Prof G Markets - How China Wins The AI War

Episode Date: May 7, 2026

Ed Elson speaks with Alice Han about where the AI race between China and the U.S. stands today. She breaks down DeepSeek’s $50B valuation, where the U.S. still holds an edge, and how China’s chips really stack up to Nvidia’s. Finally, Ed explains why AI might be making us all dumber. Alice Han is a Director at Greenmantle and Co-Host of the China Decode Podcast.  Get your tickets to the Prof G Markets tour  Subscribe to the Prof G Markets Youtube Channel  Check out our latest Prof G Markets newsletter Follow Prof G Markets on Instagram Follow Ed on Instagram, X and Substack Follow Scott on Instagram Send us your questions or comments by emailing [e-mail] Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Megan Rapino here. This week on a touch more, I'm talking to my good friend, former soccer player and current soccer analyst Lori Lindsay about all things NSL, the past, the present, and the future. Plus, I'm taking a look at the athletes who crushed at the Met Gala and Angel Rees firm boundaries with the media. Check out the latest episode of a touch more, wherever you get your podcast, and on YouTube. Today's number 15.

That's the percentage of Americans who say they'd be willing to take a job where their direct supervisor is an AI program. We're not sure if that tells us how good American AI has gotten or how bad American bosses are. Money markets matter.

If money is evil, then that building is hell. Welcome to Profitjee Markets. I'm Ed Elson. It is May 7th. Let's check in on yesterday's market vitals. The major indices extended their rally on reports that the US and Iran were reviewing a deal to end the war and gradually reopen the Strait of Hormuz. That news also sent Brent crude tumbling. Treasury yields also dropped. Meanwhile, AMD stock soared nearly 20 percent. after the chipmaker beat expectations and raised its guidance. Okay, what else is happening? Chinese AI startup DeepSeek is targeting a $50 billion valuation

in its first ever fundraising round. Leading the financing is China's biggest state-backed semiconductor investment vehicle known as the big fund. The country's goal? Build a full-stack AI ecosystem that can rival the United States. States. Deepseek first grabbed Wall Street's attention last year with R1, a powerful model that was built at a fraction of the cost of leading Silicon Valley LLMs, and last month it released V4, a model that is now competitive with top U.S. players on a number of benchmarks. So, here to discuss

DeepSeek and the state of the U.S. versus China AI race, we are speaking with our friend Alice Han, director at Green Mantle and co-host of the China Decode podcast, Alice, thank you for joining us again. I kind of want to start with the valuation here, $50 billion, because at first glance, it seems quite low when you compare it to Anthropic, which is trading at a trillion, chat GPT, open AI, sorry, also trading it a trillion on the secondary markets. These companies are ready to go public. And then I also know that this is an extremely powerful model. It's It's extremely popular. It's the leading model in China.

So I guess that number of $50 billion strikes me as small. I guess would you agree? And then also, what else strikes you about this news? I completely agree, Ed, but this is a feature, not a bug of Chinese valuations. Even if you look at Chinese tech companies historically, the valuations, the Ford P's, much lower than what you see in the Mag 7, what you see in the US. This is a feature of Chinese capital markets, just not being as developed as they are in the US. And more importantly, in terms of the fundraising for Deepseek itself, yes, there will be some

private fundraising, but it's largely, I think, going to be state-led as opposed to what you're seeing in the US with the anthropics and the open AIs of the world. So I think it's completely reasonable and within the bounds of what I expect that this valuation is, you know, orders of magnitude lower than what we're seeing in the States. More importantly, I think when you look at the capabilities. What has been interesting is that it is now announced DeepSeek v4 that it can do a one million token context window. This is comparable to Gemini and what we're seeing out of Anthropic and Open AI. But there's big, big questions moving forward about the hardware side of things which we can get into. Will Deep Seek be able to access via Huawei and elsewhere, the

kind of chips it needs to continue to power its models? Well, this is, that is exactly where I would like to go. And actually, I want to play a clip for you. This was an exchange recently between Jensen Huang and Dworkesh Patel, is a podcaster who had Jensen Huang on his program. And they were talking about China and the fact that Nvidia has been selling chips to China. And it got quite heated, and it really pressed on this exact issue of,

should we be selling chips to China, if they're going to use those chips and use them to develop extremely powerful LLMs and AI models. Let's just play the clip and get your reaction. The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation. Why is that? Because, I mean, currently you can have a model like Deep Seek that can run on any accelerator.

