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To prevent a reckless race, a proposed solution is a U.S.-China treaty to govern the resources needed for frontier AI. This would involve tracking and monitoring advanced AI chips in data centers and imposing a verifiable cap on the computational power used for any single training run.

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Dario Amadei's call to stop selling advanced chips to China is a strategic play to control the pace of AGI development. He argues that since a global pause is impossible, restricting China's hardware access turns a geopolitical race into a more manageable competition between Western labs like Anthropic and DeepMind.

A global AI safety regime should learn from nuclear arms control by focusing on the physical infrastructure that enables strategic capabilities. Instead of just seeking promises, it should aim to control access to chokepoints like advanced chip manufacturing and the massive data centers required for frontier models.

The same governments pushing AI competition for a strategic edge may be forced into cooperation. As AI democratizes access to catastrophic weapons (CBRN), the national security risk will become so great that even rival superpowers will have a mutual incentive to create verifiable safety treaties.

Vitalik Buterin suggests that slowing AI progress to buy time for safety is a valid goal. He argues the most feasible and least dystopian method is to limit hardware production. Since chip manufacturing is already highly centralized, it presents a control point that avoids more invasive, freedom-restricting measures.

The belief that AI development is unstoppable ignores history. Global treaties successfully limited nuclear proliferation, phased out ozone-depleting CFCs, and banned blinding lasers. These precedents prove that coordinated international action can steer powerful technologies away from the worst outcomes.

A pragmatic starting point for U.S.-China AI cooperation is to agree on verifiable red lines for proliferating dangerous dual-use capabilities, such as advanced cyberattack tools. This addresses a mutual security interest and builds the institutional trust and processes needed for more ambitious agreements on superintelligence.

International AI treaties, particularly with nations like China, are unlikely to hold based on trust alone. A stable agreement requires a mutually-assured-destruction-style dynamic, meaning the U.S. must develop and signal credible offensive capabilities to deter cheating.

As US LLMs achieve capabilities China can't match due to compute limitations, China may restrict access to critical rare earths. This move would be a strategic play to pressure the US into sharing its most advanced AI technology, linking resource control with tech parity.

The 2020 research formalizing AI's "scaling laws" was the key turning point for policymakers. It provided mathematical proof that AI capabilities scaled predictably with computing power, solidifying the conviction that compute, not data, was the critical resource to control in U.S.-China competition.

International AI treaties are feasible. Just as nuclear arms control monitors uranium and plutonium, AI governance can monitor the choke point for advanced AI: high-end compute chips from companies like NVIDIA. Tracking the global distribution of these chips could verify compliance with development limits.