodied AI, “aunties pressing elevator buttons” and social risk

* 55:01 – Robotaxis, delivery drivers, and why China may go slower than expected

AI-generated transcript

Grace Shao (00:00)Hey everyone, welcome back to another episode of Differential Understanding. This is your host, Grace Shao And joining me today is Kevin Xu

Kevin Xu is the founder of Interconnected Capital, a global hedge fund focused on the picks and shovels of AI. He writes the Interconnected newsletter on SubSac, which covers tech, business, and geopolitics.

His insights have been frequently cited by the New York Times, Bloomberg, Economist, CNBC Information, Financial Times, Wall Street Journal, among many other media outlets. He previously worked as a senior executive at GitHub, the world’s largest developer platform, and served in the White House and Commerce Department during the Obama administration. He studied international relations at Brown University and law and computer science at Stanford.

Grace Shao (00:40) Hey Kevin, thank you so much for joining us today. I already introduced you, but for listeners who may not know you that well, can you introduce yourself, the different hats you wear today, running Interconnected Capital, writing Interconnected Newsletter, and operating at the intersection of US, Asia, tech, geopolitics, and investing.

Kevin Xu (00:57) Yeah, first of all, thank you for having me. So as you mentioned, what I do currently during the day is I write the interconnected newsletter on the intersections of geopolitics, technology, and business. I also run my own long only fund called Interconnected Capital, focused on the picks and shovels of AI, both hardware and software. Prior to that, I actually work as an operator inside multiple Silicon Valley tech startups. The most recent one is GitHub, which is the Microsoft-owned developer

platform. I was their lead for international expansion strategy. That was my most recent real job, if you will. I also spent a bunch of time at different startups of varying sizes. And before that, actually started my career in politics. So I joined the first Obama administration’s campaign back in 2008. I was a campaign staffer. That was my first job out of college and then moved with the campaign team to DC, ⁓ worked in a few different roles.

in the Commerce Department as well as the White House doing mostly press and communications work. So that is ⁓ my sort of all over the place background that led me to what I’m doing today, which is investing and writing ⁓ in technology, but with a very heavy geopolitical lens to the process.

Grace Shao (02:13) I think that’s really interesting and explains to why you have a geopolitical lens, given that you actually have a DC background, right? But you run a fund and you actually keep most of your thinking, public, So instead of just keeping it mostly all private, which is what most investors do, why do you publish a very opinionated, very insightful sub stack and, share it very, I think generously with the public?

What kind of conversation gap are you trying to fill when you start the interconnected newsletter?

Kevin Xu (02:39) I think there are two elements to that. First is that this is more of my Silicon Valley ethos, which is that no idea is that worth keeping in secret. It’s all about the execution. Like I’m not, I didn’t come from a Wall Street finance background, right? Where a proprietary trading algorithm or some secret information you got from a meeting is this big trade secret that you want to lock into a vault inside Goldman Sachs or whatever. And that’s going to make you billions of dollars. That is not my approach to investing.

I think thinking in public, sharing in public, and really getting the feedback that I get from writing is much more valuable than keeping all these thoughts in my head as if they’re the next best thing since sliced bread. When you actually write it down, when you put it out into the internet, half of them are good, half of them are actually crap. And I use writing and writing in public specifically basically as a canvas for me

to think better, to hold my thoughts more clearly. I think knowing how to think is the most important skill for any investor to be able to succeed for the long term. And if any idea that I shared out there benefits somebody else, and you made some money off of it for free, so be it. Good for you that you actually understood some of the value from the writing, even perhaps more than I did as the writer. But for me, that’s not something that I keep very possessively as a trade secret.

Grace Shao (04:00) I really relate to that and I think exactly to your point you’re like writing everything down is the way of thinking through your thoughts sometimes it’s all jumbled up in there and then also people ask me why do you keep AI Pro all free? I was like well if it really benefits you you know I don’t really mind I’m not trying to make money off of like selling you know just my content but really the content is my thinking and to your point sometimes I put in so much work and then the result and feedback is so bad and then some things I just kind of like throw out there

And then it actually really sticks with people you never know. It’s really good to get the feedback from the public as well. Well, I think now I want to ask you about your journey into investing and really covering China and US. So you are based in the US, but you are Chinese.

birth, right? ⁓ So does that play into why you cover China-U.S. related work right now? And I do want to talk about your recent article, which you said you think calling the China-U.S. relationship in tech and AI a race is quite lazy. You said instead of seeing it as pure competition, you think it’s more of a competition. So cooperation plus competition. Do walk us through that and how you kind of came out with this frame.

Kevin Xu (04:44) Correct.

So just to put a finer print on it, as far as the personal history is concerned, I was born in China. I moved to Canada when I was little, similar to you, think, Grace. And I moved to US later on. So obviously, I work in the US government. So I’m a US citizen. So I’m actually a card-carrying Canadian as well as an American right now. And I think having had a very global citizen-ish

Grace Shao (05:22) Mm-hmm.

Kevin Xu (05:30) upbringing and life experience was the lens that wanted to bring to my newsletter when I first started writing it roughly five and a half, six years ago. Some of it has to do with the US China. Some of it actually just has to do with a specific industry trend in the software, in hardware, in the nerdy techie stuff, in open source that I like to talk about. And I think only the US China stuff got picked up for one reason or another. People started to pay more attention to

Grace Shao (05:31) Mm-hmm.

Kevin Xu (05:58) to

the stuff they’re writing when there is a China-US lens. And maybe it’s just because there’s a dearth of content out there that actually brings a level of nuance to the conversation. And that brings to what you asked me about, which is this notion of a US-China AI co-opetition, is how I like to call it, as opposed to calling it a race, which is the kind of intellectually lazy approach that I have fallen into multiple times.

