China’s AI Rollout Has No Off Switch by Agathe Demarais at Foreign Policy

More analysis pointing out the U.S. may be engaged in the wrong AI race:

Decades later, Washington’s approach to the race in artificial intelligence rests on a similar logic: If U.S. labs do not double down, China will pull ahead and be the first to reach the holy grail of artificial general intelligence—that is, cognitive abilities that match or go beyond human abilities. Maybe. In the 1950s, the U.S. count of Soviet missiles ended up being wrong. This time, Washington could be measuring the wrong thing altogether with its focus on technological benchmarks. Beijing instead measures the success of its AI rollout in terms of adoption and diffusion across its economy and beyond. […]

While Washington focuses on the supply side—chips, data centers, and frontier models—Beijing treats AI as a tool to achieve broader long-term objectives, such as boosting manufacturing productivity, tackling a dire demographic outlook, supporting innovation, and fostering the diffusion of Chinese technology standards abroad. […]

The second pillar [of China’s AI plan] involves developing industrial applications for AI. U.S. consultancy IDC estimates that nearly half of China’s industrial firms had deployed specialized models or agents by mid-2025. That data is from more than a year ago—an eternity in the AI world—suggesting that the share of Chinese firms using AI is likely to be even higher now. Looking ahead, Beijing has even bigger goals. In January, China announced that it was aiming for 1,000 industrial AI agents, 500 application scenarios, and 1,000 showcase firms by 2027. Again, the focus is on applying AI widely and quickly, rather than top-notch benchmarks.

China seems to be focused on practical, immediate applications. Not on the frontier, but on good-enough. OCT 13 | REPLY

Rationalism and Divergent Sinomodernity by Farrell Gregory at Palladium Magazine

The history of Chinese AI governance can be read in state documents filled with slogans and measured statements. Public pronouncements and comments on AI reveal a consistent focus on practical application and cautious advancement rather than the pursuit of transformative superintelligence. In 2017, China released its Next Generation Artificial Intelligence Development Plan, which set the ambitious goal of becoming a world leader in AI by 2030. Importantly, this was framed in terms of industrial competitiveness and economic output, not the pursuit of artificial general intelligence. […]

America’s 2025 AI Action Plan then went on to model development as a winner-take-all race between America and China on the basis of LLM scaling, stating that “whoever has the largest AI ecosystem will set global AI standards and reap broad economic and military benefits.” A recent strategy document released by the White House Office of Science and Technology Policy mentions artificial general intelligence as a transformative technology, which “could present fundamentally new opportunities and threats.” Combined with the widespread perception that AGI is imminent for better or worse, the American AI strategy can reasonably be summed up as an LLM-scaling race towards superintelligence.

This does not seem to be how the Chinese see it. The Chinese AI+ Plan doesn’t mention competition at all, nor does it even mention America. Its focus is on diffusion, standards-setting, and making AI a value-add for other existing parts of the economy. Current Chinese AI policy involves decentralized distribution of benefits allocated by provinces and municipalities, supporting an open-weight ecosystem, and a multiplicity of regional labs. We should not necessarily take these documents at face value, but we should question why China’s AI narrative seems to ignore the “race to dominance” framework.

Makes a good case that China is playing a different game than the U.S. And given what Yuval Levin points out in his piece about AGI, one should consider that the race the U.S. is running may lead to a dead end. It’s interesting that both Levin’s piece and this article lay the blame for adopting the wrong worldview at the feet of the Rationalists and what looks to me like a sci-fi-inspired faith in an inevitable machine god. I get the sense that the wider society is paying more attention to what Rationalism actually holds, and it’ll be interesting to see what follows. How much power do Rationalists actually have at these labs? How indispensable are they? OCT 9 | REPLY

The Looming Closure of China’s AI Frontier by Ryan Fedasiuk at American Enterprise Institute

Recent open-source AI releases have crossed an important threshold of disruptive capability. On September 29, Anthropic reported that Z.ai’s GLM-5.3 approached the capability of its Mythos model at certain tasks related to cyber exploitation. Like Anthropic had done with Mythos, Z.ai at first delayed the release of GLM-5.3 to provide time to shore up cyber defenses.

But since August 28, the model has been out in the wild—its weights are freely downloadable on HuggingFace—with built-in safeguards that can be easily bypassed with creative prompting or removed altogether through a process coined “abliteration.” Some commentators have speculated this model may have been the one used to develop “WeWorm,” a critical exploit, first reported in September, capable of reaching the 800 million users of China’s most popular messaging app. […]

Beijing has ample reason to keep promoting widely available AI. Xi Jinping personally endorsed China’s open-source leadership at the World AI Conference in July. TC260’s governance framework is notably “nonbinding” and explicitly endorses an open-source AI ecosystem. But these priorities can coexist with restrictions on more dangerous capabilities—and we are likely to see these restrictions manifest soon. The likely outcome is a bifurcation in Chinese strategy: continued diffusion at the low end of the AI value chain, with Chinese labs increasingly withholding systems that Beijing regards as threats to social stability or state control.

Given sufficiently advanced cyber capabilities, I’d expect restrictions on open-weight models to become hard to avoid. There are already calls for this in the U.S. It will be interesting to see how this plays out constitutionally. My concern is that, given the national security implications, courts might rethink the First Amendment protections that now extend to code and data from cases like Bernstein and Sorrell. That could knock over a lot of the 30-plus years of ‘code is speech’ precedent. OCT 6 | REPLY