Why would that stop being the case in the future? Well, suppose it doesn't. Suppose it optimized for Huawei. Suppose it optimized for their architecture. It would put ours at a disadvantage. You described the situation. A company developed software, developed an AI model,

and it runs best on the American tech stack. I saw that as good news. You set it up as a premise that it was bad news. I'm going to give you the bad news that AI models around the world are developed and they run best on not American hardware. That is bad news for us. So I guess the striking thing here is, one, is how uncomfortable Jensen Huang appears to be when he gets this question about China. I mean, this is the first time I've seen him as defensive as he was in this exchange. But it does get to the heart of that question, like, should we be selling chips to China? And also, where are we in that stage?

Because we know that the policy's gone off, on, off on, we keep on changing our minds. If you could just dive into all of that for me. Yeah. Well, first, I'm a big fan of both Jensen and Dorcas, and I listen to that very attentively, very recently. I would say just to break it down a little bit, what is important is that Huawei's the CEN-950 PR, which just came out and has been powering the Deepseek V4, the big companies like Bidtads, Barber, Tencent, are now rushing to order these chips. These are inference chips.

And so just looking at the stats alone, they can perform better on inference by 2.87 times more than the existing Nvidia chips that can be sold to China. These are the H20s, not the H-200s. Although those have been approved, China hasn't allowed those imports as of yet. And secondly, they improve the multimodal generation efficiency by 60%. So just looking at what is available from NVIDIA compared to Huawei, apples and oranges, Huawei is doing better on the inference side of things. But if you compare that to the H-200s or if you compare that to the Rubens,

Huawei is still a great deal behind. But it seems like Beijing is trying to prioritize a domestic ecosystem, a domestic marketplace of inference chips such that it will no longer have to rely on NVIDA. So basically, exactly what Jensen Huang expressed as his big fear to Doakash, which is that if you continue to push China with, for instance, there's chip export controls, the chip equipment export controls that just recently have been announced against Hua Hong, which is a major Chinese semiconductor company, then you incentivize across the system.

supply chain, China to say, hey, we are not going to import your next generation, although they will be outdated of chips, we want to prioritize what is coming out of Huawei and SMIC. Now, what does that mean for Chinese AI companies? It means that, yes, to some extent, the performance will be behind what you see in America, but the way that I think about it is that it creates good enough alternatives. China is prioritizing inference, and inference is still an open game in terms of the chip-making capabilities. Yes, Nvidia is really the king when it comes to the training side of the chip infrastructure, but it's still unclear whether or not it can be the winner when it comes to inference chips.

And here I think the Chinese companies like Huawei and Smic could really give Nvidia run for its money in the long term. But right now, Nvidia is the clear leader. A lot of U.S. companies like Broadcom, AMD, are also clear winners. the last thing that I will end on is that currently there isn't enough chips being produced domestically by Chinese chip makers to meet the demand on compute and inference. And that is going to be in the short term of the biggest bottleneck. China ordered these Chinese companies, rather ordered 2 million H-200s earlier this year

because there was so much demand for its AI models. None of that has been approved, obviously, by Beijing. right now Huawei is saying that it can do 750,000 units of its ascend chips. If you just look at the numbers alone, and if you even look at sort of the longer term statistics on how many chips China can produce and the compute output, China is, by some estimates, only going to be able to produce 2% of what NVIDIA and TSMC can produce in 2027

by looking just at compute outputs. That is, I think, huge. But right now, the political priority trumps what is efficient, and the political priority from Beijing is to kickstart a domestic ecosystem that will be able to rival NVIDIA long term. So just going back to some of those chips that you mentioned there, so you got the NVIDIA H20, which was the chip that was essentially designed to be a dumber, slower chip than the highest end that is created by NVIDIA. that was designed for China. And you're telling us, Huawei's now got a chip that is three times more powerful on the inference perspective, almost three times more powerful. So they're not interested in those H20 chips so much anymore, it seems.