Throughout my own writing just calling the race calling it a race But not really thinking what that implies which is that one a race implies that there is an end point There is a finish line to this race But for AI there really isn’t

Even the most fervent believer of what an AGI is does not believe that is a static endpoint in which once you reach it, you’re done. And of course, there is the implication that this whole thing is a very zero sum dynamic if you call it a race. But in reality, if you look at everything that’s actually happening on the ground between the US and China on AI, it is a manifestation of co-op petition, which is that there’s a lot of competition between different firms.

between different labs, both within China and between the US and China, lots of startups. There is also a lot of cooperation. The cooperation stuff gets probably shoved over to the side or doesn’t get mentioned as much because of the geopolitical toxicity of the conversation. But there are lots of papers, academic institutions, adjoined productions in terms of research and collaboration that is still happening both in academia and frankly in a lot of startups where the approach to all this is much more pragmatic

and

less geopolitical. And then the last element I actually want to introduce to this fake word is co-opting. There’s a lot of co-opting between leading AI labs from both sides. When the initial chat GBT moment happened three years ago, every single Chinese lab more or less used Lama as their basic building block.

to advance their ⁓ model building. Every single hyperseal in China used Lama as one of their leading cloud services to get things going, right? That is a co-opting of an American, I guess, production, if you will, of a model, just to use model as an example. And then as Chinese open source became much more well-known, much more prevalent, much more popular from B-seq to Quinn to whatever, now we have Airbnb being one of the biggest users of Quinn.

We have a UiPath being one of the biggest users of Quinn and a bunch of startups that they don’t want to talk about using Chinese models to really bring down their own costs so they can run a profitable startup, co-opting each other’s work. So I think co-op petition is the most accurate way to talk about it, but I also understand it’s probably not the easiest way to say the word. And so I’m not...

counting on the word catching on at all, but at least for my own intellectual honesty sake, that is the word or the way that I plan to talk about this dynamic going forward because I think it’s the most accurate way to reflect reality on the

Grace Shao (08:56) I think definitely your writing is one of the more nuanced kind of work that I’ve come across on the internet where it does touch on China, US, where it talks about the cooperation as well as competition and give the audience a geopolitical background ⁓ but still focus on the business, the society and offer that more neutral un biased, I think, analysis of the businesses,

But from where you sit, where do you think the founders, engineers, investors actually feel like they are really collaborating? Give me some more concrete examples.

Kevin Xu (09:27) I think open source AI, open weight AI, the rise of that is probably the best and most concrete example of collaboration and cooperation happening despite all the resistance, the challenges to cooperating, right? There is a lot of resistance to cooperating on anything. And the natural way is to kind of go towards the path of least resistance. But something that is happening that is, I think, probably the biggest

in 2025 is the rise of China’s open AI ecosystem becoming all of a sudden leading the world. Not just pretty good, not just, oh, it’s also happening, but is flooding the zone as far as models are concerned. And the nature of open source is open collaboration. There is no deep-seek open model.

without the lineage of all the innovation that came out of GPT-2 that was actually open source back in the days, or Lama, or whatever the open things that the US lab...

was feeling comfortable doing until it no longer felt comfortable doing. And then you need a lot of Chinese labs to give back to the whole ecosystem as well, entirely without charge. That is the other thing about open source is that you can do whatever you want with open source product for the most part. And DeepSeek and Quinn really led the way from not just opening it, but also having the legal license to permit

just proliferation everywhere. You can do anything with a Quinn model. You don’t have to tell Alibaba you’re doing something. You don’t have to really pay Alibaba a cent. You don’t have to even give credit to the Alibaba team. Just kind of go forth and prosper, right? Now it’s very hard to track.

⁓ what that diffusion really looks like. Having worked at GitHub, for example, which is the home of all open source code for the entire internet pretty much prior to AI, I know how hard it is to track. We’ve tried to do that internally with our data. We have some rough sense of which country is contributing on GitHub more than other country, which company, but we don’t ever get too deep into the people behind that for privacy reasons and whatnot.

But you know from a institution perspective and an intuitive sense that it’s gonna proliferate everywhere, right? And the only surprising thing is that this came out of China, which shocked a lot of people. I don’t know why it should shock a lot of people, but it did. But.

But that’s kind of where the big story comes from. So I think cooperation is happening regardless. And open source is probably sort of this last bastion of global collaboration as the world splinters into its own camp as geopolitics and AI kind of co-mingle together to make everything feel more cagey. This is still the last kind of remaining source of cooperation.

Grace Shao (12:14) I think you talk about the technology being much more cooperative than people expect or want to admit. But what about capital? Over the years, we’ve seen that. first for context, think people need to understand in the 90s and early 2000s, US capital were the predominant capital that were actually behind a lot of the Chinese big tech we see today. But today, now we know there is a decoupling in terms of US investment into China, especially in the sensitive areas such as AI, robotics, and

semiconductors, right? So do you think this is something structural or cyclical? Like, are we going to see more opening up from the US government to allow these US funds to invest in China again? Because a lot of them are obviously still interested in doing so.

Kevin Xu (12:57) I think the rumor is it is loosening up. I think there’s a lot of chatter that Chinese VCs who for a period of time just could not raise any USD fund

for probably like five to six years or so is starting to do so again and I think that spigot is slowly but surely going to open up and it probably won’t be like as wide open as it used to be before but my personal feeling is that capital finds a way it’s just like water it’s going to flow towards whatever the final destination it needs to go to even if it has to go around mountains it has to go through a bunch of rocks it’s going to grind that rock to a smooth edge

that being geopolitics sooner or later, but it will probably take more time than most people have the patience for. And you know, to come back to what I talked about open source real quick, if we can double click on that, I think the contrast between capital flow and source code flow in terms of open source is that ⁓ engineers, doesn’t matter which country you come from, want to work on

⁓ the most open piece of software or code that is open source and you can collaborate with the rest of world, right? Like that’s why GitHub became so popular because engineers, whether you’re from China or the US or Germany, you identify with the code that you build. You don’t necessarily identify as much with the nationality that you were born into. That isn’t really a big part of your work at all.

