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Sharp Tech · · 16 min

(Preview) Xi Jinping and China's Tech Companies, The Long-Run Implications of the Chip Ban, and a Pessimistic Outlook for Taiwan

Ben ThompsonBill Bishop

Podcast
TL;DR
  • DeepSeek changed China’s AI psychology by showing that a chip-constrained company could build an internationally competitive open-source model: “Yeah, we can do this.” Bill Bishop called it a turning point that briefly “crashed the US stock markets” and NVIDIA while lifting Hong Kong-listed AI stocks; Ben Thompson noted that markets subsequently recovered almost completely.
  • Open sourcing gave China a rapid global distribution channel while disrupting domestic model pricing. Anyone can run DeepSeek instead of paying Anthropic for Claude or OpenAI, while Baidu, Tencent, and other Chinese providers were pushed toward free offerings—leaving the business model “not at all clear.” Ben cautioned that DeepSeek may have made the open-source decision itself rather than following a central-government directive.
  • The supposed $6 million miracle was a misreading of DeepSeek’s V3 paper, not a claim that the full R&D effort cost $6 million. Ben stressed that the figure covered one training run and explicitly excluded experimentation and R&D. DeepSeek’s breakthroughs remain genuine, but the mythology outran the disclosed economics.
  • R1’s viral breakout combined broad access, visible reasoning, China anxiety, and fear that billions in Western AI capex might be wasted. For many users it was their first reasoning model, and watching “my little AI friend” work through an answer made it feel better than paywalled alternatives; Bill questioned whether the surge was fully organic, then retained the view that it was “some mix” after hearing Ben’s “perfect storm” case.
  • DeepSeek prompted a competitive response from U.S. AI companies Bill called “fat and happy.” Ben cited falling AI pricing, more aggressive releases, a GPT-4o update with less of an “HR voice,” and Google models that were even cheaper and arguably comparable or better.
  • DeepSeek and xAI pursued very different routes to strong models. DeepSeek redesigned mixture-of-experts training around bandwidth limits and, Ben believed, H800 rather than H100 hardware; xAI raised “$16 billion or $12 billion,” bought NVIDIA hardware, used NVIDIA’s networking capabilities, and produced the apparently state-of-the-art Grok 3 only 19 months after founding. Ben noted that o3 may be better but is a distinct reasoning model unlikely to be released directly.
  • The unresolved investor question is whether ingenuity can keep compensating for restricted hardware over the next one or two years. Bill asked whether a real separation emerges if DeepSeek effectively can buy only Huawei Ascend chips while xAI and OpenAI keep buying better NVIDIA systems; the preview ends just as Ben begins laying out his concerns.
Digest · the substance, structured for research

1. DeepSeek turned technological scarcity into national confidence

  • Bill’s central claim was psychological: despite “this chip blockade,” DeepSeek found “very creative ways” to build an internationally competitive model. Making it open source transformed that achievement into “Yeah, we can do this.”

  • The market response dramatized the shift: Bill said DeepSeek “crashed the US stock markets, crashed NVIDIA” and sparked a Hong Kong AI-stock “melt up,” although Ben emphasized that prices later returned almost to their prior levels.

  • DeepSeek had originally been a hedge fund and quant fund that bought substantial NVIDIA hardware. Its CEO, Li Wenfeng, met Xi Jinping on Monday; Ben joked, “This is my quant.”

2. Open source globalized DeepSeek and disrupted domestic pricing

  • Bill’s distribution thesis was that anyone worldwide could download a strong Chinese model instead of paying Anthropic for Claude or OpenAI. Baidu and, Bill thought, Tencent integrated it, making open source “an incredibly powerful thing for China.”

  • Asked why DeepSeek open-sourced the model, Bill called it “a bait.” Ben cautioned that people overestimate how much the central government knew or cared about the decision and suggested DeepSeek may have made its own choices all along.

