(Photo Illustration by Justin Sullivan/Getty Images)Getty ImagesAnother day, another Chinese app makes it to number one on US app stores. In this case, the Chinese AI firm Deepseeks recently released large language model (LLM) topped the charts on Monday, knocking out ChatGPT.The company managed to make the rival LLM on a much lower budgetand without Nvidias most advanced chips, which the US Commerce Department has cut them off from. Deepseek researchers wrote that they used Nvidia's H800 chip for training purposes and spent $6 million. (On Friday, Zuckerburg announced Meta would be spending $60 billion on ramping up its AI infrastructure in 2025.)This feat casts doubt on America's data center buildout strategy epitomized most recently by the victory lap CEOs from OpenAI and SoftBank, plus Trump, took on day two of the new administration in announcing the Stargate project. The initiative will deploy $500 billion over the next four years to build compute infrastructure, and was in motion before Trump took office.But the Deepseek story offers a bigger lesson, if were willing to learn it: decoupling isn't working, and American users are a big part of the problem. US consumers are accustomed to chasing the best products at the best prices. That instinct, nurtured most explicitly by free market Republicans, is working against hawkish China policies.Earlier this month, when TikTok users turned to the Chinese app Xiaohongshu (or RedNote), we saw a popular rejection of banning an app because it's Chinese. National security doesn't resonate for the average young person the way it does for the average congressperson.In Deepseek, we're seeing a similar rejection of a US-imposed ban, but this time the interest is less of a protest vote and more of an old-fashioned market disruptionone that flies in the face of Washingtons efforts to cut China off from advanced technology. Were getting a close-up of what that looks like, since this Chinese companys success is perceptible in Americas stock market and app stores.Yet Deepseeks distance from US users might be part of its appeal. Mark Zuckerberg and Sam Altman's hyper-visibility, especially of late, can't be an unfettered boon for their AI products. It is difficult to proudly support billionaires who keep sticking their necks out, especially when eggs are $7.The startup, which is only a year and a half old, also touts an open-source approach, which appeals to some users (probably especially early adopters). That view is likely what motivated Meta to make its AI tools open source. Other American AI firms, like Google and the ironically-titled OpenAI, remain closed.The attitude underlying the instinct to hold ones cards close to the chest pairs well with the scale, baby, scale attitude among executives like Altman. Framing advancing AI as generally necessary, without providing explanation or specificity, betrays an evident hubris when held up to even modest examination.A similar nationwide arrogance motivates cutting China off from the most advanced US-made chips. It portrays a sense that only we can create what society needs from AI and distribute it, vaguely ethically, to them. Per OpenAIs Stargate notice, the company looks forward to continuing to build and develop AIand in particular AGIfor the benefit of all of humanity. In the meantime, everyone else should just follow the stock prices and the hype they instill.Deepseek managed to undercut many of performance-based assumptions over the last few weeks, but its achievements didnt become headline news until American user adoption skyrocketed and Nvidia stocks plummeted.While some observers are undoubtedly amused by a Chinese companys ability to burst Silicon Valleys (and Washington, D.C.s) bubble, Deepseek is not immune from chasing the same lofty goals (the company was founded with the express mission of realizing artificial general intelligence).Yet Deepseek founder Liang Wenfangs success in furthering these plans with relatively little amounts of pomp, circumstance, and funding compared to his US peers still looks, from the outside, like an underdog story. That has universal appeal, even if its not quite accurate.The firms American policy and technology communities, both of which have repeatedly pledged mind-boggling financial support for American-made AI, could learn something from an observation Liang made over the summer: More investment does not necessarily lead to more innovation.