Right? Even calling something a Chinese open model is a bit of an anathema because like what is it? What part does it really is Chinese versus when it’s out in the open, it’s just like this piece of common good in the internet now. Right? Like no one can really control it. So what’s the point of calling a Chinese or American or whatever? And that’s how engineers like to operate.

So that’s why there’s this tug and pull between the geopolitics force and really the engineering and the builder force that is by definition very global.

Grace Shao (14:51) Yeah, I think the engineers and scientists you speak to definitely are not geopolitically driven or as ideology driven as I think sometimes the business people because they need the support of their government for certain policies. So I think the business people who seem to sound geopolitically driven are not actually geopolitically driven. They just need to do so before for their business survival. And that’s just the reality of how the businesses work. Right. So I want to put you on the spot. We touch on this quickly before we start recording.

Manus, speaking of the most famous US injection into a Chinese AI company is Manus. And I just woke up to the news, ⁓ day of recording is December 30th, that, you know, Manus was just bought out by Meta

I I used to manage this really good product. How do you view this whole thing?

Kevin Xu (15:36) I also use Manus. I think I got an early access code actually before it even launched. I was going to say back in the days, but that was only like a few months ago. It was actually like less than a year ago, right? And this company ⁓ went from zero to a hundred million dollar ARR in about eight months, which is just astronomical.

Grace Shao (15:40) Yeah.

It’s so crazy. Yeah.

Kevin Xu (15:57) ⁓ growth on the back of essentially its product quality. And I think that is one of the most interesting takeaway for me as an investor, as a technologist, which is that we talk all about like geopolitics and, you know, this and that none of this is actually about the product or the tool, right? About AI, but Manas, this little bitty startup, basically proved all of us wrong, which is that ⁓ product quality still matters.

if you have good

Quality product people will share you people will talk about you people will you know? Do word-of-mouth to tell other people to use your product I think one of their more famous element is their ability to kind of crack this black magic of viral marketing without spending any money Right back in the days when they first shared their first version, you know, Jack Dorsey tweeted about it all these like Silicon Valley Luminary started sharing about it and it’s because their product actually spoke

for itself. And it continued to evolve very, very quickly to capture not just attention, but actually revenue, which is very, very hard in this current climate of AI kind of bubble-licious noisiness that we are living through. And on the outcome itself, first of all, congratulations to the entire team. I think it’s very impressive, this outcome to be bought out by Meta. At this moment, we don’t know how much it actually paid for. Maybe by the time this app was released, we actually know how much Meta

paid for, but the last round they raised that was $500 million valuation, right? Which in AI land is actually really, really cheap because we have, you know, 10 to $20 billion startups being funded in the U.S. right now that has zero product, zero revenue, and more or less a bet on a very impressive team, which could still come out okay, but we will see what happens. But I think this Manus deal

to me is a very I want to say it’s evidence that rationality still matters. It’s evidence that like economic kind of pragmatism still has its moment in the day and doesn’t have to be whiplashed by geopolitical consideration. So I find that the deal very heartwarming as an investor who really just hopes for more economic rationality for everybody who’s involved.

Grace Shao (18:18) Yeah, I think ⁓ to your point, like it’s definitely like a positive signal because it means that people are evaluating the products how good they are instead of just the narrative of the geopolitical kind of cloud above it. And I think it’s really interesting. Like when I was speaking to people like about this deal this morning, they’re saying actually, you know, people overestimate the PR they done back in the day when they first released it. It wasn’t because, you know, they did some black magic PR.

It was simply because they didn’t even have the compute capability to actually serve too many people. So they sent it to people to try first. And I think I have a lot of startups that come to me being like, how do I achieve madness PR? I was like, it’s not just the PR. The best PR you can possibly do is to have a really, really strong product and have the product speak for itself. Right. So yeah, it’s, think it’s a very interesting time and it’s, and it’s interesting to see probably one of the first Chinese homegrown.

company in AI being completely separated from the Chinese market now and operating in the West per se and now being bought up by American US company. Okay, talking about startups, I want to ask your opinion on MiniMax and Zhipu They both submitted their prospectus now. We are expecting them to go public in Hong Kong.

What would you need to see before you feel comfortable owning one of these IPOs and how do you evaluate these companies as they go public?

Kevin Xu (19:40) So first of all, I am actually a public market investor. So I don’t do any VC at this moment. So I’m very, very interested in how the Zhipu and Minimax listing happen. Even though as a rule, I don’t invest in IPOs because they’re quite frothy and confusing. I’m happy to wait it out. I think there are a couple of signals. And this is actually interesting as a comparison to Manus. If you look at the revenue numbers that Zhipu and Minimax have shared, they’re both in the

Grace Shao (19:45) Okay.

Kevin Xu (20:08) double digit USD million range, right, which is very modest. And it’s even more modest compared to their losses, which is all in the hundreds of millions of USD as far as how much money they’re losing right now as companies. And you compare that to Manus, which probably is like reasonably profitable at this point as like a hundred million dollar ARR company, not revenue ARR, but still they’re small, they’re growing and they’re probably managing their costs.

because they’re not model trainers, right? Like I think Manus was very clear that we don’t build models. We don’t really have expertise in that, but we are very good at wrapping a model into a very good, trusting user experience. But Drupal and Minimax both became or started out as the model makers, which is a very expensive endeavor. So as far as what I look for as an investor is concerned,

It’s very, hard. I think a path to profitability, and specifically, think EBIT profitability, so earning before interest in taxes, is going to be key for me to see how does a business ⁓ like this, which has a...

