Grace Shao on What the World Should Know About Chinese AI

23:03And then you kind of force copy that into your said model. And then you forcefully make them basically like get the exact same answer. Smart distillation is like you using the frontier model almost as a partner to help you with the judgment for the evaluation and even the data labeling itself. So you're using it as almost a teacher for your own model. It guides it a little bit versus really copy-pasting the answer, if that makes sense. And that part of it is frankly not that unethical or like, you know, that frown upon right now because that is what enterprises do when they're fine-tuning. So it's all kind of a bit of a murky area, to be honest.

23:40Grace Shao:Okay. So you mentioned data just then. Talk to us about what the Chinese data set actually looks like. Because I imagine if you're a Tencent, I mean, you've got WeChat, right? That must be a whole load of data on which to actually like build your AI. But on the other hand, I imagine like there are some restrictions around the internet, obviously. What does it actually look like here? So I'll actually split that into two parts. On the data itself, people often think China is so data intensive and you just have a mass amount of data to use for AI training. However, actually, people forget, again, China's enterprise build out or, you know, whatever, the knowledge work economy is very new and not as sophisticated, frankly, as the American ecosystem or the Western ecosystem, if you have to put it that way.

24:27So data is often unstructured and data, thus a lot of the specific needs for, you know, the kind of training we're seeing today is not as vibrant or the data ecosystem is not as sophisticated as what American data providers kind of can provide, such as Mercore, like we just mentioned. Now on the big tech side, it's a bit interesting. So I'm glad you brought up Tencent because Tencent actually just announced last week that they are working in the works of creating an agent that can be plugged into WeChat. This has been very controversial and it has actually had a lot of pushback even internally because WeChat's product manager, Alan Zhang, has been famously or notoriously known to be kind of hard to work with if you want to push something within WeChat because he's so protective of that user experience.

25:13It's his baby, right? And Tencent, like you said, has WeChat, which is a super app that has more than 1.4 billion MAU globally, like mostly 1.3 billion people in China and the Chinese Aspera globally or people who work with China. That is immense value, but the risk and compliance risk of potentially an agent going rogue within that chatbot or that of agent going rogue in executing, you know, whether it's a purchase or whatnot, is very, that risk is very high. So they've been working on that. And on top of that, Tencent itself has been lagging behind compared to other big tech in their own proprietary models.

25:53And they've really been trying to really play catch up. They actually last year poached someone from OpenAI, who is a researcher called Yao Shunyu as well, has the same name as the other researcher we just mentioned, to lead this whole initiative. And their whole goal is to basically build a Tencent agent native model. And that is their biggest goal. Because at the end of the day, like you said in the very beginning, their goal is to optimize their existing businesses already and bring AI to the mass consumer as fast as they can. You know, you mentioned poaching a researcher from OpenAI, and it's like the way I see it, AI will definitely be built by the Chinese.

26:30The question is whether it'll be built by the Chinese working in the American labs or whether it will be built by Chinese working in Chinese labs. Has there been a gathering of steam of researchers from that had been working at American labs going to Chinese labs, or are they still sort of one-off and somewhat rare? I think even during the internet era, we saw a lot of Chinese nationals or Chinese ethnic people returning to China, right? I think this, it's easy to blanket statement as geopolitical headwinds, people are scared. But realistically, I think most people are just trying to take care of their families and live a good life, right?

27:06I hate to sound so crass about it, but you know, sometimes it's what your package looks like. And to overgeneralize, I've heard from many researchers say, look, if my wife is a lawyer in China, my wife is a nurse in China, my wife is a teacher in China, that kind of employment opportunity is very, very hard to actually transfer to a new market. If I can get a similar package and a growth opportunity in one of the big labs in China, I will pick that over living in the US. And on top of that, I think that something is lost in the nuance is my parents immigrated to North America 30 plus years ago.