  • DeepSeek also disrupted China’s AI market: companies that had charged for models now had to go free. Bill saw no clear business model; Ben replied that the U.S. has the same problem, despite OpenAI and Anthropic generating subscription revenue that still does not cover costs.

  • Ben’s consumer thesis was sharper: ChatGPT had achieved tech’s hardest asset, a consumer brand with meaningful market share. Advertising was the “inevitable end state,” and OpenAI needed to reach it quickly so free users could receive its best possible models.

3. The viral moment was a perfect storm, not a $6 million trick

  • Bill wondered whether DeepSeek’s sudden rise on X and in the App Store was partly inorganic. Ben judged it “pretty authentic”; after hearing the case, Bill said he thought it was “some mix” and deferred to Ben’s more compelling case.

  • V3 arrived over Christmas after years of published papers. Its roughly $6 million figure covered only the specified training run—not experimentation or R&D—and the paper disclosed those exclusions plainly. Ben said people were twisting the figure to serve their own agendas, even though the paper was clear about what it did not include.

  • R1 then gave many users their first access to a reasoning model and exposed its thinking. Comparable reasoning models were paywalled, while OpenAI withheld its process for competitive reasons. Add China anxiety, billions in AI investment, and a stock market resting on that spending, and DeepSeek became “a current thing for a weekend.”

4. DeepSeek and xAI optimized for opposite constraints

  • Ben believed DeepSeek’s technical story because its architecture matched its claimed bottleneck. It reworked mixture-of-experts training to scale around bandwidth limits and, Ben believed, used H800s rather than H100s; DeepSeek’s CEO and employees had also identified chip access as the largest constraint.

  • Grok 3 offered the inverse case: xAI, founded 19 months earlier, produced an apparently state-of-the-art model by raising “$16 billion or $12 billion,” buying NVIDIA chips, and using NVIDIA’s networking capabilities to wire them together at scale. Ben qualified the comparison by saying o3 might be better, but that o3 was a distinct thinking model unlikely to be released directly; its Deep Research version was impressive but had clear flaws.

  • Ben’s comparative-advantage analogy was that startups must capture “lightning in a bottle,” while cash-rich incumbents can de-risk by buying the people behind a breakthrough. Facebook abandoned its Poke response and put Stories into Instagram. DeepSeek optimized scarcity; xAI purchased abundance. Both approaches fit their circumstances.

5. Competition improved quickly, but the chip-access verdict remains open

  • Ben saw a competitive response: AI pricing had already come down, OpenAI had become more aggressive in releasing products, and the GPT-4o update appeared less scolding, with less of an “HR voice.” Google offered models that were cheaper and arguably as good or better.

  • Ben stressed that DeepSeek’s engineering included genuine breakthroughs that would be, or already had been, adopted globally. The episode’s reaction reflected a mix of AI mythology and a reality that was itself “fairly spectacular” but not fully appreciated.

  • The long-run question remained unanswered: if DeepSeek continues to lack the best NVIDIA chips and can effectively buy only Huawei Ascend chips, while xAI and OpenAI keep buying better NVIDIA hardware, Bill asked whether “a real separation” emerges within one or two years. The preview ends as Ben says, “So let’s buckle up and get into it.”

Ben Thompson

Speaking of DeepSeek, one of my thoughts—and I mentioned it in passing when writing about it—is that there’s going to be some impact that’s hard to know now, but probably significant for China, almost more from a psyche-and-belief perspective. You go back to the idea that these are very hard problems that need to be solved. Money isn’t enough. Incentive is also not enough. You sort of need the belief that we can do this.

Is that a good read? Is there a bit where DeepSeek—which is a very good model; it’s not the leading model, but it’s in the class of the leading models, both V3 and R1, and beyond—has had, or will have, this positive impact? Do you anticipate this sense that, look, even the stuff the West is supposed to be best at, we’re just as good?