I don’t know. I feel like they’re limited to the China market, which is big, but not huge, I would say. And I think MiniMax does have some consumer product similar to ChatGPT, which is going to be how they can maybe justify their higher evaluation, even though most of the revenue comes from serving up their model as a form of APIs, which is a B2B play. How do they balance those two, which are two very different go-to-market motion? It’s going to be interesting.

pretty clear path or lane at this point, which is I make my models and I’m very good at serving large, older legacy enterprises and governments that is a very specific type of customer with a very specific taste, if you will. And you have to really orient your whole company to cater to that kind of customer. And Drupal kind of has cornered that market for now, at least. So that could work really well from a profitability perspective over time, even though those are very tough customers.

customers to track. But the big takeaway, I think, is that the revenue is still very modest and certainly very modest compared to the large labs that we just sort of talk about willy-nilly in the US, like OpenAI, which is going to have $20 billion.

in ARR by the end of this year, probably, right? Like Anthropic is projected to have five, $6 billion in ARR. These are two orders of magnitude larger than Whatchupu and Minimax has shared to the public. But the enthusiasm for investing in AI pure play is still very high in the public market. And I know Hong Kong’s IPO market has been doing very well this year and probably will continue. So that energy can be kept

hopefully by these two companies because they actually need the money, right? That goes to what you were mentioning before, which is that I think if we had done this, Chad, in 2018, there will probably be multiple rounds of VC in China with USD backing that are readily available to fund the Gipu and Minimax for maybe two, three more rounds. So they don’t have to go public.

Grace Shao (22:53) They need the money.

Kevin Xu (23:14) They can still operate as a private company, raise more money, mag around, just like what we have been doing here in the US. But that option has basically run out of this course.

right now for any Chinese VC-backed company. So they kind of have to touch the public market earlier in their life cycle for fundraising, which may not be a bad thing for organizational perspective, because you do become a more disciplined, well-run company for the most part, I think, when you become public. But it does expose you also to the public market. But they need the funding clearly, so that’s why they’re doing it.

Grace Shao (23:47) Yeah, I actually just interviewed one of the leaders at Zhipu recently for the podcast and he was saying candidly, for them, it’s really about survival at this point because they’ve just run out of money. And if they don’t want to be swallowed by someone else and if there even is a desire to swallow them, because given that, you know, all the BATs we see have very, very strong labs themselves, they don’t really need to acquire a talent, new talent pool. So then there’s no way to keep going unless they go public because they need that money.

But on this point on them going public and you know, actually it’s, it coincide with them trying to go global, right? A lot of them, like you said, they’re currently serving China as a market, but they are selling their model as a service to the global South, maybe for a much cheaper price than a lot of the US labs and the peers out there. How do you view that? Do you think that’s something that could potentially work out for them just by selling cheaper services compared to maybe the open AIs of the world?

Kevin Xu (24:39) I think it could.

Yeah, I think it could. mean, I think USAI, American AI is very expensive. Like the quality may or may not justify the premium, but it’s very expensive, right? Like we have like thousands of dollars.

Grace Shao (24:44) Mm.

Kevin Xu (24:51) I think the max chat GBD plan is like 200 bucks. People want like $1,000, know, no rate limit, chat GBD plans. And we’re spending a lot of money. And that’s partly goes into these revenue numbers, right? The billions that we’re talking about. Like you can think that is like an inflation almost of AI product costs here in the US for the most part. But we know that Chinese entrepreneurs are very good at reducing costs, right? They’re already released their models because the models are commodities. They’re open source. There’s not a whole lot of value capture really that happens at the

Grace Shao (25:14) Hmm.

Kevin Xu (25:20) auto

layer. And if you can wrap that around with really good services for just throughout random examples of like a city government in Malaysia, right, or a hospital in Thailand, for example, right, these are all the kind of unsexy industries in very unsexy countries when it comes to AI adoption that we don’t ever really think about. But if they have a strategy to go after them, and I do think listing Hong Kong as opposed to on the

you know, Shanghai market, which I think could have done as well. But choosing Hong Kong is very smart because it increases their name recognition, their exposure ⁓ in that part of the world. As much as you and I talk about these companies like everybody should have heard about them eons ago, most people don’t know what these companies are. They don’t know what the differences are. They have no idea. They probably have heard of Chachi PT, but that’s about it. They probably don’t even know what Ethlopiq really is. Right. But if you can really

tap into that capital market and use the public listing as a way to raise your profile for these second tier market and second tier countries, then I think there’s a decent business to be made there.

How much will it fetch a premium in the public market? I will never know. But I think that’s been a playbook for a lot of Chinese companies that were shut out from what’s called the premium markets globally, which is the US, Canada, and Western Europe. And they have to go to the so-called global south to make a living. And they’ve been able to make it work. And there’s no reason to just assume that these companies can’t make it work either.

Grace Shao (26:40) Yeah.

Yeah, for sure. Okay. I want to talk about sovereign AI. You’ve written a lot about sovereign AI and you’ve used South Korea as an example.

Why is South Korea a champion basically in the region as for sovereign AI?

Kevin Xu (27:09) I think to back up a little bit, sovereign AI is one of these things that ⁓ I’ve been really fascinated with for a better part of this year, ⁓ which is, it’s the first time I’ve seen where a major technological transformational period has been

aggressively embraced by national governments everywhere, right? Part of that has to do with Jason Huang of Nvidia just being the incredibly charismatic salesman that he is, right? Like sovereign AI, he did not come up with the term. I think it came from the EU in 2019 or something, but he really embraced it as the next wave of AI adoption. So more countries can have their own AI, which initially I thought, oh, this is just like a clever sales pitch, you know, to kind of sell more chips. But if you really think of

about it, ⁓ all these AI models do have a way of encoding culture. Encoding not just your mainstream culture, but also your minority culture, your different languages and whatnot. And the countries have learned, I think, their lesson by being really hands-off during the first wave of the internet and especially social media, but not caring about how does technology impact their domestic

situation, if you will. You can talk about in terms in the context of Arab Springs or, you know, violence in Myanmar or just generally speaking data privacy, social media, all this sort of stuff that countries used to have just by definition a lot of control over by having sovereignty and they’re actually losing sovereignty.

to the wave of technology. So with this AI coming together, this wave, more and more countries are actually exerting that notion of sovereignty without really knowing what it means, but they’re exerting it right now more aggressively than ever before. Now I picked on South Korea because sovereignty is kind of this big fuzzy word that means different things to different people. But if you use sovereignty as a proxy to talk about control, South Korea actually has probably one of the better

set of tools to exert more control over their own AI future more than other countries. Because if you really think about full stack AI from top to bottom, from land power chip models and then applications, only the US and China really have a grasp of every single layer of that stack.