27:39It was a very clean cut, like quality of life. It's just like objectively better in any city in North America compared to any city in China. Now that's kind of a personal debate, right? Because it depends on what you really value. If you want to be close to city center, you want that fast paced, like techno, EV, futuristic lifestyle, China actually gives that to you. And then on top of that, if you want to be close to your family, it's a very personal reason. So I've met a lot of researchers that actually decided to come back to China or this part of the world simply because they wanted to do it for personal family reasons.

28:14Grace Shao:Are they paid as much as they are in the U.S.? Because we get headlines all the time about, you know, so-and-so is joining whatever company, and people treat that news like sports stars, right? Like teams trading their best players. Is it a similar thing here? I think you definitely get less of that sports star vibe or mentality here. They're still getting paid like hefty amounts. How much, they don't usually disclose but at least even in the internet era like a bite dance product manager can make just as much as a meta product manager similarly if you're like an average ai researcher you're probably making a similar amount although the star star players like the ones that are signing 100 million bonuses i don't know if we had anything like that big like in china but look they made their money with the ipos they made their money recently with all that this ai boom it's just on on maybe slightly smaller scale doesn't mean that they're not making much more than the frankly average person.

29:13Tracy, can I say something that might be sort of sacrilege for a podcast host to say?

29:19Grace Shao:Okay. I'm only speaking for myself here. I'm not necessarily speaking for the team. But it occurred to me, like, I'm not really sure if I'd be that interested in, say, getting the CEO of, like, an American AI lab on the podcast as a guest. I don't know what I would ask them because like, like, do I really want to hear like Sam Altman or Demise Hissabes or whatever, like the future of work and all this stuff or like these, all the big, you know, I love doing AI episodes. I just feel like at that level, I would rather talk to someone in the engine room rather than this sort of big picture person who may have some degree of AI psychosis and just speaks in the biggest generalities.

30:06Grace Shao:Okay. Well, now Sam Altman needs to invite himself on the show just to test your commitment to not having AI CEOs. No, I would. I would do it. But let's just agree here that if we ever get one of the really big lab CEOs, let's just ask the very sort of mundane questions about operations and not like, what are we all going to do? And what is the meaning of life going to be when we don't have jobs? Because I'm so sick of those conversations. They may be important at some point. But Grace, I'm sort of curious from your perception, like, it does feel like the heads of the American AI labs have some degree of AI psychosis themselves.

30:47Either they talk about all white collar employment is going to disappear, or that they're going to build a monster that if done wrong, is gonna be out of control and that they're not, you know, escape the sandbox. Is there the same sort of existential discourse in the Chinese AI community? Yeah, I think to start with, in the AI community themselves, I would say people are a lot more pragmatic. And I think recently I was talking to Nathan Lambert, who is an open source researcher who just came to China and visited all the labs. He said, look, I was shocked to see majority of labs are so young, as in like a lot of the researchers are still students.

31:27A lot of them are interns and the core research teams are maybe led by a handful of people. And then these people are academics by training. So maybe they're a bit less commercial. Maybe you can say they're less like sophisticated to manipulate the market, whatever you want to call them. So I definitely feel like there's less of that kind of psychosis or high level narrative going around. However, I would say that there is obviously anxiety from the public in some degree, not as much of a pushback. But recently, there was a very interesting court case in Hangzhou, which is, you know, home to Alibaba and a lot of these AI labs.

32:05Basically, a company tried to like lay off a person saying you are being replaced by AI. And the court literally ruled say that is not allowed. and no company can use AI as an excuse to lay off or replace or even cut short their contract time. So that was a really swift reaction from regulators. And I think it really did serve as a calming factor for the public. Obviously, I also think I want to preface the fact that the knowledge worker economy makes up less of the overall economy in China as well. So that kind of fear maybe doesn't feel as imminent. But that conversation is being had. But I do think in Asia in general, not only in China, you look at South Korea, Singapore, all these countries are approaching AI in a very pragmatic way.

