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2028: Two scenarios for global AI leadership
Anthropic's new paper outlines two 2028 global AI leadership scenarios, arguing that US policy action on compute export controls and distillation attacks is crucial to maintain its lead over China and ensure democratic AI governance.
What: Authored by Anthropic, the paper presents two potential futures for AI leadership by 2028: one where the US sustains a significant 12-24 month lead by tightening export controls and disrupting distillation attacks, and another where China, benefiting from policy inaction, catches up. The US currently leads in advanced chip technology, but China exploits loopholes and uses distillation to mimic US models.
Why it matters: This research highlights the critical role of compute access and intellectual property protection in the geopolitical competition for AI leadership, suggesting that hardware and data security policies are as important as algorithmic innovation in shaping the future of global power dynamics and ethical AI governance.
Takeaway: If you work in AI policy or research, review Anthropic's paper for specific recommendations on maintaining US compute advantage and preventing intellectual property theft by foreign AI labs.
Deep dive
- Anthropic's paper models two scenarios for global AI leadership by 2028: one with a US lead, and one with China as a close competitor.* The US currently holds a strong lead in AI compute due to American and allied innovation in advanced chips and effective export controls by past administrations.* Chinese AI labs remain competitive by exploiting loopholes in export controls (smuggling, offshore data centers) and performing "distillation attacks" to replicate US frontier models.* A key policy recommendation is to close these loopholes and deter distillation attacks to secure a 12-24 month lead for the US and its allies.* This lead is seen as crucial for democracies to set global AI norms, ensure safety, and prevent authoritarian regimes from using AI for repression and military advantage.* The paper cites the "Mythos Preview" model, released by Anthropic as part of Project Glasswing in April, as an example of accelerating AI capabilities, which allowed Firefox to fix more security bugs last month than in all of 2025.* It emphasizes that compute advantage compounds into algorithmic advantage, making continued control over advanced semiconductors critical.* The competition is framed across four fronts: Intelligence, Domestic Adoption, Global Distribution, and Resilience, with Intelligence being the most important driver.
Decoder
- Compute advantage: A strategic lead in the availability and capability of advanced computer processing power, specifically high-end GPUs and AI accelerators, crucial for training and deploying large AI models.* Export controls: Government regulations that restrict the sale or transfer of certain technologies, products, or data to foreign countries, often for national security or foreign policy reasons.* Distillation attack: A method where an attacker systematically queries a larger, more capable AI model (often a proprietary "teacher" model) to generate data, which is then used to train a smaller, less computationally intensive "student" model to mimic the teacher's capabilities, essentially illicitly extracting its innovations.* SME (Semiconductor Manufacturing Equipment): The specialized machinery and tools used in the fabrication process of semiconductor chips, a highly advanced and capital-intensive industry.* Open-weight models: AI models where the trained model weights are publicly released, allowing anyone to download, inspect, modify, and run them, often used synonymously with "open-source models" in this context.
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