How China Caught U.S. AI — With Grace Shao

31:35It's been around since 2018, but it honestly didn't really get much traction until maybe last year when post-Deep Seek takeoff. And now like there's floods of American investors, American policy, think tank people all going in. And I think what was really interesting is to your point, I think governments are viewing AI as a very strategic driver. Now it could be a driver, I think it's a fewfold, a driver for economic prosperity, economic growth, of course. It's a driver for, I think, soft power and diplomacy, of course. And now also, obviously, a very fundamental point on technological competition.

32:12In terms of what she said, I think the highlights was really about, you know, openness and inclusivity, which cannot be actually mistaken for quite literally embracing open source. I think he talked a lot about openness, inclusivity that was echoing what even the previous leader that attended, which is I think I think it was the premier that attended WSA last year. it's a lot of the messaging towards the global south because i think there's a lot of worry around you know countries that frankly don't have the talent or compute or even just the raw material whatever needed to right now participate on the model layer they don't want to be left behind and xi jinping's message is saying hey we will be exporting this along our belt and road essentially um that you can still be participate in the ai boom or the next wave infrastructure upgrade yeah i mean i'll just say you know and then we'll go to break unless you want to comment on it like it's definitely in china's interest for this all to just commoditize um even if it's not the direct strategy i'm sure they're they're quite happy uh to see um the u.s industry after all these billions of dollars have been put towards the developing of models at least sweating a bit So there will have to be some adjustment on the U.S.

33:33side because this is sort of, if you're thinking about it from a closed model standpoint, it's not what you want. It's probably why we saw Anthropics spend all that time waffling, or not waffling, but just not responding to this open source moment of praise in the U.S. And so that sort of leaves us to what the competitive dynamics of AI looks like, assuming this continues to be the rule that open source, you know, it used to be that the thought was open source was a year behind like the U.S. frontier models. Now it seems like it's just months. So what does the competition look like? We'll cover that when we come back right after this.

34:21Hi, everyone. Alex Kantrowitz here. I want to tell you about a documentary I've made with Gravity to explore the future of AI agent security. To find out if we're truly ready for autonomous agents, I sat down with MIT professor Ramesh Raskar, former White House CIO Teresa Payton, Michelin's Group Chief Data and AI Officer Ambika Rajagopal, and Sharon Guy, a former executive at Alibaba. They each offer unique insights into this evolving landscape. We conclude with Rory Blundell, CEO of Gravity, to discuss the path forward. With Gravity leading the way, join us on this journey. You can watch the full documentary at the link in the show notes.

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36:53Go to ironwall.com slash big technology, fill in the quick form, and request your free risk assessment. The team will show you just how exposed your executives are and how to lock it down before a threat reaches their front door. That's ironwall.com slash big technology. Stop online threats before they become real world attacks. And we're back here on Big Technology Podcast with Grace Hsiao. You should check out her Substack. It's AIProem. So it's A-I-P-R-O-E-M.substack.com where she covers this world in great depth and with great clarity. So highly recommend you sign up. Grace, let's talk about what the competition...

37:33By the way, feel free to comment on what I shared before the break. But also, what does the competition in AI look like right now If you have, you know, basically this world, let's say we get to the world where open source commoditizes the closed models and, you know, the whole plan was to sort of have these closed models and sell AGI on a meter. But if you can't do that, then what happens to AI? I think for sure there has been a bit of a global reckoning, I think, on twofold. One is the need for governance because of how much these AI models can do and the potential risk that's been talked about, especially in the mainstream narrative in the US, right?

38:16And I think that's really sent kind of fear a bit around the world. Now, given that, I think following up on what we just talked about, I think it is in China's interest. And it was reiterated at WIC where AI governance will be another focus. And this ties to, I think, the whole open source thing, because it says it basically they're signaling, let's build around the industry and find guardrails to basically in some way control or contain this technology because they still see this technology as similar to any other technology in that sense. It's not like this new mythical creature that we cannot contain.

38:51And then from there, let's export it to the world from a very from a high level, from a business level. I think this is the second point I was going to touch on, which is it's been really interesting. I think even a year ago when we spoke on Big Technology Podcast, a lot of companies were really, really gunning for the U.S. market. It was seen as if I want to sell, the U.S. market is always going to be the most lucrative. Enterprise companies are willing to pay, blah, blah, blah. You know, if we make it in the U.S., we've made it right. That was the like holy grail. and there has been a complete change of mind recently when I spoke into quite a few of the leading Chinese products, whether they're on like coding agents or whatnot.