32:52And the tired moms are trying to train up the kids to be AI native. The students are trying to train themselves up to be AI native. People are preparing for the future versus pushing back on the future. That's interesting. In the US, obviously, companies announced that they're laying people off and they cite AI even frequently when there's no evidence that AI had anything to do with it. So it's interesting they're not allowed to do it. In defense of American AI labs, most of them lose a lot of money. And yet they actually do spend at least the big ones, spend quite a decent amount on so-called like alignment research, safety research, making sure the AIs don't go rogue, et cetera.

33:33How big of a part of the Chinese labs, how much do they spend on, I guess, what they would put, what the American labs would put into the safety bucket? I do have to say I'm not a policy expert, so I don't work with a lot of the safety people as much. But there are organizations in China that are definitely working, like the regulators, as well as the private sector working together. And for some context, in China, there are various moving parts in the government. There's MIT, the CAC, et cetera. These agencies, basically, some are to propel economic development. So in this case, AI diffusion, the whole idea of AI plus, AI plus every single sector you can think of.

34:14Some act more like a guardrail as a protector. So they are working hand in hand. And on top of that, every single AI, gen AI application, as well as LLM company have to go through the national registry in China. So they actually disclose what is being trained, what is the potential risk. That said, I think right now, no one really knows what the real impact of AI will be on the economy. But definitely that fear-mongering narrative is not mainstream in China.

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36:44Grace Shao:How would you describe, I guess, the approach of the Chinese government to AI in general? Because it feels like the tradeoff for maybe not being on the cutting edge with frontier models is, well, you're further along with sovereign AI and the government maybe has like a better handle on what the labs are actually doing. The Chinese government probably sees this in a much more pragmatic way. You know, just like how there was an Internet Plus policy 15 years ago. There's now an AI Plus policy. When DeepSeek moment took off, you know, there was a frenzy of private companies, even in home appliances, trying to embed DeepSeek, integrate DeepSeek.

37:26I'm just like, what is an AI vacuum going to do for you or an electric toothbrush going to do for you? It was wild, right? But the government picked that up. And I think what the Chinese government, going back to what we talked about earlier, is that they have the advantage of having the ability to push things down from top down. And at the very high level, they're seeing AI as an economic driver to propel maybe efficiency, to address some of the labor shortage that is coming as the population continues to age and decline. It also addresses a lot of issues where a lot of the young people don't want to work in manufacturing roles.

38:01They want to be automated, actually, and they want to work in urban areas. So they have that now. And then each of the provincial governments will take that as kind of like a KPI. They're like, all right, let's go act like VCs, essentially, and go find, you know, future deep seeks and fund them. However, how much these companies want to take government money is a different discussion. A lot of them will then even support them by providing, you know, infrastructure, like buildings, offices, even like some of them are heard like dormitory for these young entrepreneurs and then give them money and capital to try things out.

38:36There's also these AI pilot zones being rolled out across the country. I think now about 11 or 12 of them where, you know, people can try out new AI products. I met with the largest AI developer community founder in China a couple of weeks ago, and she was saying there's more than a couple hundred thousand developers in this ecosystem and they are working with regulators and the private sector. So if, say, ByteDance have a new product, they might go to them first and say, can you try this out? And then they will report and debug and see what's happening and then tell the whoever local government that's funding them with providing with infrastructure, say, hey, this product might come out.

39:12Do you want to be part of it? Do you want to give it money? Do you want to provide it with whatever resource you want to? So there is kind of this like cohesive ecosystem where they kind of all dance together. How much these companies actually want to take state money. I think that's debatable. However, as AI and robotics become more and more sensitive and being recognized as not only an economic driver, but potentially a military use or geopolitical, I guess, talking point, at this point, it is becoming more and more nationalized, not only in China, but globally in the US and so on. Robotics is obviously an area where China is just straight up ahead of the United States, or at least according to all the videos on my Twitter and Instagram feed of humanoid robots and so forth.

