The US and China Are in an All Out Race For AI Domination

26:25So from export controls, you have limitations on the types of chips which you can be exported into China. We've had EUV restrictions so that China can't make the most advanced chips domestically, the types of chips that that the U.S. is no longer allowing Chinese firms to buy in country. We're starting to see more and more restrict, you know, there's movement in the water around restrictions of letting Chinese firms access those types of chips abroad and with foreign cloud providers. And then there's also starting to be some interesting movement around restrictions when it comes to both data and algorithms.

27:01On the data side, you're starting to see new data walls be lifted with regards to electric vehicles in particular. We'll maybe see more coming forward. And then from an algorithmic perspective, two weeks ago, OpenAI said that they were no longer comfortable giving API access to developers based in the PRC. And that may be a harbinger of something larger. Congress recently gave this the power to explicitly stop algorithmic exports. So the wall slowly but surely is coming up. And the Chinese developers and semiconductor ecosystems response to this is really interesting because you're seeing very aggressive investment on the hardware side.

27:46You see stockpiling of chips and even billions of dollars of the best of what NVIDIA can legally export to them. Smuggling too is starting to be a real thing. We recently saw some mainstream coverage of. So, you know, there will be kind of gray areas and people trying to play corner cases to get more technology and access. Industrial espionage as well is something that's starting to bubble up a bit more. The scandal of sorts with Leopold Ashenbred are getting fired only for two weeks later, OpenAI to bring on General Nakasone, the former head of the NSA, to shore up their internal controls, I think is an interesting leading indicator of what's to come on that front.

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29:20That's public.com slash market. Paid for by Public Investing. All investing involves the risk of loss, including loss of principal. Brokered services for U.S.-listed registered securities, options, and bonds in a self-directed account are offered by Public Investing, Inc., member FINRA, and SIPC. Crypto trading provided by XeroHash. Complete disclosures available at public.com slash disclosures. Introducing the all-new Adobe Acrobat Studio, now with AI-powered PDF spaces. Do more with PDFs than you ever thought possible. Need AI to turn 100 pages of market research into five insights with a click?

29:53Do that with Acrobat. Need templates for a sales proposal that'll close that deal? Do that with Acrobat. Need an AI specialist to tailor the tone of your market report to sound real smart in real time? Do that with the all-new Adobe Acrobat Studio. Learn more at adobe.com slash do that with Acrobat. One of the things that you sometimes hear about restrictions on, for instance, semiconductor exports to China is the idea that by cutting off the country from all this external technology, you're only going to accelerate its own technological progress and its own development of leading edge chips and things like that.

30:33How much credence do you lend to those types of arguments? I think it's a moving target right now. I think logically, you would expect China to put all of its resources into building the best GPU possible, right? If we all think AI is going to be the next big paradigm shift for national competitiveness, not just market competitiveness. Yet, right now, because of, I will say, the effectiveness of US expert control, two rounds of expert control, and also working with allies around the world to solidify expert control, it's actually been a very difficult time for China to catch up from the hardware side, both in terms of designing the best GPU possible, but also to manufacture the chips in bulk using its own chip foundry, SMIC, because China's been cut off from TSMC, to be able to meet the demand that China itself, its own companies need to build its own product, let alone expanding to other parts around the world.

31:34And that's why you see all these behaviors still of either Chinese developers using VPNs and other ways to access OpenAI's API, or you have these sort of smuggling of prevented or prohibited media chips into China to be able to keep the building of the infrastructure going. And I think that goes back to what you were talking about, Tracy, earlier, is that there is a limitation to how much the national government wants certain things to happen and whether that could actually happen or not when it comes to especially building hard tech in China, when it comes to AI infrastructure in particular. We see a lot of pretty poor examples of government money being wasted in chip manufacturing already in the last few years before AI was even really a thing.