Grace Shao (29:24) component, yeah.

⁓

Kevin Xu (29:25) in diff to

different degree, obviously, but you know that they have control over every single step, right? Every other country for the most part is a customer of one of those stacks coming from the US or coming from China, except I think for a handful of countries, South Korea being one of them because it has a very strong memory.

⁓ ecosystem for chip fabrication, not for logical chip, but for memory. And high bandwidth memory is basically an exclusive South Korean national export at this point coming out of SK Hynix and Samsung. Yeah, we have some Micron over here in the US too, but the two thirds of the market is dominated by two Korean players.

Grace Shao (29:46) Yeah.

Mm-hmm.

Kevin Xu (30:03) And then they have their pretty cool little internet ecosystem as well with Naver, with KakaoTalk. They’re all very Korea-centric. They don’t do so well outside of Korea, but inside Korea, just like how we go to China, we have to install WeChat. If you go to Korea, you have to install KakaoTalk. You have to install Naver for your map. Otherwise, you just can’t get anywhere, right? So you kind of have...

Grace Shao (30:23) There is Google Map.

Yeah.

Kevin Xu (30:24) Exactly.

So they have that set up cone coming into it. So they actually have a bunch of different good dominant controls nationally throughout all that layer. So when Jensen visited South Korea recently to sign a bunch of deals and allocated a bunch of black wall chips to different major players among these Chibos, I just thought this is like an actual manifestation of a South Korean sovereign AI at play. Now they’re still using American chips, but part of that American chip is fused with South Korea made memory.

And that gives them a lot more say, at least, to sovereignty of the AI application that they’re hoping to adopt. And South Korea is just very digitally forward, I think, in general. It’s one of the most digitally connected society, period, of any country in the world. And so ⁓ I think they have a good shot at actually making sovereignty real in the AI era.

Grace Shao (31:03) Yeah.

It’s interesting because I just went to Korea I think earlier in the year and I was talking to investors on the ground and they were saying that South Korean startups are actually a lot more, again going back to our point, non-geopolitically driven or minded and a lot more agnostic about which kind of, what countries models they use. However, for the country itself right now, the government, they’re still pushing US models forward. And I think it’s really interesting to see to your point like

They actually have such a small but closed ecosystem in the digital infrastructure. Like everything is with, they don’t use American apps like for social media. They don’t use Chinese apps for social media. They’re actually completely independent. So it would be an interesting kind of case studies to follow through with, I think. When we look at sovereign AI and I look at, know, projects like Stargate, is that something like a de facto US sovereign AI project? Like, how do we understand that?

Kevin Xu (32:03) That’s how I understand it. I think Stargate is, first of all, for people who don’t follow this stuff as closely, is this brainchild from OpenAI to build these massive multi-gigawatt data center, not just in the United States anymore, but actually throughout the world, to support its global multi-trillion dollar ambition. And it’s in countries that are willing to be on Team America. So in a way, it’s a sovereign extension

Grace Shao (32:05) Mm-hmm.

Kevin Xu (32:31) of American AI in a way is also a reduction of sovereignty in whichever country is willing to receive American AI and be a proxy of American AI, right? And we have a few different sites already announced. We have ones in Argentina, in the UAE, in Norway. I think these are the ones outside the US Stargate projects, maybe perhaps India as well. And that is the most aggressive.

expression of American sovereign AI and the most explicit one as well. And the US government is very honest about this as well. Like they want to promote and literally sell the American stack to countries around the world that want to buy American projects. It’s basically like a big

know, White House driven go to market strategy, right? Where the content of the product is actually open AI, Anthropic, Nvidia chips, Oracle, construction, and all the American kind of major companies that come together into literally a package, right? And then we want to sell that abroad to different countries around the world, including the global South as well. And I think that’s one of the things that a little bit of a shift geopolitically is that the US is no longer

giving up the global south as this also ran that it is no longer paying attention to in the way that China has been paying very close attention to for two decades at this point. It’s no longer willing to surrender that part of the world commercially. And Stargate and AI export program is actually a way to express that re-interest in those regions, if we will. And Stargate is just kind of the tip of the iceberg there.

Grace Shao (33:56) Mm-hmm.

I think to talk about sovereign AI, we have to talk about Middle East and it’s something I really know nothing about. I was really fascinated by your recent article and your series in sovereign AI. So first for listeners, can you tell us about your trip? You just got back from Abu Dhabi, I think a week or two ago, you wrote a really insightful long piece on just how the Middle East is building out their AI strategy. And you talked about it as a region, also kind of breaking it down the whole, looking at the Gulf separately, the UAE, the Saudi Arabia, Qatar, Bahrain, each of the...

AI strategies, right? Can you kind of walk us through, first of all, why did you go? What was the event for? And then just some of the high level takeaways from that trip.

Kevin Xu (34:44) So I went to that trip from the exact same position that you are now, which is that I’ve never been to the region. I’ve heard a lot of things about the region. Just in the AI conversation alone, we’ve had major announcements and deals being signed by Saudi Arabia, by the UAE, with the United States. We know Chinese tech have been in that region for a very long time as well. There a lot of robot taxi Chinese companies that are deploying their self-driving vehicles on the ground as we speak. So it’s a region that I’ve been really wanting

to go if I get the chance to go for a long time. And just by happenstance, I was invited to be part of a delegation among other Washington, D.C. think tankers to go to visit the UAE for a week. So we are an American delegation, right? So that’s important context for you to know. If you were to read the post that I wrote and understand what I was trying to convey and how I learned things, we spent a whole week in both Abu Dhabi and in Dubai meeting with pretty much everybody

that has a hand in its AI future, from government officials to investors to all the funds that you have heard of. And the major takeaway for me was, first of all, just to see stuff on the ground, which is that

They are very, ⁓ from an AI perspective in particular, just take away the other stuff for now, from an AI perspective, they’re very much in Team America’s camp. They really want to be building UAE Stargate. That’s one of the very few Stargate projects outside the United States that has actually broken ground. Like there are actual buildings that have been built in the desert.