1. DeepSeek Builds Chinese Confidence

Bill Bishop

DeepSeek really created that view. There are other models: Alibaba has a model, Apple apparently is going to use it for Apple Intelligence in China, and Baidu has a model. But DeepSeek kind of came out of nowhere, and they open-sourced it.

Of course, after the DeepSeek story percolated for a few days, it crashed the US stock markets, crashed NVIDIA, and caused a real melt-up in some of the AI- and tech-related stocks that trade in Hong Kong. It was very much a turning point from a psychological perspective, in the sense that, yeah, we can do this. Even though we’re struggling under this chip blockade, DeepSeek showed that they could find very creative ways to maximize the hardware they had and build an internationally competitive model. Then they made it open source, so now everyone is using it. Baidu has integrated it, and I think Tencent has integrated it.

Are you running it yet on your local machine?

Ben Thompson

Oh, yeah. I downloaded it, or a smaller version. I don’t have beefy enough hardware to run the full model.

Bill Bishop

Right.

Ben Thompson

But, yeah, why is it open source?

Bill Bishop

It's a bait.

Ben Thompson

People overestimate the extent to which the central government knows or cares about this. I think DeepSeek may have made their own decisions all along. Is there a sense that, oh, this is actually really valuable—should we be open-sourcing it?

Bill Bishop

To what you said, I think they made their own decisions. They were originally a hedge fund. They actually got in a little bit of trouble around a crackdown on quant trading. They were a quant fund, and they had bought all this hardware—all these NVIDIA chips.

Ben Thompson

And Xi Jinping is now saying, “This is my quant.”

Bill Bishop

Right. It’s amazing how quickly he’s risen. Li Wenfeng, the CEO, was at this meeting with Xi on Monday. He met with the premier a week, 2 weeks, or 3 weeks ago.

But no, I think they just did it. They open-sourced it. Now, though, I think there’s a realization that this is an incredibly powerful thing for China because it’s a very good model and it’s open source. Anyone, any country, anywhere around the world can download it and have this Chinese model running instead of having to pay for Anthropic, for Claude, or for OpenAI. It’s a really fascinating way for a Chinese AI model—at least one Chinese AI model—to go global very quickly.

2. OpenAI Faces a Brand Threat

Ben Thompson

The reaction to it has been really interesting, because most people’s encounter with it is not downloading it to their local machine and running it. It’s using the DeepSeek app. But it speaks, just from a business perspective: I think that OpenAI—number 1, I said from the very beginning that ChatGPT was just an accident in many respects—had achieved the most valuable and difficult thing in tech, which is a consumer brand with meaningful market share.

Part of that is that your inevitable end state is advertising, and they need to get there fast so that they can give free users the best possible models. People got DeepSeek and thought, “Wow, this is amazing. It’s so much better.” Well, yeah, because they weren’t paying for the better OpenAI models. It wasn’t the best, but to a lot of people it felt like it was.

I don’t know: Was the propaganda effect of DeepSeek greater in China, or on people in the US and the West?

Bill Bishop

That’s a great question. I think what’s interesting in China is how quickly it changed the market, because now all these other companies that were trying to charge for their models have to go free, too. It’s not at all clear what the business model is around these models in China now.

Ben Thompson

That’s a question in the US, too. Don’t worry.

Bill Bishop

At least in the US, OpenAI has revenue. Anthropic has revenue from subscriptions—not enough to pay for it, not enough to cover costs, but still.

3. Why DeepSeek Went Viral

Bill Bishop

I’m a fairly skeptical person. I’m curious about the sudden surge of DeepSeek on social media, like on X and in the App Store. I do wonder how much of that was totally authentic and how much of it was inorganic.

Ben Thompson

Yeah, I know you mentioned that. I feel like it was pretty authentic. I think the meta bit is that V3 came out over Christmas. They had documented a lot, and they’ve been publishing papers and models for several years, so this wasn’t out of nowhere by any means.

