Contrary to common Western assumptions, China's official AI blueprint focuses on practical applications like scientific discovery and industrial transformation, with no mention of AGI or superintelligence. This suggests a more grounded, cautious approach aimed at boosting the real economy rather than winning a speculative tech race.

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.

The US AI strategy is dominated by a race to build a foundational "god in a box" Artificial General Intelligence (AGI). In contrast, China's state-directed approach currently prioritizes practical, narrow AI applications in manufacturing, agriculture, and healthcare to drive immediate economic productivity.

Unlike the Western discourse, which is often framed as a race to achieve AGI by a certain date, the Chinese AI community has significantly less discussion of specific AGI timelines or a clear "finish line." The focus is on technological self-sufficiency, practical applications, and commercial success.

Joe Tsai reframes the US-China 'AI race' as a marathon won by adoption speed, not model size. He notes China’s focus on open source and smaller, specialized models (e.g., for mobile devices) is designed for faster proliferation and practical application. The goal is to diffuse technology throughout the economy quickly, rather than simply building the single most powerful model.

Contrary to the narrative of a simple "tech race," the assessment is that China is already ahead in physical AI and supply chain capabilities. The expert warns that this gap is not only expected to last three to five years but may widen at an accelerating rate, posing a significant long-term competitive challenge for the U.S.

A key strategic difference in the AI race is focus. US tech giants are 'AGI-pilled,' aiming to build a single, god-like general intelligence. In contrast, China's state-driven approach prioritizes deploying narrow AI to boost productivity in manufacturing, agriculture, and healthcare now.

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.

While the US focuses on creating the most advanced AI models, China's real strength may be its proven ability to orchestrate society-wide technology adoption. Deep integration and widespread public enthusiasm for AI could ultimately provide a more durable competitive advantage.