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The US-China AI race is not a simple sprint. It's more like a bicycle peloton where the US, as the front-runner, does the heavy lifting of innovation. This means a unilateral US slowdown for regulatory purposes would likely decelerate the entire pack, including China, rather than simply handing it an easy lead.

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AI development follows the game theory of the nuclear arms race. If the U.S. slows down, it risks creating an asymmetric power dynamic where another nation like China could dominate. The goal is not to stop, but to achieve a global balance of power to ensure stability.

The argument that US AI regulation will cede leadership to China is flawed. China's AI progress often follows and copies US breakthroughs. By slowing the cutting edge in the US, we would also inherently slow the global pace of development, including in China.

The proposed data center moratorium, while intended to address safety, would create a strategic advantage for China and other nations if enacted unilaterally. An American slowdown without global agreement allows adversaries to catch up or surpass the US in AI, highlighting the prisoner's dilemma inherent in global AI regulation.

The rush to regulate AI in the US, driven by panic, is strategically dangerous. Because AI development is a global race, if the US slows down with poorly designed rules while China accelerates, it effectively cedes the most important technological advantage of the century.

A significant portion of China's AI progress is "parasitic," relying on copying or reverse-engineering breakthroughs from leading US labs. Therefore, a unilateral US slowdown on R&D could be the most effective way to slow down Chinese AI development, contrary to the logic of a competitive race.

A US policy that slows down its own AI labs for safety is logically flawed and self-defeating unless it also effectively slows China's progress. Unilateral deceleration doesn't make the world safer; it simply cedes ground to a less safety-conscious competitor, increasing net risk.

Self-imposed safety pauses and regulatory hurdles on US frontier models create a vacuum. Chinese open-weight models like GLM-5.2 are now as capable as the *currently available* US versions, eroding the American lead while its most advanced models are benched, effectively ceding ground in the global AI race.

The fear that a US slowdown will let China race ahead is flawed. China's AI progress largely relies on a "fast follow" strategy, reverse-engineering US breakthroughs. Stopping US frontier research would remove the trail they are following, slowing down the entire global race, not just the American side.

The proposal for US AI labs to slow down development is undermined by the fear that China won't reciprocate. Chinese labs are effective at incremental progress on existing paradigms, creating a classic security dilemma where any US pause could cede the technological frontier.

The US-China AI race is a 'game of inches.' While America leads in conceptual breakthroughs, China excels at rapid implementation and scaling. This dynamic reduces any American advantage to a matter of months, requiring constant, fast-paced innovation to maintain leadership.