32:20And now it's in a very tough spot, I think, for a lot of people in China to be able to overcome the current hurdle. And I think this gap, this specifically hardware GPU imposed gap will only widen when NVIDIA mass produce its Blackwell chip, which is the next generation of GPU that's going to be produced in bulk starting next year, which has a huge performance kind of advantage, roughly 32 times more than the A chips, which is what OpenAI used to train GPT for. to be able to, you know, close that gap. So I think, unfortunately, for the Chinese technology builders, the gap will only widen. Jordan, I think you've talked about this before as well, the idea that if China is restricted in the amount of compute that it has access to, maybe there's a scenario where its own AI models just become really, really efficient in one way or another.

33:21Yeah, I mean, this is, you know, when you're under constraints, and there's money to be mained and, you know, engineers will find a way, right? So I, you know, on the compute side, right, you know, it's interesting thinking about Blackwell, only about 10 % of the gains that it is making from the past generation came from node size. The vast majority of the gains that they've been able to squeeze into the Blackwell system are from stuff like optics and interconnects. And that stuff, you know, high bandwidth memory, that type of stuff is a lot more difficult to export control than just one machine coming out of the Netherlands.

33:56So, you know, it's difficult. There's tens of billions of dollars of R &D that's been on this stuff, but it's sort of an open question to me how difficult re-engineering all of the innovations that went into Blackwell is going to be versus re-engineering an EUV machine, which like seems to be next to impossible. This is an important point just to jump in here. Like when people, when in pop culture, When people talk about chips, it's almost always like node size and smaller and smaller. I like the idea of like a vibrant pop culture of semiconductors. I'm not sure we're quite there yet. But this is how like ignorant people like myself, if I think like, oh, well, you know, the cutting edge chip is just in my mind, smaller node size.

34:37But this is like a really important point that you hit on that when actually, when we're talking about, say, NVIDIA GPUs, there are other dimensions that are actually much more important than node size. That's right. And, you know, if you look at all the new products that NVIDIA is releasing to the market, it's not a chip. Of course, you can buy a chip, but, you know, it's really eight chips together connected with high bandwidth memory and the interconnects and all the other elements that goes into a system. And the next generation, the packaging will be 36 chip and then 72 chip. And of course, there's a good reason for that, because all these models, if you believe that larger models become smarter models, then they need massive amounts of parallel processing to be able to train all these models efficiently and to deploy them efficiently.

35:22So that's why you tie up all these high performing GPUs together. And I think that's what makes this hardware gap even more difficult from a system level for even a cloud level to really overcome. I think, you know, before we've been talking a lot about the chip war between different countries, I think we're vastly quickly evolving into a cloud war between different countries competing on AI and technology in general, because it's all about the cloud and the system and how officially can you acquire and then utilize them. That makes a big difference. Tell me if I'm wrong here, but my sense also with like semiconductor rivalry, maybe to a lesser extent, but certainly with the AI rivalry is that it's mostly a competition between the US and China.

36:08Like as far as I can tell, Europe isn't necessarily obsessing about developing national chat GPT versions as much as, you know, the US and China are. Why is that? So, you know, I think from the semiconductor perspective, right, like it's really China and the rest of the world. There is a very integrated global ecosystem in which you have European players, East Asian players, South Asian players, the U.S. that are all kind of working together to push, you know, to push node sides and improve the sort and develop the sorts of technologies which are going into something like Blackwell. And China, you know, has kind of been cut off or is at some levels being cut off from that broader ecosystem and having to start to domesticate a lot of the technologies that they were able to formally rely on from other countries.

36:59Now, Kevin, I don't know if you want to talk to the like every country with its own model and own cloud thing, because I think that's a really interesting. Yeah, I'm curious about that. Yeah, I think, you know, not to beat on Europe too much, but I do think given just the regulatory, I would say, bias towards releasing new technology really quickly in general, it just isn't a very hospitable environment to be able to build a product like ChatGPT, which was really released, I believe, on a whim or on a quick competitive note. It wasn't something that super thought through. But because of the environment that we have in America, we allow that sort of things to happen.

