China Might Be Better at Capitalism Than the U.S.
How DeepSeek’s breakthrough shows the cracks in Silicon Valley’s monopoly-driven innovation model.
When I saw messages show up in WeChat group chats from journalists asking around whether anyone knows DeepSeek founder Liang Wenfeng or other leaders at the company, it was obvious the U.S. tech press had been caught flat-footed. Everyone is still scrambling to make sense of what DeepSeek’s breakthrough means—not just for AI, but for the tech stocks propping up everyone’s 401(k) these days.
One of the best takes on this came from Biden’s FTC Chair, Lina Khan in a recent New York Times op-ed. Khan makes a point that’s rarely acknowledged in the U.S.: China’s so-called "crackdowns" on Big Tech may be less about stifling innovation than about fostering competition. In the U.S., the reality is that Big Tech often functions as a brake on innovation. The larger these firms get, the more they prioritize rent extraction over genuine competition, buying up rivals and cementing their dominance rather than taking risks on disruptive new ideas.
This is one of the paradoxes of capitalism: left unchecked, it tends to create monopolies that block the very competition that’s supposed to drive progress. That’s exactly what’s happened in the U.S., where tech giants, despite all their money and legal protections, are now looking increasingly vulnerable to a more nimble and dynamic AI scene emerging from China.
DeepSeek’s big reveal underscores this shift. It’s not necessarily that their models are superior to OpenAI’s or Google’s in sheer power, but the way they’ve shown how stacking AI models is proving to be highly effective. This kind of efficiency and iteration—the ability to build on existing technologies in novel ways—is something that entrenched monopolies struggle with. When you’ve spent years consolidating your power and eliminating competition, the last thing you want to do is introduce something that might disrupt your own dominance.
Then there’s the familiar “China stole our data” refrain, which is looking increasingly flimsy. If data scraping is the crime, then U.S. companies are just as guilty. ChatGPT and other models were trained on vast swaths of internet data, much of it scraped without explicit permission. The real issue isn’t data theft—it’s about who controls access to these models and, ultimately, the narrative around them. The U.S. and China have taken similar approaches to AI development, yet only one of them is constantly accused of playing dirty.
Meanwhile, the fate of NVIDIA is unclear, as is the effect on its stock price. Will U.S. policymakers continue to push for tighter export restrictions, hoping to choke off China’s AI ambitions by limiting access to cutting-edge semiconductors? The logic of containment seems to be that if AI is a nuclear weapon then chips are the enriched uranium. But recent developments suggest China may not need NVIDIA chips to keep advancing in AI. If that’s the case, then what exactly is the goal of these export bans? If China can keep innovating without U.S. hardware, then restricting chip exports is less about technological advantage and more about political posturing.
The DeepSeek moment isn’t just about a single company—it’s a symptom of a much bigger shift in global innovation. For decades, the U.S. has dominated the tech industry, assuming that its lead was unshakable. But now, with the rise of new AI players in China, that dominance is being tested in ways that Silicon Valley—and Washington—weren’t prepared for. The question now isn’t whether China can catch up. It’s whether the U.S. can get out of its own way long enough to stay ahead.