⁓ ready to receive NVIDIA BlackWall GPUs if expert control were to be permitted from the US side to let them buy as many as they would like to buy. So that’s number one. I think number two, they are in this very interesting geopolitical position as a very tiny country of 10 million people where they don’t want to actually be Switzerland. They’re not neutral. That was the message that I received from a lot of people that they have a point of view on where they want to be in this global

a big game of AI, of geopolitical influence, which is that they can vote for one country or one side, but they also have their opinion to build a society of their own. That’s a very modern Arabic.

you know, society, I think there’s a lot of stereotypes to, know, how does it, what is it like to be in a be a woman in the Middle East? What is it like to operate in the Middle East? Lots of cultural stereotypes that they want to debunk. It’s Dubai is one of the most modern cities I’ve ever ever been to. Right. And that is kind of the cultural takeaway that they want us to have. And then lastly, when it comes to this US China conversation, frankly, they’re a little bit tired that they always get mentioned in that context. Right. Every time the US official goes to the UAE is about

What are you doing with China? then, know, presumably when the Chinese official visits, they’re also like, what are you all doing with the Americans? But they want to be seen on their own term. And they certainly have the wealth to do so.

as well. So it’s a fascinating region and I think they’re playing both sides very well. I call them the swing vote of the global AI competition. They can swing one way, can swing the other, but they have a lot of leverage in this conversation because they need to have the best of both worlds to feel an economy that is in the desert that literally grows nothing.

So they have to export import, sorry, they have to import basically everything from talent, from food, from vegetables, from, you know, the only thing they have is energy coming out of the ground, oil, but they’re trying to diversify away from that, which is the only point where they’re investing all this technology stuff in the first place. And that has been happening for 20 years at this point. So it’s not like a Chad GBT moment thing per se. So a lot of takeaway there, but happy to answer more questions because it’s a trip that I’m still processing, to be honest, because that was first time in the region, had a lot of

coming at me and I’m trying to still come to terms with ⁓ what I understand now but also what I still don’t understand even though I just went there.

Grace Shao (38:40) Yeah, I think that that’s super interesting. And I’ve been really fascinated by the region as well. Actually, we were just talking about this offline. A lot of people in Hong Kong are now being recruited over on the point of talent. And I think, you know, as a lot of these countries have huge sovereign funds, they’re looking for top tier investor talent to go to whether it’s UAE or Saudi or Qatar to really deploy that capital, whether it’s an AI or not. And it’s really interesting kind of to see how

You mentioned they have, what, UAE has 10 million people, but 90 % of that is actually foreign workers, including laborers, as well as knowledge workers. And people kind of forget that actually these are extremely wealthy countries per GB per capita. So I think it’s interesting to hear that they don’t really want to be put in the middle as a China camp or a US camp country now. Similarly to Singapore, where we also talked about, know, like Singapore is

Tiny small, you know peninsula has actually really made it work from themselves and Pretty much have to import everything from groceries and labor is sometimes from Malaysia and even energy to talent from around the world and now mostly China It’s kind of like in that sense not a Switzerland like Singapore right like you said in your article. I want to understand better actually How do we understand the sovereign funds behind?

these investment funds are investing in AI because it actually is so different from private capital in the US and even how Chinese capital is structured.

Kevin Xu (40:06) The way I-

the sovereign fund in the UAE in particular, know, just that part of the Middle East have not been to Saudi Arabia or anything. Obviously Saudi Arabia is a major, major player as well. So is Qatar, which actually announced their own AI initiative while we were in the UAE as part of the Doha Forum. So there’s a lot of, let’s also call it co-op petition as well, among the Middle Eastern countries as well. Like they’re presented as this sort of monolith sometimes, but there’s actually a lot

Grace Shao (40:23) Exactly,

Kevin Xu (40:37) of rivalry or friendly competition between, in particular, these three Middle Eastern golf countries, Saudi Arabia, UAE, and Qatar. Now, the UAE sovereign wealth fund in particular, again, we met with everybody there. so their strategic purpose is, of course, to diversify away from oil wealth.

Right, but that’s easier said than done. What do you do when you have all this money? From selling oil that you know, it’s gonna run out at some point or you don’t want to be overly dependent on this one source of wealth, right? So Mubarak is their kind of marquee sovereign wealth fund that plays very actively in the world of technology investing and they’ve been Investing for 20 plus years around the world. They’ve had offices in China in South Korea in Brazil

obviously in the United States, in Europe for many, many, years. They’ve been placing bets and serving mostly as LPs to local VC firms for

a long time. They’ve also bought a global foundry, which is the chip manufacturing plant, similar to TSMC. But you know, that was kind of a spin out out of AMD, I believe, back in the days. So they’ve kind of placed their bet in the chip ecosystem, again, long before AI was a thing. Now, that doesn’t mean they’re all successful, because the diversification justification is very different from ABC, who is motivated to generate the largest

financial outcome right per fund per fund and they actually did understand more recently why that’s not such a good model which is directly related to your point about Hong Kong professionals finance professionals being recruited

to go to the UAE because they started this new fund called MGX, which is basically more of classic VC fund that has all the incentive structures of a Silicon Valley VC firm like a Sequoia or a 16Z. Mubadala is one of the anchor GPs, but they’re raising money from around the world just like a normal VC would because they need to attract the best talent, which they actually could not if you just run a

sovereign wealth fund because sovereign wealth fund is kind of like a quasi government institution, right? They’re still kind of government employees at the end of the day. They don’t get a huge carry or a payout because one of their funds hit it out of the park and got less than the NASDAQ. They’re just kind of collecting their paycheck, right? They’re more like a pension fund manager. And that doesn’t get you the best, most hungry, I don’t know, money.