39:34It's really focused on potentially going to, you know, Southeast Asia, potentially going to Europe because they're saying, okay, first of all, geopolitical headwinds is not like, it's no joke. It's not going to be easy to sell to US. There's obviously a grueling competition in the US domestic market, But there's a lot of desire from other markets that want Chinese technology providers. They're saying maybe some of them don't want to pay that massive premium from U.S. tech. And maybe some of them are also losing a bit of interest from, you know, the very scary narratives that they're hearing from the U.S.

40:07as well. And then on top of that, many of them are looking to build on top of open source models. And they need the support to help them kind of build that infrastructure around it. So it's been very interesting to hear that kind of mentality shift. Yeah, you also, I mean, you put it basically the problem for the U.S. closed source or closed model developers. You put it very clearly. Essential risk to the frontier labs is not that their models suddenly become useless. It's that frontier level capabilities, capability becomes increasingly difficult to monetize at premium prices when open weight alternatives can perform most tasks at a fraction of the cost.

40:44I mean, you come at this from a business standpoint. If that becomes the reality, right, what do you even do if you're a closed source company like a closed foundation? I think you can still charge. I think, you know, for certain government agencies, certain companies, you know, Fortune 500 that might have very strict regulation compliance or rules, whatever. I think for certain sensitive sectors, if you were to want to use American tech stack, it still makes a lot of sense because maybe the money is not a main considering factor. Does that make sense? But for a startup, for SME, like every penny matters and you're going to want to find the best model for your ROI.

41:26So I do think at the end of the day, majority of the world actually runs in a very pragmatic lens because you got to pay your bills and you got to make sure your business is generating money. So when you are buying for intelligence, that intelligence needs to make sense and justify the cost of it. And I think what we saw a couple months ago was a sudden awakening or realization that a lot of the token maxing wasn't making investment sense. Because, you know, spending a million dollars per person on token usage is mental when their salary is maybe like 200K and their revenue generation is even lower than that.

42:02Do you know what I mean? Like it doesn't make any business sense. So I do think businesses will look at this very differently and it's putting pressure on the closed models. but I think people who are working at the most frontier or even like I'm just pulling a name out of my head but like a Jane Street if you're going to spend two million dollars per head but you're going to generate like 20 million on each you know bet like on each investment then that money is justified to Jane Street probably but I think you know it goes back to how do you justify that cost right and I think you also I mean you you effectively have the answer in your piece or or maybe a different answer or maybe an answer that expands upon this in your piece that i think is you know sort of says it all right so you say uh and this is your reaction to kimmy k3 you say kimmy k3 but you can basically say this about this entire open source uh moment it you say it's the latest evidence that the ai frontier is becoming more contested more global and potentially less proprietary and i think we talked about this a little bit last time also what happens when the AI intelligence itself becomes more proprietary, becomes less proprietary.

43:13The thing that matters is the product, right? So I asked earlier, what do the AI labs do? And we've been on this a bit on the show recently. If the intelligence that you've developed becomes less proprietary, if it becomes more of a commodity and less of something that you can hoard, your products are just what matter. And we saw this with DeepSeek and we're seeing it again here. I think that if there was a belief that you could build a trillion dollar company just by selling intelligence from the API alone, not going to happen, most likely. But what could happen is if you're the developer of the intelligence, you can build products with that intelligence and sort of return to your investors that way.

43:58Your thoughts? Yeah, definitely. I think, you know, on DeepSeek, first of all, I don't think they would push out products because, like I said, I don't think they're trying to commercialize. No, no. I'm talking about OpenAI and Anthropic. I think the DeepSeeks and the Kimmy K2s of the world are thrilled to build just the models. But I do think, I agree with you. I think there's a lot of stickiness in the products. And I think, you know, Claude, Cowork, these products like are still very, very sticky and there's still going to be a lot of potential for them to continue to grow. Like I recently spoke to designers where I thought maybe like, do you use Claude Design or do you still switch back to Figma?

44:34because fig figs they're going to add on ai surprisingly the answer was that if i'm going to do everything within clod already i'm already using it as my thinking partner i'm already using it for coding i'm already using it for all the other tasks beyond my actual day-to-day design work then i will also use clod for design so it's almost adopting a super app kind of mentality like i want to capture all now however i have the reverse kind of like the counter argument as well so I went to visit Alibaba recently and I was really fascinated with a product that's really really not under in the radar and frankly I don't even think their own company is really valuing it it's called Axio and it's actually just a very simplistic agent interface built on top of their supply network and why it really amazed me it was because the the the know-how and the actual edge they have is exact not as intelligent because like we said frankly finding a supplier for or I don't know, a glass or a lipstick or a microphone is not difficult, right?