37:36And then we think about regulation later. Coming back to the national angle, I think there is a strong sort of motivation coming back to the cultural point that every country does want its own national champion to some extent. I think France has Mistral, which it kind of puts up as its own national champion. It's a very strong open source AI model maker that has a lot of strong relationship with Microsoft as well. I think there's another company out of Germany that also is a model maker. So there are a few examples out there. Even Japan has, I believe, Sakana AI, which is its own possible startup national champion to model Japan's, you know, culture or truth or knowledge or whatnot into a national model.

38:19And India has a few others as well. And the Middle East is another very important region that is playing an increasingly large role. I think as the government actually pushed out some really good open source model about a year ago called Falcon, that series, which has been able to put the Middle East on the map when it comes to national development of AI models. So there is a lot going on, but certainly not nearly as much as the US-China competition besides that. Actually, you just reminded me, this is something I've always wondered as well, but what is the state of open source in China? Like, is it as much of a thing as it is in the States or elsewhere?

38:57What does that actually look like in terms of sharing code and things like that? So it's very much a thing. In fact, so I used to work at GitHub, which, you know, is one of the largest code repository of open source code and to drive international expansion. So I got to work with a lot of Chinese open source developers. And it's actually one of the very few, I would say, vibrant communities that really embrace a lot of openness, transparency. They have this really nerdy holiday on October 24th, which if you, you know, binary is, you know, two to the eights. But basically, it's called Programmer Day.

39:35And it's a completely grassroots holiday in China that celebrates open source development. They have, you know, a huge party, a huge convention, they talk about open source sharing, they all use, you know, GitHub or Hugging Face or all the your usual open source collaboration platform. So the open source kind of movement, if you will, has really deep roots in China. And that has been around for a couple of decades already, before we have this kind of open source, closed source model dichotomy that's happening in AI. In fact, a few of the nonprofits that are kind of government affiliated in China has released open source models, as well as a way to showcase what they have done as a way to kind of both compete, but also to collaborate with academics and researchers elsewhere.

40:22Yeah, you know, just coming a little more on the government open source connection. You know, it's easier to be, like open source is a good strategy, particularly if you're behind. We've seen a lot of investment on the hardware side with RISC-V, as well as Kevin mentioned on the software side. And, you know, I think it's still an open question, But a lot of there's a lot of chatter on the Chinese Internet about just to what extent the Chinese model makers are dependent on meta continuing to drop open source models in the Llama series. And, you know, we may if and when Zuckerberg decides that he's done playing the open source game, we may see a very different trajectory for the Chinese model makers if they're not able to kind of, you know, get their algorithmic and hardware shops in order before that.

41:12So we just have a few minutes left. But, you know, we talked about the current state of U.S. restrictions toward China or how the U.S. thinks about AI in the geopolitical context. There are chip export controls. There's more being done, you know, when it comes to cracking down on industrial espionage. There have been a lot of stories, including several broken by Bloomberg, about, you know, academic collaboration and, you know, trying limiting who can talk to whom. And we know that there's a lot of issues in academia related to computer science and tech and Chinese researchers in the US, etc. We have this framework, but it might all change because the president, the party of the presidency might change in a few months.

41:56What do we know, if anything, about the Trump view towards AI and AI in the geopolitical context? so i think the interesting about trump is that uh during his presidency his first term yeah he actually did have uh worked on national ai initiative of something which i believe is also chaired by eric schmidt the former ceo of google and he signed on to some kind of a national initiative plan in 2020 but it was you know middle of covet none of us had any time to pay attention and it just kind of like didn't go anywhere but he did have some kind of uh history with ai but But based on the most recent kind of national, the Republican National Convention's platform just being released, one of the line item is that they will overturn Biden's AI executive order.

42:44So Trump can put his own spin or his own branding or his own substance on AI when he if he does become president again. So we can expect a lot of kind of volatility on that front. And another thing that I would say that I think is the most consistent thing about Trump is his unilateralism, right? He's always been about America first, American only. And right now, there is a pretty good rhythm of global AI governance that's happening, starting with in the UCLA, the Bletchley Park Declaration, to a summit in South Korea earlier this year, to then another summit in Paris in February of next year, where you have world leaders, including China, and all the other relevant departments.