making talent from London or Hong Kong or wherever. So they’re just very recently started to restructure that because it’s an evolution of sovereign wealth fund being managed, one, to diversify and then to get into the best technology and then to actually generate a good return and get the best talent, which is really a long-term play because if they can lock down the best talent from Hong Kong for a decade or two to live in Dubai, to live in Abu Dhabi, then that is a long game that they can, again, supplant this 10 million people that needs to be constantly replenished.

with better talent and more diversified talent. So the sovereign wealth fund, the game is very complex, I think, and they probably played it better than most people that I’ve seen coming out of any sovereign wealth fund. Singapore sovereign wealth fund is very sophisticated as well, but that took a long time to evolve GIC and Tomasic.

Grace Shao (43:49) Yeah.

Yes, yes. That’s really interesting context. I think I have one last question for you on Middle East, just given the time constraint, but I would love to talk more about this offline. If you had one non-consensus bet on the Middle East and how it may shape AI globally in the next few years, what would it be? Like, how do we understand the Middle East role going forward, especially amongst this US-China co-petition?

Kevin Xu (44:18) I think I was skeptical going into the trip that it’s going to be a region that actually would matter because there so many data centers being built everywhere. But coming out of it, ⁓ I think there is a good chance that the UAE Stargate will house a significant amount of compute for not just that region, but for the entire world.

First, because its energy is abundant. Second, its construction force, which is something that we did not talk about explicitly. They have 1.5 million construction workers. So 15 % of the population in the UAE is constructing something. They wake up, they’re building something. It could be a hotel, it could be a resort, or it could be a data center. That is something that we’re actually very...

Grace Shao (44:59) these are mostly workers from abroad, right? From India, Pakistan, Philippines. Yeah.

Kevin Xu (45:02) These are almost, these are entirely workers from abroad, right? These are Pakistanis,

a lot of South Asians who are there on workers visa. So they’re not, you know, living some glamorous life. They’re just a construction worker life, right? And there are a lot of kind of like issues with that approach, if you think about it. But as far as the capacity is concerned, they’re able to really build stuff faster than just about any country that I’ve seen. And as the United States hits its challenges, I think, when it comes to labor,

when it comes to energy capacity and I think will also become a domestic political issue very very soon especially this upcoming year with the midterm election that could grind a lot of the pace to a bit of a halt and the UAE is ready to risk kind of

receive all that chips that are being made in Taiwan. And I think that will really be something that people haven’t really thought about as far as where their computer will actually physically live, which really will bring again the sovereign AI story of the UAE to

to life because it’s not just another talking point anymore. They actually have a significant amount of compute that could be used for training models and it can also service a bunch of the region over there because the telecommunication cable between the UAE and say India, for example, or Pakistani, the speed there is like 30 or sub 30 milliseconds, which is super, super fast. So you can actually serve a bunch of users from the UAE to India if you’re okay with that kind of, you know, data center set up.

So that’s something that I think people are probably still sleeping on. We may see that becoming a more real just in another 12 months or so.

Grace Shao (46:39) Interesting. Kevin, you’re so knowledgeable and everything. I love reading your work and I just really enjoy this conversation. I have one last question for you, which is a question I ask every single guest that comes on the podcast. What is one differentiated view you hold? Non-consensus, something maybe even controversial that you truly believe in that maybe your peers don’t?

Kevin Xu (46:57) I think, I’ll share two, but they’re interconnected. Obviously they’re really one, but in two parts. One is that I think there’s a consensus that China AI, AI in China is diffusing better than the US. I think from an economic perspective, from an economic impact perspective, that is actually not true. If you just compare the revenue number,

between Gipu and Minimax to any lab that we have here in the US. It’s peanuts, right? Now you can say we have a bit of a token price inflation over here in the US, as I’ve admittedly mentioned during our conversation, but it’s not 100x premium as far as like that delta is concerned. So there’s actually a lot of economic ⁓ value being captured here in the US just by the diffusion pace that we’ve been able to push out here alone.

So that’s sort of a non-consensus thing, the one. And the other thing that is related is that because the pace of diffusion in China is a bit more up and down the stack, you know, not just in knowledge worker, but in factories, in on the road with self-driving and in robotics and whatnot, let’s just assume all these will just kind of continue at pace faster than any other country in the world. Then China will also be the one country

That has to deal with all the social ramifications of AI before any other country in the world So this is a very interesting moment where the Chinese government and regulators will have to lead the world Into this kind of dark space as we’re all filling out what the hell this AI is gonna do Before anybody else and I’m really interested to wait to see how much they’re willing to share their learning

their failures, their successes from a rulemaking perspective? And also, how humble will the European regulators and the American regulators be willing to learn from the Chinese failures so we don’t screw up too much in our own backyard?

That will be something that I think will happen for sure, but it could really determine the direction of where all this is going. And we kind of saw a little bit of that with the most recent regulation coming out of China when it comes to regulating the chatbots. It’s much more prescriptive than the usual list of harms when it comes to data privacy and whatnot. It touched very specific use cases, like if a chatbot is going to talk a lot about, you know,

Grace Shao (49:02) What’s you say?

Kevin Xu (49:16) the giving mental health advice or all these much more personal use cases that could lead to self-harm the regulators in China is having a very particular point of view on how this should be Diffused in its society whether that lesson good or bad gets learned here in the US and elsewhere in the world is Gonna be interesting but China will have to lead on this front ⁓ Which is a position that I don’t think the Chinese regulators are used to

Grace Shao (49:42) Even expected,

Kevin Xu (49:42) ⁓ up to this point.

Yeah, they’re used to learning from outside. They’re very good at absorbing the best rules from Europe and the US to bulk up their own regulatory capacity and knowledge. But this could be the one thing where they will be the first to step into the abyss and they have to help us get out of it.

