While the US pursues cutting-edge AGI, China is competing aggressively on cost at the application layer. By making LLM tokens and energy dramatically cheaper (e.g., $1.10 vs. $10+ per million tokens), China is fostering mass adoption and rapid commercialization. This strategy aims to win the practical, economic side of the AI race, even with less powerful models.

For a blueprint on AI governance, look to Cold War-era geopolitics, not just tech history. The 1967 UN Outer Space Treaty, which established cooperation between the US and Soviet Union, shows that global compromise on new frontiers is possible even amidst intense rivalry. It provides a model for political, not just technical, solutions.

China is pursuing a low-cost, open-source AI model, similar to Android's market strategy. This contrasts with the US's expensive, high-performance "iPhone" approach. This accessibility and cost-effectiveness could allow Chinese AI to dominate the global market, especially in developing nations.

The current trend toward closed, proprietary AI systems is a misguided and ultimately ineffective strategy. Ideas and talent circulate regardless of corporate walls. True, defensible innovation is fostered by openness and the rapid exchange of research, not by secrecy.

An emerging geopolitical threat is China weaponizing AI by flooding the market with cheap, efficient large language models (LLMs). This strategy, mirroring their historical dumping of steel, could collapse the pricing power of Western AI giants, disrupting the US economy's primary growth engine.

A common misconception is that Chinese AI is fully open-source. The reality is they are often "open-weight," meaning training parameters (weights) are shared, but the underlying code and proprietary datasets are not. This provides a competitive advantage by enabling adoption while maintaining some control.

While the US prioritizes large language models, China is heavily invested in embodied AI. Experts predict a "ChatGPT moment" for humanoid robots—when they can perform complex, unprogrammed tasks in new environments—will occur in China within three years, showcasing a divergent national AI development path.

China is compensating for its deficit in cutting-edge semiconductors by pursuing an asymmetric strategy. It focuses on massive 'superclusters' of less advanced domestic chips and creating hyper-efficient, open-source AI models. This approach prioritizes widespread, low-cost adoption over chasing the absolute peak of performance like the US.

While the West may lead in AI models, China's key strategic advantage is its ability to 'embody' AI in hardware. Decades of de-industrialization in the U.S. have left a gap, while China's manufacturing dominance allows it to integrate AI into cars, drones, and robots at a scale the West cannot currently match.