39:59How much does, you know, when we were all kids, when we thought of like AI, I think we thought of robots, right? We thought about the T-1000 or some version of it. And now when we think of AI, most people think of chatbots, but that's just one aspect of AI. For the advanced labs, whether we're talking about the DeepSeaks or the Minimaxes or GLM and so forth, Like, are they actively working hand in hand with some of the unitaries and advanced robotics companies to figure out how you can actually have that the true robot of the future? Yeah, I think China, having been the manufacturing hub of like literally everything under the sun over the last like three decades, has definitely a an advantage have owning all the supply chain.

40:45And it's like not only just owning the supply chain, but there are literally regions where that whole supply from raw material to the end product from OEM is all within, say, 50 kilometers of each other. So what we're seeing is a lot of American investors and entrepreneurs coming into China to kind of get a sense of that. And like you mentioned, because we've been so fixed in software, I think China having a very strong hardware background is now thinking about how can we actually integrate the software into the hardware. How ready that is to the mass market, I frankly don't think it's really there yet.

41:21So recently, I just met with some robotic companies. They actually can't just plug in a minimax, you know. That's like for them, they need to actually get physical data. This is where now all the hype is on world models, physical AI. That is a complete different set of kind of technology, essentially, where without the 3D data that these models need right now, the bottleneck right now is that these hardwares, these humanoids, quadrupeds, dogs, whatever you want to call them, they cannot be powered by LLMs. That's number one. Number two is despite that China being very strong on hardware, the bottleneck is actually a lot of times in the integration as well as the battery solutions.

42:04You know, you think of China having very strong battery solutions, but most of these gadgets can't last more than like, say, two hours. And there's no one that's really come out with a better solution so far. What I've seen the most creative thing so far is like, you know, those glasses you wear, like the meta glasses, they kind of die within two hours. But China, like iFly Tech or Rocket, that's kind of a newer player startup, they created these battery capsules where you can just like stick onto your glasses. It's very lightweight, doesn't really affect your user experience. And that's actually able to kind of extend it by a few hours.

42:39So to go back to your question, is China trying to do physical AI? Definitely. What is their edge? I think it's still in manufacturing. Is their software good enough? I don't think anyone really has good enough software right now as of now.

42:51Grace Shao:Wait, I'm just going to press you on this. So if we fast forward 10 years, like what would you say is most likely to be China's comparative advantage? Is it like the cheap, open source, super optimized models? Is it software, AI software that's like integrated with like industry and existing business? Or is it robotics and the sort of hardware side of AI? 10 years is a long time. 10 years is a long time. Sorry. Well, we want to challenge you. A lot of these companies didn't exist 10 years ago. We're not even five years ago. Yeah, that's fair. Okay, I can shorten the time frame. In three years.

43:27All right. So don't chase me down if I'm wrong in three years. But I think, you know, there's two parts. One is I think I agree with you. Hardware side, China is definitely going to have, I think, more breakthroughs and have a lot of edge. Not only is the supply chain all domestically there, I think something overlooked by people is the fact that a lot of the know-how is also there. And that's not easy to transfer overnight. You know, Patrick McGee's book recently in his Apple book saying how Apple tried to move this whole supply chain to India. The biggest bottleneck is actually these like highly skilled laborist jobs that actually are so technical that cannot be even trained in one generation.

44:07It took decades to really train up the local community, labor force, whatnot. So that's still there. Now, because of that ecosystem, a lot of these robots, home appliances, whatnot, these tech gadgets are produced at less than 50 % of the cost of where you could produce at anywhere else in the world. They are also extremely innovative. I've talked to people at EV companies, just for example, to ship out a new model from ideation to production to hitting the like floors. That takes maybe less than 15 months. Wow. But for a traditional OEM, like wait for at least three to five years, right? So there's the hardware side.

44:45I think another very underappreciated fact on the Chinese open source model is that people don't realize. So a year ago when I spoke to startups in Silicon Valley, they were the most cost conscious, frankly, less compliance conscious and gives very little care about geopolitics. They were building on top of quit. Now it's actually a lot of AI Native American enterprises building on Chinese open source. because we're seeing headlines on the ROI is not like showing it's extremely expensive for these token maxing projects whatnot so Harvey cursor they've talked about using a hybrid model where they will build majority on GLM or Kimi but kind of like what we talked about earlier where they use like opus to act as a judge or a guidance so I think that's something where we continue to see And these companies are generating a lot of revenue and going back to the fact that like a lot of them don't even have enough capability to support the demand that's coming through.

