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Unlike the US's public-private debate over Anthropic's powerful AI model, China's equivalent will involve a more consolidated power dynamic. A closely-held private company will face a much more aggressive government, creating a different and potentially more dramatic outcome for AI control.

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The dispute highlights a core tension for democracies: how to compete with authoritarian states like China, which can command its AI labs without debate. The pressure to maintain a military edge may force the U.S. to adopt more coercive policies towards its own private tech companies, compromising the free market principles it aims to defend.

The US government is restricting Anthropic's commercial rollout of its new model, Mythos, over concerns it could hamper the government's own access to compute. This move treats AI capacity as a strategic national resource and effectively creates a de facto licensing system for powerful models, marking a new era of AI governance.

If an AI model like Anthropic's Mythos is capable of causing 'cataclysmic' economic damage, it may be too powerful for a private company to control. This raises the serious argument for nationalizing such technology, similar to how governments control bioweapons or nuclear capabilities, to manage the immense systemic risk.

When a private company creates a "digital skeleton key" capable of compromising critical national infrastructure, it fundamentally alters the balance of power. This moves the policy conversation beyond simple regulation and towards treating AI labs like defense contractors, with some form of government nationalization becoming a plausible endgame.

The public, acrimonious dispute between the Pentagon and a leading U.S. AI firm is a strategic gift to China. While America's defense-tech ecosystem is distracted by infighting and political risk, China continues its comprehensive and focused military AI development unimpeded.

In China, academics have significant influence on policymaking, partly due to a cultural tradition that highly values scholars. Experts deeply concerned about existential AI risks have briefed the highest levels of government, suggesting that policy may be less susceptible to capture by commercial tech interests compared to the West.

The argument that the U.S. must race to build superintelligence before China is flawed. The Chinese Communist Party's primary goal is control. An uncontrollable AI poses a direct existential threat to their power, making them more likely to heavily regulate or halt its development rather than recklessly pursue it.

The US and China view AI superiority as a national security imperative comparable to nuclear weapons, ensuring massive state funding. However, this creates a major risk for investors, as governments may eventually decide to nationalize or control leading AI companies for military purposes, compressing multiples.

A key risk to OpenAI's trillion-dollar valuation is not just market competition, but the rise of a state-backed, parallel AI ecosystem in China. This creates a future where global AI leadership could be fragmented along geopolitical lines, challenging long-term dominance.

Ben Thompson argues that if AI is as powerful as its creators claim, they must anticipate a forceful government response. Private companies unilaterally setting restrictions on dual-use technology will be seen as an intolerable challenge to state power, leading to direct conflict.