But still significantly behind the H200 and the Rubin, and those are Nvidia's really fantastic chips, and they're still behind on that front. I guess the question then becomes like, how far behind are they? And also, how quickly have they improved recently? Because Huawei, I mean, it was a name in the AI world, but not that big of a name. And suddenly it seems to be gaining a lot of momentum and a lot of steam. As an observer, I'm reading about it a lot more. I mean, are they getting close to a point where they could actually rival

Nvidia's most advanced chips, which we do not allow to go to China? They're not yet close. But there are smart workarounds. So firstly, on the training front, obviously there's a lot of news about Chinese air companies distilling models coming out of Anthropic and OpenAI. That helps them. It's almost as if it's a student cheating on an exam and it's just copying a smarter student, right? This is what is allowing them to really catch up. On the inference front, and the inference is really, you know, when a student having learned the information takes the exam,

so even the answers to the queries that you give to, say, an LLM or to an agent. Here, Chinese models are actually doing extremely well. And I think the long-term bet is that if a Huawei can produce a lot more in terms of chips, it can do these clusters. And you may have heard of this idea of this cluster architecture. So, for instance, if a Huawei chip is 10 times less compute efficient than an Nvidia chip, maybe you cluster 10 of them to equal the equivalent of an Nvidia. That, I think, will be the long-term bet.

A lot of it rides on how much capacity Huawei and Smith can do. Right now, and this connects to Iran, there is a real risk that helium, for instance, which is critical for chipmaking, is actually going to be a bottleneck and a headwin for Chinese chipmakers. Another thing that could be a headwind is if the U.S. decides it's actually going to do more restrictions on chip equipment. China's even more reliant actually on the chip equipment providers, like an AMD, for instance, and ASML. if there are more restrictions there, that could again set back China's domestic chip production. We'll be right back after the break. And by the way, we are heading out on tour at the end of the month. So if you want to get tickets to a show near you, head to profi-marketstor.com. It's going to be a lot of fun.

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I'd give us like a C plus. There is no perfect past, but there is also no exclusively negative past. Because humans are going to human. That's what we do. I think the story of America is the struggle of people who have not been included in the promise of America to expand those principles to include more people. What's going to determine the next 250 years of America? And how do we write a new social contract that can give us the democracy we deserve?

Okay, so I'm just going to be a jerk here because I'm a historian. So we have to have a prologue explaining, you know, we the people. Okay. You know, I do still remember it from Schoolhouse Rock. We the people, in order to perform a more perfect union, established justice. What is it? Ensured domestic tranquility? So you're talking about a foundational document.

So I'm building a document that will protect American democracy. That's this week on America Actually. This week on Network Therapeutic. and chill, I'm joined by Tank Sinatra, the meme king, with over 15 million followers across Tank's good news, influencers in the wild, and his personal account. Tank is breaking down what the meme economy really is, how much a single sponsored post pays, why major brands are throwing serious money at jokes, and how meme culture, think Preparation H, starter packs, and a perfectly timed screenshot is actually reshaping how we think about money and value. Get ready for

a conversation that will change the way you scroll, make you rethink what, going viral is really worth and prove that sometimes the most serious money moves are wrapped in the silliest of jokes. Listen wherever you get your podcasts or watch on YouTube.com slash your rich BFF. We're back with ProfG Markets. When you think about all of the different, I guess, pieces of leverage, or I guess all of the different races would be the right way to describe it. I mean, you've got compute capability.

America's winning on that front, it seems. You've got energy, you've got supply chain, you've got, I think access to the Strait of Hormuz seems to be increasingly an important piece of this. And when you think about all of the different fronts on which the AI war is being waged, on which of them is China winning against America and on which of them is America winning? So I think about it as a five-layer cake, and in this regard, I was happy that Jensen Huang also had a similar framework. You know, from upstream to downstream. So we start from the upstream, which is going to be, you know, basically the rare earths that are used, for instance, that power semiconductors and data centers.

This is where China has, you know, huge dominance. We've seen that as of last year as well with the export restrictions. The second layer that we're going to look into is the energy layer where China, again, has, it seems, an electricity front, a great deal of leverage. It has, you know, twice the amount of electricity output that the Americans have. And that is going to be a bottleneck for American data center rollout as well moving forward. Number three is the data center infrastructure layer, where the U.S. has done exceptionally well. China will only get to 60 gigawatts. It's targeting by 2030. The U.S. is basically already there as of now. And then the fourth layer is going to be

the models themselves were again, you know, based on the status quo right now, the U.S. is still leading, although that gap is at times closing because Chinese models are getting more efficient. They're distilling and improving at a rapid pace. And then it's the application layer where I actually think it's a bit of a mixed bag. China is making really interesting applications. This is why META wanted to buy and failed to buy Manus. its agentic AI that came out of mainland China and moved to Singapore.