45:47That's such a fascinating idea and it makes a lot of sense that at the application layer that probably a lot of different models can go into it. You know, by the way, I was talking to someone at a dinner recently and he said he thinks that AI writing will get a lot better when AI is embedded in humanoid robots because then we'll have this sort of groundedness in the real world where I have no idea if this is true. But he said the reason – his theory was that the reason why AI writing is still so weird is because it's in this disembodied data centers and that as soon as they're really in robots, then they'll have a sort of real-world groundedness.

46:23All right. I have one last question. You know, after OpenClaw came out, I started seeing – again, my entire Twitter feed and Instagram feed, I have done this to myself. But all I do all day is consume Chinese propaganda. But I started seeing all these videos, like all these grandmothers and stuff, like setting up their claws and stuff like that. And I saw these videos and I said to myself, I just don't believe this. I think this is fake news. I do not actually believe that there's all these 80-year-old grandmas or whatever really excited about setting up their open claw or whatever. Are those real?

46:56Like what's the deal with that? I think that was definitely a bit of a hype. I knew it. No, no. But I will say there were grandmas lining up to get it done. Okay. I will answer this twofold. On the kind of the surface is I think Chinese aunties, uncles, whatnot, they are just much more open to technology because, you know, you go around, whether it's by force or by nature, you know, you can't really navigate modern Chinese life without being on Alipay. No, you really can't.

47:25Grace Shao:You can't like buy Starbucks in Beijing without like having WePay. After COVID, I went back to, I think, Shanghai for the first time. And I was sitting at a restaurant just like waiting for someone to like help me order food. No one came because they're just like, why are you so like, why are you a caveman? Don't you know how to like scan the QR code on your table? Okay, so that tangent inside, I think the overall optimism around technology is very different from the West. because in the last 20, 30 years, a lot of rural areas in China literally could not access resources, information, goods, whatever, that, you know, like big cities could.

48:05Not until these super apps came about. So a lot of people don't have TVs in their homes and they live in a village and their maybe annual household income is like$1 ,000. But they will have a smartphone and that smartphone will be able to actually enable them to get microloans, to purchase goods, you know, to help their kids access information online, whatever that is. So technology is very much kind of accepted and respected. And actually like big tech is loved. Like if you work for one of big tech, you are like a pride of the family. So there's that very cultural aspect of it. Then is like going back to the super apps.

48:41So I think the open claw frenzy was interesting because some people say it was the first agent that, you know, Chinese people could get their hands on, like a Western agent that they can't get their hands on because, you know, Anthropic and OpenAid doesn't actually operate in China. You can't access that. So when Tencent and Alibaba tried to embed OpenClaw products into their own like series of products or business products, whatever offerings, it got people really excited. And because of these super app models that they have, it was a very natural way for people to access them. There's a functional adjacency to, you know, the search bar and then opening up an open claw and then trying to like run, like, you know, manage your mini programs within Tencent, WeChat, and then trying to order something.

49:28So all of that kind of took off. But that said, actually, the Chinese government, again, regulators acted very swiftly. In the beginning, I think local government like Wuxi tried to even encourage local businesses to embrace open claw. But the Beijing government immediately said, guys, actually be very, very careful of your data privacy, your security. Banks shouldn't do this. SOEs shouldn't do this. Be mindful of what you're doing with this technology. And then the big tech kind of rolled back a bit of their marketing. And you can see actually hilariously, there were advertisements for helping these aunties and uncles how to uninstall these open cloth on their gadgets.

50:07So anyway, that's a bit of a kind of background on that. All right, Graysha, thank you so much for coming on, Adla. It's great to connect with you. here in Hong Kong. And we'll have you back in three years. No, hopefully before then. We'll have you back at least, certainly in three years to see how your predictions held up. Thanks so much.