45:35But what their actual proprietary strength or their know-how that no one else can replicate is their 20 years of like kind of doing business in finding suppliers, matching with merchants, and then helping merchants sell it. So they're a 2B2C business. And now they basically built an agent on top of the 1688, which is their wholesaler website. and like I was talking to their people like their their representatives and they're showing me the interface it looked like co-work um a bit glossier like prettier because you know how Chinese apps love to have like a zillion different buttons so there's colorfully colded and it has all these buttons and if you are just an SME or like a drop drop shipper or like a Shopify brand owner all you need to do is go on the platform and say I'm looking for insert eight like you can make merch for big technology.

46:27And he said, I want merch for big technology. This is my, these are people I've interviewed. This is my vibe. I don't know what color I want. I don't know what size I want something universal. Help me think it through. And they will literally go through their database and try to find you the right optimal kind of product. And then they will source it and they'll talk to the suppliers for you, find the best price for you, then give you the three to five like, you know, options and then you can pick. So, so for me, I was like, wow, the actual edge of these products are not an intelligence. It's opposite of Claude, what Claude is doing or GPT is doing.

46:59They're not going into every vertical. They are simply doing this one thing, but doing it very well. And it's kind of similar to what I talked about in Mate Tool as well, which is the creative industry. They're like, we build these models and they're going to be the best models for you to use to optimize your e-commerce product placement or to filter your jaw of face and make your jawline more shizzled or whatever. But they're not for you to build, you know, use to create the next, you know, Hollywood blockbuster or whatever. So I think there's more and more awareness around that now. It's so interesting.

47:32What you're describing is almost a flip of what we've seen in the consumer internet up until this point, where China had the super app, and the US had a bunch of disparate apps. And I think maybe because of China's embrace of open source, and because of the US closed AI model, we might end up seeing a proliferation of individual AI apps in China, while the US goes to super apps. It's like the craziest dynamic. That's so funny. We just coined something, Alex. We need to IP this. We called it first. That's good. That's good. We'll do a co-byline on Substack. That'll be fun. Okay, we have to talk more about compute.

48:11Because yes, you could say Moonshot was able to design Kimmy K2, or K3. I keep calling it K2 because I get the mountain stuck in my head. K3. And there was a Kimmy K2. But with the compute they had, but you talked about they get paid when people want to use the model off their API. The issue is that they couldn't really sustain a lot of demand, right? They had to take the model off basically, or not. They had to limit new signups because of their compute constraints. And so if I'm, let's say, I'm going to try to channel like Greg Brockman from OpenAI, you know, he might say, China can go and ship all the parity AI they want.

48:57If they can't deliver it with enough compute, it doesn't matter. And compute is going to be the thing that makes OpenAI win in this race. What do you think about that? Honestly, I think compute is the obvious constraint. I don't think anyone's hiding from that none of the lab leaders are hiding from it and the fact that you like you said kimmy literally posted on x saying that they needed to you know reassess basically who they serve they're not the first to talk about i think last year around chinese or this year around chinese new year um glm faced something similar deep sleep has faced something similar when demand is literally higher than supply um which is funny because you know the the argument in mainstream is always about is there enough demand for ai there is now on the china side is there's not enough supply for ai so i i like as an intelligence side i like the compute side so i think um it's it's not a secret that china is trying to figure out how to build their like self-reliant tech stack um it's not a secret huawei is working very closely with deep seek on how to optimize hardware and software and try to figure out this.

50:05Now, I am not a semi expert, so I can't comment too much more on the technicalities. But I think even Elon Musk recently came out during a economist interview saying he said something in the lines of I believe China will figure out bloggery and it's closer than we think. So I wouldn't give a number on it. But when I hear from other experts, like I've spoken to Paul Triolo, who is a expert in semi semiconductors and especially China's supply chain on this space. He also believes like China is going to find probably solutions, you know, it might not be the smallest chip, you know, but they could potentially find other ways to optimize the chip, even if it uses more energy.