I think there will be really interesting applications coming out of China, especially on the agentic front. They could rival what you see in America. It's not just an LLM game, and that China has proven that. So I see it as a five-layer cake. Right now, it's really mixed across the board, but China tends to dominate on some of these upstream as opposed to downstream. You mentioned Manus there, which is this company that Mehta was trying to buy as a Chinese company, or I guess a Singapore-based company, but has Chinese roots. And then Beijing banned it, which seems to sort of lend itself to the argument that this is becoming quite a hostile race. It's fully a competition. If America tries to get access to stuff that's happening in China as it relates to AI, Beijing will ban it. They will stop it. Same thing is true over in America.

And an analogy that I am increasingly hearing when it comes to the AI race is that it's sort of like getting your hands on a nuclear weapon. And this is more and more relevant, the more we hear in the headlines. I mean, anthropic coming out with mythos, and we learn that there's this AI technology that could hack every single cybersecurity system in the world. It could literally bring the infrastructure, the digital infrastructure of a nation to its knees. it's seeming more and more that maybe it's a fair comparison, but I don't know, maybe it's a bridge too far. Do you think that that is a reasonable analogy when it comes to the AI race?

Just to clarify, which analogy in particular are you preferring to Ed? The nuclear weapon. The nuclear weapons. You know, Kirstenger, before he passed away a couple of years ago, wrote a book, as you probably know, with Eric Schmidt, and in which he basically said that AI and autonomous weapons was going to be what nuclear weapons were during the Cold War when he was Secretary of State and National Security Advisor. And he was deeply worried so much so that he, in the last few years of

his life, went to Beijing to speak with Xi Jinping and high-level officials to set up the framework for strategic dialogue, which Biden did take up towards the end of his administration, a strategic dialogue between Beijing and Washington on AI arms controls. Now, there's an open-end question as to whether or not when Trump meets with Xi's likely next week in Beijing if there is going to be a kickstart to that discussion and new strategic dialogue will emerge. But I was just in Beijing last week, Ed, and what was very startling to me was the level of fear as to how effective US AI technology has been in its application in the Iran conflict. There was a lot of concern as well about the use of Claude by

the Department of War by the defense community in America. And when Mithyos came out, I've seen a consternation in China about what that means for Chinese national security. One thing that I will end on is that this is part of the reason why China has tried to make AI not just an economic issue, but also a national security issue. It also made quantum a national security issue, too. Quantum is also going to be key for decryption and encryption, to your point, if there is going to be a mythos that can hack into every system, quantum may be able to leapfrog that and create a new fortress. So these are all these ongoing concerns, but I think the view from Beijing right now is that there needs to be high-level strategic discussion.

I won't be surprised if after this meeting between Trump and Xi, there is a revival from the Beijing side about ongoing strategic dialogue concerning AI work. weapons because right now things do look very scary from China's vantage point. Just going back to the Dworkesh Jensen Huang interview, I mean, it seemed like there was sort of this miscommunication in the dialogue where on the one hand, the argument is being made to Jensen Huang that if AI is a nuke, if it is comparable to a nuke, you shouldn't be selling equipment that they are going to use to go and build that nuke. and therefore nuke America. And then he's saying, no, they're already going to, they're already building it.

They have the ability. So do we want them to be using U.S. made equipment or do we want them to be using China-made equipment? Which I feel like didn't quite get to the heart of the disagreement. And something I was thinking about this, and I'd like to get your thoughts, I mean, running with the nuke analogy, China has nukes. Yeah. they haven't dropped them on the U.S. And the reason they haven't dropped them on the U.S. I think is because they don't want to.

Mutually assured destruction. Mutually assured destruction. And so to me, I just, it seems as though this question of the AI race between America and China, increasingly it's not actually about the technology. It's about diplomacy. And it's about the relationship between the two. And it's about getting us to a place where China doesn't feel that there is any reason to drop the AI equivalent of a nuclear bomb on America.