I think V3 had some of those cost estimates, which were totally twisted and warped by everyone driving their own agenda. They were very clear in the paper that the cost they published was for the specific training run. It wasn’t for all the experimentation, all the R&D, and all those sorts of things. They never said otherwise. People are trying to paint it as if they were trying to trick people, but the paper is very clear. It lists all the things that the cost did not include.

So V3 comes out. It was the one that actually had that dollar figure, $6 million or whatever it was. It was a very, very good model that was very, very cheap. Then R1 comes out, and I think it was a combination of the fact that people hadn’t used reasoning models yet because they were paywalled.

Number 1, it was people’s first access to a reasoning model. Number 2, the UI—or the UX, I should say—for DeepSeek was better because it actually laid out its thinking. If that was the first time you used a reasoning model and you saw the model talking to itself and trying to figure out the answer, it was kind of charming. It was like, “Oh, look at my little AI friend trying to help me out and figure this out.”

OpenAI did not expose that for competitive reasons. They were saying, “We’re not going to list what we’re doing.” So you had a double whammy: it was behind a paywall, and it was behind a competition wall, or whatever you might want to call it.

Then you layer on the general angst about China—the idea that at least we have AI, and that’s our great hope. And then there’s the bit where we’re spending billions and billions of dollars. The stock market is resting on these investments of billions and billions of dollars. Is this all kaput?

I think all of those things created a perfect storm. It just became a current thing for a weekend. We’ve seen that happen before. There were so many factors that made sense for this to explode that I’m inclined to give the benefit of the doubt to it being organic, as opposed to inorganic.

Bill Bishop

Okay. I think it was some mix, but I will defer to you on that. You made a pretty compelling case.

4. DeepSeek Disrupts the AI Market

I will say what’s interesting is that DeepSeek disrupted, obviously, stock prices here and some videos.

Ben Thompson

And to be clear, everything is almost back up to where it was. It was very much a current thing.

Bill Bishop

Right. Yeah.

But the disruption was that they also disrupted the Chinese AI market, which is really interesting.

Ben Thompson

Right.

Bill Bishop

Right?

Ben Thompson

Yep.

Bill Bishop

This is where they went: They disrupted globally, and frankly, I think, good for them.

I think the U.S. AI companies needed to be disrupted. They were really fat and happy.

Ben Thompson

Oh, yeah. No, I mean, people were comparing OpenAI pricing. That's because their margins were super large. The pricing's already come down. They've already gotten more aggressive, I think, in releasing things. The GPT-4o update over the weekend appears to be significantly reduced in terms of the HR voice, like scolding you for things; it's more open.

And I think we're actually seeing a pretty compelling competitive response. By the way, Google has models out there that are even cheaper and arguably just as good or better. Again, it was just this perfect: everyone's perception got—it was a bubble—

Bill Bishop

Reordered.

Ben Thompson

—that got pricked, but if you were paying attention, it wasn't totally shocking.

Now, I hesitate—I almost feel bad saying that—because DeepSeek deserves so much credit, and the engineering they did was amazing. All their work, if you go back 2 years and read their papers—and I haven't read all of them, but I've read 3 or 4 of them—is really good stuff, with some genuine breakthroughs that are going to be, or have been, adopted globally.

But that almost makes the point. The myth of AI has always been a bit different from the reality, but the reality is also fairly spectacular and not fully appreciated either. So there's just this crazy mishmash.

Bill Bishop

No, it's interesting. Again, I think the U.S. Silicon Valley firms should thank DeepSeek for a lot of what they did, right? Because ultimately, even though OpenAI, Anthropic, and xAI could buy as many NVIDIA chips as NVIDIA can make, won't they be able to make their models run much more efficiently and much better if they learn from DeepSeek?

Ben Thompson

Well, this is the interesting thing. With Grok, Grok 3 just came out this week. It appears to be the state-of-the-art model. At least, o3 may be better, but o3 is this very distinct sort of thinking model that I don't think anyone is ever going to release directly. It is in Deep Research, which is incredible but has very clear flaws, to be clear.