50:47And it goes back to what we talked about even last episode when we spoke, it was like China's energy infrastructure side is not a problem. So if you have enough electricity and power to be powering these chips, even if you need to use double amount of energy, that's not a kind of a bottleneck for the AI compute side. However, obviously, the argument is then how sustainable is it in the long run for the environment and everything. But I think it's an ongoing R &D and potentially we'll see more breakthroughs coming in the next few months or years. Now, I'm going to ask you a question that you've called ridiculous in your writing but i feel like we shouldn't let it go unaddressed which is you know we started this conversation about you know you talked about how china has a lot of homegrown ai talent uh and that that is true but the wrinkle in the kimmy k3 story is the moonshot uh ceo yang zilin uh did a lot of his graduate work or his graduate work at carnegie mellon and in fact is like Carnegie Mellon advisors were celebrating his breakthroughs on X in the days after their release.

51:57So the question that you've called ridiculous is why didn't he stay in the U.S.? I think for, you know, audience outside of China, it is an interesting question. And so I'm just going to ask it to you. Why did he leave and decide to do this elsewhere? I can't exactly tell exactly what he said, obviously, but I think multiple star researchers have returned to China over the years. There's obviously various different layers of this. At a very high level, people love to say, obviously, geopolitical headwinds is not making it easier for Chinese national or Chinese ethnic people. I think the rise of, you know, racism, frankly, even during COVID made people feel uncomfortable at a personal level that we don't know that could potentially attribute it to it.

52:43Right. But then there's also just the personal reason I think is the main driver for most people, honestly. like I've spoken to researchers where hate to overgeneralize, but their wives or spouse or whoever are maybe teachers, lawyers, you know, healthcare professionals in China. And those are not very transferable skills, like not very transferable credentials. You know, previously, what we saw a scene in immigration or immigrant families is that people who got like who are doctors will maybe go to the US and have to retrain, redo their residency, or even, you know, frankly not be able to practice anymore so there are a lot of personal reasons driving a lot of researchers and tech professionals saying hey i would actually rather be close to my home and then i can have my spouse or family do whatever they want and they can still build their own career there's number one then there's obviously the family kind of point um i think you know again people really want to be close to family i think it's not that hard to understand right there's that and then on top of that i think is the more nuanced thing where i get some hate from but look i i I was raised in Canada.

53:49I was educated in the US. I think a lot of my peers around me are similarly like that. And I think there is a choice for people, frankly, like us. And it's a privilege we have. And when you think about it, where you want to stay, there is obviously the visa requirement. But then there is also the quality of life and your own native culture, right? So where I sit in Hong Kong, I can natively be both Chinese and Western. I think it's very actually accepted. I think someone like Yang Zhiling or, you know, Yao Shunyi at Tencent, who's a former OpenAI researcher, you know, their native language is Chinese.

54:23Their native culture is Chinese. And then it goes back to the quality of life. I'm sure people love to say, oh, but, you know, why would you want to stay in Asia? The fact is, I think 30 years ago for any average Chinese immigrant to go to North America, it is a no brainer because the quality of life in almost any major city is going to be higher. higher than a major city in China. But that kind of, I'm not talking about politics, I'm talking about individual taste and individual lifestyle, the day to day of me buying coffee and living in a nice apartment, things like this, the quality of life is no longer justifiable.

54:59And I think it's really a trade off people decide. So just to bring it back to myself, my parents immigrated to North America more than 30 years ago. That was a very easy decision for them back then. They were educated in North America, they stayed on, right? No one actually questioned why would you return to China or anything like that. And but now actually, if you meet very, very top talented researchers, finance professionals, journals, whatever, right? People want to return to their home country because of familiarity, but also because of very high quality life. And then on top of that, I think Yang Jilin, knowing that he is a genius that he is, probably had some more, you know, relationship in China to help him build this out and his own peers, his own team to build out.

55:46Imagine, you know, moving to a new country in your 20s and trying to build that kind of relationship and build up that reputation. Totally. Okay, Grace, my last question for you, I don't want to let you out of here without addressing what the next step in this is going to be. And I think we all know it's robotics. You know, we spoke about it last time that you were here that China has this advantage because they've been building a lot of hardware, and now they have AI development. So just give us like a quick look at how robotics has progressed in the last year in China. I recently saw, I think it was in Shanghai, a bunch of robots fighting each other in a UFC.