And it seems to be that that's the trajectory where this is headed. This is a political discussion, not a technological one. I'd just be interested to get your thoughts on that and how this topic is kind of evolving. I love that question. As I was listening to that podcast, it was clear that neither of them were historians or politics majors as they approached the question.

Because as you know, China built them with no American help. It was largely Soviet aid, and then they had engineers, physicists who came and built it by 64, they surprised the world by launching a successful nuclear test in China. That shows you historically that China can, in this AI age, create its own AI capabilities without American largely support or input. I think what they confuse is this question, can in the meantime Wall Street monetize China's AI development? Clearly, Jensen has an incentive to make that case, which benefits parts of America. But regardless of that argument, China will find a way to create a rival AI system. If that AI system is antagonistic or not, that question and its answer resides on your point,

which I completely agree, is there going to be continued strategic dialogue and diplomacy? Kissinger understood this and he was harping on about it even towards the end of his life. And I think it would be very, very sad and ultimately tragic for humanity if we don't have Washington and Beijing continue discussion about their capabilities and intentions as it pertains to AI. And more importantly, if there isn't track to diplomacy where these Chinese tech companies are also involved, because you also need experts in the room to help both sides assess the capabilities. My concern right now is those two sides, both on the expert side,

as well as on the diplomatic side, are very far apart. And that, as Kessinger rightly predicted in his last book on AI, is going to create massively tragic outcomes that we have yet to seem far greater than we have yet to witness in our lifetime. But if we do ultimately come to a point where there is mutually assured destruction in AI, then we may be able to achieve equilibrium. But that rests on both sides having extremely strong and telegraphed AI capabilities. Alice Hahn, director at Greenmantle, co-hosts of the China Decode podcast.

Alice, Trump and she are likely to meet next week. Maybe we'll get some answers when that happens. Thank you so much for joining us. Thanks so much, Ed. Here's a question for you. Is AI making us dumber? That is the question our research lead Mia Silverio asked in one of her recent substacks, and her findings were pretty conclusive.

The answer is yes. According to Dr. Jared Horvath, a neuroscientist who recently spoke in front of Congress, every generation in history has been smarter than their parents' generation except for Gen Z. Young people underperform on, quote, every cognitive measure from IQ to literacy to basic memory skills. One look at the data will confirm that this is indeed true. Roughly half of American 12th graders are now scoring below a basic level of math, and roughly a third of them don't have basic reading skills. In fact, that is the worst rating that we've seen among that group in three decades, but it isn't just America.

Over the past two decades, science, math, and reading scores among teenagers in high-income countries have all fallen nearly 5%. Meanwhile, literacy rates for adults have fallen roughly 3%. In some, yes, we are literally getting dumber. Now, is this just because of AI? No, as Mia points out, there are other factors such as social media addiction and also the pandemic, which stunted learning for millions of children around the world, but we should also acknowledge the extent to which AI is still playing a role here and the fact that it actually is accelerating the trend. One study found that students who use AI tools for homework assignments experience a 55% reduction in overall brain activity, which means that when you use chat GPT, your brain is actually more impaired,

more suppressed than if you were to be twice over the legal alcohol limit. However, unlike alcohol where your brain can actually recover over the long term, the impairment effects of using AI appear to compound even after the AI tool is removed from usage. In other words, every student in America is effectively operating as if they were a drunk driver. So will AI make us more productive as a society? probably, but will it also make us dumber as a society? Certainly. In fact, it already has. If you want to read more about this, you can go check out Mia's work at substack.com slash Mia Silverio. She discusses this trend in detail and also many other interesting trends in business and in the

economy. That post is called, is AI making us dumb? The answer is yes. Okay, that's it for Today, this episode was produced by Claire Miller and Alison Weiss, edited by Joel Passon and engineered by Benjamin Spencer. Our video editor is Brad Williams. Our research team is Dan Ceylon, Isabella Kinsel, Chris O'Donohue, and Mia Silverio. And our social producer is Jake McPherson. Thank you for listening to ProfG Markets from Profg Media. If you liked what you heard, give us a follow. I'm Ed Elson, and tune in tomorrow for our conversation with Daniel Juergen.