50:37Tracy, that was fun. There was a lot of interesting ideas in a fairly short conversation. But one thing specifically, And then that like sort of stands out to me is thinking about some of these application companies, how much it makes sense for them to sort of, yeah, they'll use like a state of the art American closed model for like some of the work. But then other just, you know, almost as capable models underneath. So you have like a legal AI app like a Harvey or something. I'm sure some of these open source models work well for some tasks within that context and how much it makes sense to sort of combine them under one app layer.

51:17Grace Shao:Yeah. Well, you don't need the cutting edge model for everything, right? But like if you can get some of the cutting edge model combined with like the cheapness of the open source thing, like that seems like a pretty good deal for a lot of companies. Yeah, definitely. I also think like how is the massive manufacturing edge that China has not going to just keep compounding itself? I mean, this is like the multi-trillion dollar question of the entire world. But it really does. I mean, when you think about, OK, there is this sort of presumably natural synergy. There's all this real-world physical data that Chinese manufacturing companies can theoretically get from their various robotic vacuum cleaners and so forth and then feed those into certain models that then we call AI.

52:08That really does seem like a potential leg up that, you know, just on the data collection alone from all those physical things, like a huge potential edge over the next several years.

52:18Grace Shao:Yeah, although it was very interesting, Grace was saying that it's not as developed or as structured as it is in the US. Because I thought the same thing. Like if everyone's talking over WeChat, if everyone's paying over WePay, you must have oodles and oodles of data. But yeah, that was interesting. The ecosystem thing I think is really important. And it just seems like really hard to get an ecosystem kind of going from scratch. And I remember maybe it was with Dan Wong, but someone describing how like if you go to Shenzhen, you can basically start like an entire company manufacturing a physical thing because every single supplier is there.

52:59Grace Shao:You just go from like one storefront to another storefront to another storefront. I don't think that can be replicated anywhere in the U.S. I mean, this is a bit of a tangent, but, you know, this is economists talk about, quote, agglomeration all the time. The advantage is exactly that of having everything there and then you build these deep networks. One thing I find to be a little strange, and again, this is a tangent, is how San Francisco concentrated AI is. Even though at the American level, it is sort of pure like desk work, right? Like it's not the sort of we need the bolts manufacturer, we need the servos manufacturer, we need the robovision manufacturer.

53:38and yet it's still so agglomerated or the fact that finance is so agglomerated in New York City. I find that – or conglomerated. I find that to be a little odd. So – but yeah, I thought that was – Glomerated is a good word. Glomerated. I don't know whether it's conglomerated or agglomerated. I'm just going to say glomerated. We know that there are certain industries in the U.S. that are, quote, glomerated one way or another. But yeah, I did find that to be – and man, these – like Minimax,$20 billion company. That's like nothing compared to the valuations that we see with American companies. Pretty wild stuff.

54:13Also, the point we should do more. I mean, there's a million. We got to do. We have, and there are plenty of non-AI things to do, so you can't just keep saying we should do an episode on X or Y. But data markets and like the idea of like, OK, these Chinese companies can buy very pricey proprietary data after some exclusivity window. There's some interesting stuff to be done there.

54:36Grace Shao:Yeah, the monetization was really interesting to hear. Okay, shall we leave it there for now? Let's leave it there. This has been another episode of the All Thoughts Podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Jill Weisenthal. You can follow me at The Stalwart. Follow our guest, Grace Schau. She's at GraceMZSchau. And check out her sub stack, AI Prom. Follow our producers, Carmen Rodriguez at CarmenArmand, DashelBennett at DashBot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And for more OddLots content, go to Bloomberg.com slash OddLots. We have a daily newsletter in all of our episodes.

55:12And you can chat about all these topics 24-7 in our Discord, discord.gg slash OddLots.

55:18Grace Shao:And if you like OddLots, if you want us to do an episode on data markets, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.

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