56:23I don't know if they were like telecontrolled or autonomous, but it does seem like there's some progress being made. And obviously it's a place we got to pay attention to. So give us the update on that. Yeah, there's definitely a rise of so-called like tech investor tourism in the Shenzhen GBA area, which is the greater Bay area that connects Zhuhai, Shenzhen, Hong Kong, because that's where all the manufacturing of robotics happen right now. So for sure, I think China right now has a huge advantage in the supply chain of robotics, because given the last 30 years of being the manufacturing hub of essentially everything under the sun, any robotics company that need will have some kind of a supply and touch point in China, and likely from that GBA area to start with.

57:07Then beyond that, I think a lot of the speed is an advantage when I speak to people on the ground. Production line can roll off almost 50 % faster than other countries. Even if you look at an EV car or something, when I spoke to people in the EV industry, they're saying a Zeker car can roll off the production line within a year and a half from design to production versus maybe three to five years for a traditional OEM. That kind of Shenzhen speed transfers into robots. It's significantly cheaper. It's said that, you know, a lot of these robots, whether they're humanoid or industrial robots, the raw kind of hardware itself can be like at least 50 % cheaper than produced elsewhere.

57:50So all of these have really kind of emboldened China's hardware space or robotic space. And beyond that, what's really interesting is you're seeing a lot of companies in the EV space or in other areas that are autonomous driving. They're now inching towards and expanding their range into humanoid robots. So it's very interesting. However, that said, I will preface saying I think, you know, humanoid robots right now, it's still in a very nascent state. Of course, the dexterity and the mobility has improved significantly from what we've even seen last year or 10 years ago significantly. significantly, but the real life use cases are very, very minimal.

58:29Because if you think about how much it takes for us to even like lift up an arm like that, like I look like a little T-Rex, but you know, it's not easy. And what is the real use case of this? But this takes training. And then the real, real, real bottleneck for these, all these companies, whether you're talking about autonomous driving or industrial robotics or human robotics with, in terms of AI integration, is that they don't have enough physical data. And I think that's where the world models come in. And we're seeing a lot of competition going in there right now. yeah that makes me relieved i i think you know i have appreciated the fast progress that we've seen up over the past couple years but if we had a robotics intelligence explosion alongside uh this like llm explosion that we're happening right now i don't know if we could handle it i mean i'm sure we'd figure it out at a certain point um and they they will get there the researchers will get there on robotics but kind of i don't know i think it takes more time you I just spoke to Pony AI CEO a couple weeks ago, and he basically was, you know, when Silicon Valley said, okay, autonomous driving is going to reach us in the next three to five years, he said 10 years.

59:34And it took him 10 years. So I think he founded the company 2016. Now 2026, they're deploying hundreds of cars in their fleets. He was saying, I was like, what about robots? He's like, look, it's the same thing. People love to hype about it. They're saying, look, human robots are going to be deployed in the next three to five years in the mass market. He gave me a rough number 10 years again. And I believe in because I've seen a lot of these robots. They frankly can't do much. And then it's also the, again, ROI. Like if you're going to buy a robot and help you restock bottles on your convenience store shop, those cost about 700K, almost 100K USD.

1:00:13In markets, especially like Asia, across Asia, where labor definitely does not cost 100K for a year. How do you justify that? And they do extremely so and often like make mistakes where you can actually create employment. I don't think they're taking anyone's jobs anytime soon. I think industrial robots in manufacturing warehouses where actually there is already a labor shortage globally, they will see more use cases and more mass adoption. But this is not going to be seen by the consumer eyes. In fact, they're already being deployed, right? Like the six axes arms, the things that lift things, logistical use cases where autonomous vehicles like that look like I think the company was called Neolex.

1:00:51they they look like little boxes are already on wheels and shoveling things and taking things and putting things back in shelves in warehouses these are i think uses days where they're actually complementing the current workforce because a lot of times these are not really fun jobs these are labor's jobs that people don't want to do already and frankly the intelligence of it is very low so they can just repeat program it yeah i i believe in the potential for these things but Right now, nothing makes me happier than seeing a humanoid robot brought on stage for a demo and just falling and totally collapsing.

1:01:27I mean, I have great joy when that happens. But eventually, get it right eventually. Just like, let's take our time on that one. All right, Grace. The website, I should say it again, aiproem.substack.com. P-R-O-E-M.substack.com. Grace, you've done it again. two years in a row, great opportunity to speak with you and help us understand everything going on with the Chinese AI movement, which I think will only get more interesting from here. So thank you so much for coming on. Thanks for having me again, Alex. All right. We'll have to do it again soon. Thank you, everybody, for listening and watching.

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