Get audio access with any FP subscription. Subscribe Now ALREADY AN FP SUBSCRIBER? LOGIN

Get audio access with any FP subscription.

ALREADY AN FP SUBSCRIBER? LOGIN

The United States has bet the farm on artificial intelligence across the board, from industry to finance to government policy. But the combination of a China shock and multiple cases of AIs gone rogue, set against the backdrop of a growing populist backlash, have forced a moment of truth that calls into question the foundational assumptions guiding U.S. development and regulation of AI.

The July release of Chinese start-up Moonshot’s Kimi K3 open-weight model, which proved nearly as capable as closed U.S. frontier models, stunned the American AI industry, which has largely ignored open models in favor of closed ones. Open-weight models provide users with free access to the “weights,” or the parameters that shape a model’s outputs, enabling easier customization and lower-cost access than closed models.

The United States has bet the farm on artificial intelligence across the board, from industry to finance to government policy. But the combination of a China shock and multiple cases of AIs gone rogue, set against the backdrop of a growing populist backlash, have forced a moment of truth that calls into question the foundational assumptions guiding U.S. development and regulation of AI.

The July release of Chinese start-up Moonshot’s Kimi K3 open-weight model, which proved nearly as capable as closed U.S. frontier models, stunned the American AI industry, which has largely ignored open models in favor of closed ones. Open-weight models provide users with free access to the “weights,” or the parameters that shape a model’s outputs, enabling easier customization and lower-cost access than closed models.

Until Kimi K3, many presumed that this ease of customization—and sharing of intellectual property in the form of open weights—meant sacrificing advanced AI capability. U.S. policymakers and developers prioritizing the pursuit of AI superintelligence were shocked when Kimi achieved both openness and frontier capability at once. Kimi K3’ s success raised the serious possibility that while the United States has been pursuing closed frontier capability, China has been running a different race—and winning.

So how did the United States go down what may be entirely the wrong path? Just what artificial general intelligence (AGI) would mean is widely disputed, but it’s a concept that’s used widely in American AI strategy. The most basic interpretation of AGI is that it means AI that matches or surpasses human intelligence—but this definition struggles to encompass the broad set of ideas that people hold when they talk about human intelligence itself.

Practically speaking, “AGI” is often used in the United States as a catch-all for the end goal of AI development, with little measurable or testable dimension to it. So, when and how did such an ambiguous, even eschatological, goal such as AGI become the endgame for American AI policy?

Much of the answer lies in Silicon Valley’s sci-fi-inspired, techno-utopian/techno-dystopian culture. An almost........

© Foreign Policy