43:27and ministries around the world coming together to talk about AI governance in a global sense. If I were to put my money in the betting market about Trump, I think he will probably blow a lot of that out of the water to go to his unilateral instinct and really put America's stamp on this. And it's hard to predict what that will look like. Trump went on the All In podcast, maybe the podcast that must not be named on the show. No, it's fine. It was really remarkable because they asked him about China and AI. And he had like, you know, a moderately sophisticated answer, which was sort of shocking.

44:02He, you know, identified that it's a race between the US and China. And he also said that energy is really important to data centers. And we got to make that happen. You know, if you edited down his comments from five minutes to like 30 seconds, it was pretty coherent. But it was a remarkable thing that like he was talking to someone about this and they got like two halfway decent talking points in his head. So, you know, how he's going to approach technology in China is, I think, is a really open question. On the one hand, we had this very, like, well thought out, sophisticated playbook that he ran to basically get the world to turn on Huawei.

44:38On the other hand, you know, we had a lot of weird Trumpy stuff. Like with ZTE, the Commerce Department was basically going to kill it. She called him, said that it was going to cost too many Chinese jobs. And then he went on and tweeted the next day saying too many jobs lost in China. of like, we're going to give ZTE a reprieve. So he's really of two minds on all this stuff. Maybe someone talks him into being scared about inflation. Who knows? But I think there's a very wide range of outcomes, both on the sort of his domestic approach to artificial intelligence, as well as how he's going to think about technology competition in China.

45:11You said something there that actually I wanted to ask, and this is just about the sort of technological arms race again, but obviously within the US and the data centers, there is a lot of anxiety about access to electricity and how are we going to supply that? And we all know the U.S. is not in a good state these days. They like building things and adding a lot of energy capacity. Is that when you think about U.S. versus China in that respect, could that be a comparative advantage for the Chinese companies? I mean, I know China continues to add more nuclear generation and they're probably more liberal in terms of adding more coal power and other things like that, could they end up with an advantage based on their electricity grid and solving the power side of AI?

45:56You know, this might be a bit of a red herring. I am like cautiously optimistic that Republicans and Democrats will end up kind of giving some, you know, NEPA exceptions for these data centers, which like everyone is now agreeing is this like incredibly important national strategic resource. I mean, I think the bull case with China, right, is if they're stuck with less efficient chips and just have to build data centers twice the size that are twice as expensive, then like, yeah, maybe they can like throw on a few more coal plants and nuclear reactors to get them going. But I am cautiously optimistic that NVIDIA will continue to make increasingly power efficient chips and state, local, and national regulators will understand that this is something worth bending the rules on, which is sort of what you've seen on the sort of semiconductor fabrication build out over the past few years with the chips act.

46:47And if I can add one more point to what you just said, Jordan, I think a lot of the focus that we've talked about has been the algorithm, the model, how powerful the GPU is, but a lot of engineering sources has been devoted and will continue to be to reduce the power hungriness of AI model. Because one of the big things that's a hugely hotly debated topic is that All these tokens that we're generating for all these apps are just way too expensive, right? The expense comes from the compute and then the power that's being consumed to it. So there will be a lot of engineering that is going to accomplish when it comes to reducing the cost and the need for energy over time.

47:25So I don't think the energy trade is a long-term investment thesis, but maybe a short-term arbitrage as far as how much extra power we need just to feed a hungry AI data center when all the engineering is going to reducing that dependence because everyone sees how that could be detrimental in a lot of ways. Jordan and Kevin, thank you so much for coming on OddLots. That was fantastic. Our goal for the episode of understanding this more, I feel I do. So thank you both so much for coming on. Thanks for having us.

47:59Tracy,

48:04I thought that was great. I mean, there were just a bunch of things that like I, you know, even setting aside the geopolitical aspects that I just didn't know about what the AI space looks like in China. And that was very helpful right there. I'm sort of obsessed with the programmers day now. I want to learn more about the holiday. Do you think all the open source programmers, they like all get together to celebrate and do a dance, maybe a bite dance? Yeah. Oh. Boom. Come on. Okay, Tracy, you get it. We'll leave that one in. Thank you. Like the producers will add that cricket noise that we have on hand.

