The Exchanges

Q is not that their models suddenly become useless, it's that frontier level capabilities, uh, capability becomes increasingly difficult to monetize at premium prices when open-weight alternatives can perform most tasks at a fraction of the cost. I mean, you come at this from a business standpoint, uh, Uh, if that becomes the reality, right, then what do you even do if you're a closed source company like a closed foundation?

A I think you can still, 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, um, 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 does not, is not a main fact 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. So 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 200 K and their revenue generation is even lower than that. Do 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, …

AI assessment note: “I think you can still, you can still charge. I think, you know, for certain”

Q I've seen from coming from Western, uh, companies, of course, you've had Elon Musk with a person in a robot suit. Okay. Maybe they've had some other, uh, people piloting the optimists, but, um, the stuff that we're seeing from China has been pretty, pretty impressive. So give us the state of, uh, humanoid robotics in China in particular. And, um, and where, where can we expect this to go?

A Yeah, I think, um, to even start with, I think in the start of the year at CES, you know, there were, people were saying there were like more than half the exhibitors were Chinese and majority of them were actually robotic companies. And, you know, like you said, there's humanoid robots, like the, the one that kind of went viral, which is like the dog, the robotic dogs from Unitree. And then, you know, you have, um, obviously the other very variations of embodied AI products, I think. In China, industrial robots not been new and that demand for industrial robots not been new, right? Like we've, uh, you know, like everyone's talking about, you know, the aging population, the urbanization, the reluctance to work in, uh, manufacturing labors, et cetera. And even, you know, cost increase of human labor that's been happening in China. All of these have driven a lot of companies find industrial robot solutions. And that's been around for at least the last five, 10 years. Right. But now, I think human robots in China is really interesting right now is because, um, It's very rare for, I think, a place where you can have the engineers actually understand the software and then the hardware, and that's where China's kind of, I think, strength in the last couple decades of being a manufacturing hub really plays into it now, um, because it's been the manufacturing hub for basically all appl…

AI assessment note: “human robots in China is really interesting right now is because”

Q show, uh, it's doing really well. This is from, uh, Nathan Lambert's Substack Interconnects. It comes number two on the VALS AI Index. Number three overall on artificial analysis is, uh, Intelligence Index, uh, Uh, number one in the front end cone arena, and it has many more, uh, impressive results. So let's just start there. Uh, should we be this surprised, and, and how did, uh, Moonshot do it?

A I can't comment exactly how Moonshot did it, but I'll start with a comment. Actually, Nathan even shared with me when we talked about after his China, big, big China trip, when he visited all the labs, I think it's a lot of it's in the talent and people are really, really shocked by the talent. And this is something we talked about as well a year ago when deep seek, you know, came out with a whole, uh, domestically educated and domestically, you know, um, trained talent pool. Now I think that's something really under, uh, looked right now. Um, You know, the talent pool in China right now kind of is because the base is so big, and then there's such a strong STEM education, um, which feeds into right now the AI, you know, researcher realm. And then we see like the leading researchers really, really, um, a lot of them, if not, you know, maybe 40, 50% of them are of Chinese descent or heritage. Um, Chinese talent right now is kind of having a moment, I think. And then I think within AI research, you know, um, what I've heard from a lot of labs are saying, they're like, look, it's not really rocket science, actually. Um, the, the R and D itself requires a lot of taste and curiosity and test and error, but it, it does take talent and China just has an abundance of very smart mathematicians, physicists and whatnot that are going into AI. Now, beyond that, I think what's the kind of el…

AI assessment note: “I think it's a lot of it's in the talent”

Q Yeah, now some people will say, oh, well, this is just like nine, nine, six, so people in China are outworking, uh, people in the U.S. where they're doing, you know, nine a.m. to nine p.m. six days a week. How much of that would you ascribe to it?

A I think there's nine six everywhere. Honestly, I mean, this sounds, this is really controversial. I think if you're passionate about what you're doing, I nine nine six myself, you know, but only selectively when there's days you need to grind. Alex, I'm sure you're staying up right now. It's nine PM in New York. You're doing this recording with me. Yeah. So I, I don't think it's a top down mandate from the company, but I think if you're driven by a mission and you're passionate about what you're doing, people are willing to work. However, it's actually interesting. Um, the Amazon even talked a lot about how, He does not believe in overtime for the sake of overtime, FaceTime for the sake of over FaceTime, which really goes against kind of the stereotype of what people think of Chinese corporates. Um, so it goes down to, I don't think it's just pure grinding, but obviously, uh, people are hustling when they need to.

AI assessment note: “I don't think it's just pure grinding, but obviously, people are hustling”

Q part for a desire to mitigate the harms, but also because they view it as Important, you know, from a national strategic perspective to have the lead. So there is this view that like, you know, the companies in China can open source because for the government in China, it's, you know, basically the best possible outcome is to commoditize this like leading industry in the United States. Your thoughts?

A Okay. First, I think the argument around subsidization is really funny because I, I don't know if the government is that rich, frankly, just chucking billions and billions at every lab. So definitely I don't think they're like, yeah, like they have a lot of money though. There's a lot of subsidization on energy and data centers, but it's definitely, if you talk to these labs, they're still, they're private companies. And in fact, some, most of them actually don't want to take government money because there's some hindrance as well, right? Like, and when they go public and et cetera on their structure. Now that side, I think it was really interesting that President Xi Jinping attended WAC, which is like the world, it's called the World AI Conference that hosted annually in Shanghai. Um, It'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 few fold, a driver for economic prosperity, economic growth, Of course, um, it's a driver for, I think, soft power and diplomacy, of course, and now also, uh, obviously a very fundamental point on technological com…

AI assessment note: “openness and inclusivity, which is cannot be actually mistaken for quite literally embrace the open source”

Q tell you in the U S I think the view is that China is open sourcing these because they want to mess with us research labs and show the open AIs of the world that the product that was supposed to be their moat is no longer a moat and take the USA industry down a notch. Uh, Is our thinking on the, on that line anywhere close to reality?

A I think, honestly, there's a lot of politically charged narratives going around given the last couple of years of where the trade war has led us and on a very personal level for someone like myself and friends around me who had to kind of like build their, Identity and business and everything on these two worlds and an assumption of that working together, that's not good. It's not a very productive or cohesive narrative going forward. Now on a very business, I think very pragmatic way. Let's just look at it. Um, China actually, I wrote about this extensively with a collaborator called JS and, you know, we, we really examined why China had to kind of go through, um, or go with, A AI monetization strategy. That's really heavily leaning to our consumer versus enterprise. And it fundamentally starts with a really, really low SAS adoption. So in China, there's, we all know enterprise software just never really took off, right? Like, like this is based on many, many things. Number one, let's just start off with, let's just look economic structure. Um, China's still not a very heavily depend is not heavily dependent on knowledge workers, Compared to the U S where it's like, 60% of GDP is driven by knowledge workers. Actually, if you think about China's vast, like significant economic growth over the last three decades, it's very much driven by labor. So it's still in manufacturing sec…

AI assessment note: “there's a lot of politically charged narratives going around”