But this is, at least for someone like me, a very visceral feeling: Yeah, there's a lot of jobs that are really screwed looking forward. I know the people who program have felt this way for a while because AI has made such a difference there. And so it's a state-of-the-art or state-of-the-art-adjacent model. What's incredible about xAI is that it was founded 19 months ago.

Bill Bishop

Right.

Ben Thompson

And now they have a state-of-the-art model, and it's almost the inverse. It's the flip side of the DeepSeek story, which is: it's incredible, these optimizations DeepSeek did. They completely rethought how you do a mixture-of-experts architecture, which is definitely better for inference, but it had all this training overhead. They changed how you do the training to be able to scale that much more gracefully because of their bandwidth limitations; they couldn't handle too much overhead.

And I also believe, by the way, they were using H800s. They weren't using H100s because—

Bill Bishop

Right.

Ben Thompson

—they did so many things with how they designed the model. That speaks to a company struggling with bandwidth limitations, which were exactly the sort of limitations they shared.

Bill Bishop

And they said that. I mean, they've said—the CEO has said, other employees have said—their biggest constraint is chips.

Ben Thompson

Right, which I think totally lines up with the way the model's designed.

Bill Bishop

Access to chips.

Ben Thompson

So I actually think DeepSeek—again, with China, with everyone in general, you just should be skeptical—but this is another case where I believe them. Everything around this story lines up with that.

Bill Bishop

Yeah.

5. XAI Takes the Capital Intensive Route

Ben Thompson

But xAI comes in, and they deliver this state-of-the-art model in 19 months. A big part of that is they've raised $16 billion or $12 billion, and they bought a whole bunch of NVIDIA chips and wired them all together. And how could they do that? Because they had access to the chips. Also, NVIDIA—one of their big differentiators is all the networking stuff they do, where they make it easy and possible to tie a ton of chips together to get this sort of performance.

And so you can look at American AI companies and say, “Wow, why didn't you do this optimization?” On the other hand, if you look at it from a comparative-advantage perspective, it's like—I always mock big companies trying to copy a startup. A startup invents something, and they're like, “Oh, we can do that, too.” Then you get Facebook releasing the Poke application. It's like, why are you trying to do that? Inventing something's really hard. You're almost capturing lightning in a bottle. When you're small and a startup, you do it because that's the only way to do it. And, by the way, most startups fail.

Bill Bishop

Right.

Ben Thompson

If you're a big company, you have large amounts of cash. You can de-risk by just going and buying the startup. Go and buy the people inventing it, bring them in-house. Or, in the case of Facebook, Poke was a response to Snapchat. What they actually did is just, “Okay, we'll just rip off Stories and put it in Instagram,” and basically stopped Snap in its tracks.

And it's not very glamorous, but it's actually recognizing your advantage. I think that's what we saw with xAI. Did they do the grunt work of DeepSeek to heavily optimize around a limited number of chips with low bandwidth? No, they just bought a bunch of chips because they had a bunch of money, but it also got them where they wanted to go.

Bill Bishop

Right.

Ben Thompson

Right? And so xAI and DeepSeek have totally different approaches, but both of those approaches are rational given their circumstances, and that in and of itself, I think, is an interesting takeaway.

6. Chip Access Shapes the Race

Bill Bishop

And then one of the questions, right, is, going forward, you push out 1 year or 2 years. If DeepSeek continues to not have access to the best NVIDIA chips and effectively can only buy Huawei's Ascend chips, whereas xAI or OpenAI can keep buying the better NVIDIA chips, do you start seeing a real separation?

Ben Thompson

I mean, that is the big question. There are a couple of concerns that I have about this, and I think we've talked a bit about this offline.

Bill Bishop

Yes.

Ben Thompson

So let's buckle up and get into it.

(Preview) Xi Jinping and China's Tech Companies, The Long-Run Implications of the Chip Ban, and a Pessimistic Outlook for Taiwan | BidClub