Grace Shao (49:59) I think a really, really interesting point. And I actually been thinking about this as well. To your point, I diffusion in China is so much more obvious to the human naked eye because it’s seen through consumer usage, through just the rampant digital infrastructure buildup that we’ve seen in China. So everyone, like you said, from random auntie to knowledge workers will be using AI. But the actual capital gain, the real money has not been proven to be greater than...

than the US and already we can see that from just IPOs like MiniMax and Zhipu And I think the regulation that you were talking about actually came out interestingly right after MiniMax and Jhipu actually released their prospectus to the public. So it’s like, I think regulators are really keeping a keen eye and a hand on it and trying to see what could potentially happen. We speak to people in China practicing AI, like the actual builders and the scientists, they say, there’s less of a discussion about this like.

Doomerism kind of view people are taking more pragmatic view, you know, people are really focused on technological advancements less about societal implications Yes, I kind of believe that being probably the case given that you know in China last 20 years people really saw technology as a Path to economic prosperity, but however, I think what your point is is really interesting is that actually this time they can’t see what happens how the US regulates by tech

they have to do and start themselves, right? So that’s a really interesting point. I actually will think about that a bit more as well. ⁓ Thank you, Kevin.

Kevin Xu (51:29) Yeah, there’s a 100

% chance that China will have to be the first country to lay off a bunch of delivery drivers and, know, ride sharing drivers if robot taxi becomes a thing, right? What will Wuhan do? I think everybody else in the world will want to know when that happens. Yeah.

Grace Shao (51:46) Yeah, yeah, especially when

embodied AI becomes more of a but okay on this point I wonder your thoughts on this because When we go to China, it’s really interesting you have these random jobs that are like placed for sure not for like actual practical reason like you know those aunties who sit in elevators and press the button for you or Like a uncle who sits there like an older kind of larger man who sits outside the parking lot who just pressed the toll button for you like

Kevin Xu (52:03) Mm-hmm.

That’s Right. That’s right.

Grace Shao (52:13) These

jobs frankly are not needed, but they’re implemented I think for societal harmony purposes because you need employment. You need to give these frankly not very skilled laborers a job. So if you’re gonna push for embodied AI in China and these physical, whether it’s robots or whatnot, are gonna replace a lot of these lower skilled jobs, what’s gonna happen to society? Do you think they’ll actually?

implemented at mass or do you think they would actually take a more cautious decision?

Kevin Xu (52:43) My read on that is they will be very, very cautious, which again goes to the non-consensus view that I just shared on the diffusion narrative about China and AI. Right now, the consensus is that, oh, China’s diffusion is so much faster. They’re going to push all this AI. We’re screwed here in the US. But really, there is a very good human reason to not do that.

⁓ You know, this is not exactly public knowledge, so I won’t cite it. But if you look at the pace of deployment of the self-driving companies operating in China alone, right? know, you Baidu, you have Pony, you have Rewrite, you have some of smaller players. It is, they’re all born there. They have very good regulatory environment to experiment and develop their technology. But they’re actually throttled by local permit capacity.

on a city by city basis as far as how many of these cars can they actually deploy on the road? Because it’s not a free for all at all. Every city is looking at the numbers and be like, okay, if we actually do this tomorrow, like let the floodgate open because the technology is actually really, really good already. And we already know the Chinese, yeah, well the Chinese OEMs can pump them out really quickly, right? I think that the safety concerns actually getting really, really good. But what would the delivery drivers do?

Grace Shao (53:49) It’s not a safety concern.

Kevin Xu (53:59) What would the DD drivers do? So there is this toggling already between how much are the government willing to let this technology loose versus taking care of the aunties who pressing the buttons and the dachu who’s letting you into the parking lot because there has to be a pathway there. It’s just not obviously a subsidy program, but it’s clearly a government funded economically irrational employment program.

Right? Like the only corollary we have in the US is the greeters at Walmart stores. I’ve never been to a Walmart super center. There’s like this person who just says hi to you and you walk in and you get your Walmart stuff. Like does that person need to exist? It’s of Walmart’s premium user experience for shopping there. But we don’t have as much of that here in the US, but we certainly have a little bit of that too. Right? So again, China is going to hit that at scale.

Grace Shao (54:23) Yeah.

It’s part of user experience, Kevin. They want you to feel welcome.

Kevin Xu (54:45) before any other country. And they’re trying to figure out the right balance right now as we speak, but we don’t really have a good sense, at least from the outside, of what are the rationales, can we learn from that, can they share more of the thinking, so we can all kind of benefit from that, from a rulemaking perspective.

Grace Shao (55:01) Yeah. And you saw that with the urbanization demand, like what, 10 years ago, we saw a huge rise of young men from rural areas moved to urban cities to become delivery workers, whether food delivery or package delivery courier, that created a lot of economic gain for the country. And then when COVID hit, it was crazy. A lot of people got laid off from their white collar jobs. And then you saw a huge increase of essentially Chinese Uber ride drivers.

Kevin Xu (55:27) That’s right.

Grace Shao (55:29) So all of a sudden people all became drivers and there’s a huge oversupply of riders and now you can call a DD and any car would shut up within like a minute. It will be interesting where would these people go if you’re gonna introduce all these self-driving cars, self-driving delivery man, whatnot. It will be interesting because that makes up a huge part of the urban economy right now. Yeah.

Kevin Xu (55:43) Yeah.

That’s right. That’s right.

And you know, one approach is just that you don’t, right? You just say, okay, we know we have the tech, you can export to the UAE all you want, which though they’re doing really well in the UAE, the Chinese are all with taxi companies. But at home, you’re going to pace yourself because we have a lot of people who are going to get really, really upset if this thing gets unleashed tomorrow, which it can. And that kind of goes against the whole China that just defuses everything because China loves AI sort of narrative.

Grace Shao (56:16) Yeah, interesting. Thank you again, Kevin. Really appreciate your time and your insights.

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