48:40I am also interested in the holiday. I do think so. Kevin's first answer, I just thought was like really clarifying about why a country might think that having a national version is important. Right. Because if and I hadn't really thought about it in those terms, because on some level. Right. Like it's easy enough. Like if it's, you know, llama, you can use that anywhere on, you know, various chips and stuff. But the idea that like the AI is going to like codify truth as it means in the context of that country. And, you know, if China, their version of what's true, Kevin gave the Jack Ma example, which is that one day he may be a hero and one day he may have a villain or maybe a villain.

49:24Like that's always changing. And so there may be some impulse to have the model sort of correctly reflect what is state policy. But this idea that like it capture, you know, creates this version of the national identity, culture and language is very interesting. No, absolutely. And I think China is sort of the extreme example of that. And that's sort of what I was alluding to. Not very well in the intro when I was talking about data control. But like there is this cultural element to AI where you are using something like chat GPT, or maybe not at the moment, but you could imagine a future where you're using something like chat GPT in the same way that you're using something like Wikipedia, where it's almost like the codified public version of events, right?

50:08And so if you are a government like China, why wouldn't you want to have some degree of control over what that's spitting out and the narrative that it's building? I was also really intrigued that, you know, we talk about chip wars all the time. But the idea that there is a distinction that is useful to make between a chip war and a cloud war and that, OK, there is, you know, we all know that like it was supposedly, you know, smaller nodes or whatever are better. although I think in the context of GPUs that's less important, but that so much of the technology is about the interconnect. And we talked about this with CoreWeave that there is a distinct element to building up a very powerful GPU cloud versus a traditional cloud because of the cables and the packaging, etc.

50:54And so the idea that it's about more than just like the chip itself and, the size of that chip, so to speak. No, absolutely. And one thing that really stood out from that conversation, and I'm thinking back, this actually happened when I was in Hong Kong and I was coordinating some of the news coverage there. But I remember the big crackdown on the sort of like retail internet companies like Alibaba. And I remember at the time, policymakers were very, very specific and very deliberate and very open about trying to direct more capital, you know, less disorderly capital flowing into SaaS, more capital going into hardware and making things like chips.

51:37It was almost, you know, for lack of a better tech analogy, it was like flipping a switch, right? They basically said like, no more money going into retail tech, everything going into semiconductor manufacturing and all that stuff. So it was, it was interesting to hear like, both the challenges and the opportunities from that perspective in China. By the way, I don't know if it was the Financial Times, but that was the first. Whoever came up with Chet, she, PT, that was very clever. That was very well done. I first saw that word in the FT, but that's a pretty clever term. That was a good one. I'm disappointed to find out it's actually vaporware, although perhaps not surprised.

52:17Okay, shall we leave it there? Let's leave it there. This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Joe Weisenthal. You can follow me at The Stalwart. Follow our guests, Jordan Schneider. He's at JordanSCHNYC. And check out his China Talk newsletter and podcast. And Kevin Hsu. He's at KevinSHu. And check out his writing at Interconnected. And follow our producers, Carmen Rodriguez at CarmenArmond, Dashiell Bennett at Dashbot, and Kale Brooks at Kale Brooks. Thank you to our producer, Moses Andam. And for more OddLots content, go to Bloomberg.com slash OddLots, where we have transcripts, a blog, and a newsletter.

52:56And you can chat about all of these topics 24-7 in our Discord, discord.gg slash OddLots. We have an AI room in there. Maybe when this comes out, we'll see if either Kevin or Jordan or both would be up for doing an AMA in there the day it comes out. I'm sure people have a lot of questions. So we'll try to make that happen. And if you enjoy All Thoughts, if you want us to, I don't know, start a pop culture semiconductor spinoff show, 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.

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53:45Thank you.

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