Commentary: How China Could Keep Up With the Global AI Race

On August 7, OpenAI released GPT-5, its most advanced large language model, featuring superior capabilities in reasoning, coding, writing, and multitasking. Notably, GPT-5 has a significantly reduced hallucination rate and faster response times due to intelligent routing. A basic version is available for free users, while premium users receive higher API limits. Sam Altman, OpenAI’s CEO, called it “like having a Ph.D. expert at your side,” highlighting its significance as a step toward artificial general intelligence. The global release has intensified the AI race, raising questions about future leaders in the AI field. [para. 1]

Already in May, the U.S. Senate emphasized the strategic importance of AI, equating it with core infrastructure like electricity and the internet. Sam Altman advocated for massive investments in AI computing power, chips, data centers, and energy, while warning against overly restrictive approval processes and instead recommending agile regulatory “sandboxes.” U.S. political and business leaders underscored the necessity of outperforming China in this sector for national competitiveness. [para. 2]

Amid these developments, China faces critical gaps in AI infrastructure, regulatory policy, and innovation and needs a proactive, forward-thinking strategy in response. [para. 3]

In terms of infrastructure, the U.S. leads in computing power and chips, thanks to its technology giants and capital advantages. OpenAI is constructing the world’s largest AI training center in Texas, with CoreWeave operating over 250,000 GPUs. The U.S. dominates advanced chip design and production through companies like Nvidia and AMD, and in 2024, accounted for 32% of global computing power (291 exaflops). China has made progress with 246 exaflops as of June 2024—projected to reach 300 exaflops by 2025—driven by its “Eastern Data, Western Computing” initiative. However, China still faces performance limitations due to U.S. export controls on high-end chips, with domestic alternatives only partially closing the gap so far. [para. 4][para. 5]

Regulatory approaches differ starkly. The U.S. uses “light-touch” regulation, favoring innovation through voluntary standards and regulatory sandboxes, opposing the more restrictive European model. By contrast, China requires preemptive controls: generative AI services must register and undergo content security reviews. By the end of 2024, 302 such services had complied. While the American approach enables rapid technological iteration, China’s system is more robust in terms of security and social stability. Experts suggest that future Chinese policy could allow more flexibility, utilizing tiered regulation and sandboxes for lower-risk applications without compromising security. [para. 6][para. 7]

In innovation, the U.S. maintains a strong lead, producing 40 major large language models in 2024 compared to China’s 15, and attracting $109.1 billion in AI investment—almost 12 times China’s. China’s advancements, such as Baidu’s ERNIE 4.0 and DeepSeek R1, are quickly closing technical gaps. Its AI industry was worth $80.3 billion in 2023, with 4,000 AI companies and high societal acceptance. Yet, China still faces hurdles in translating research to applications, building an influential open-source ecosystem, and cultivating top talent. [para. 8][para. 9]

The article recommends China further develop its AI infrastructure, pursue hardware independence, optimize regulatory systems for both innovation and security, and foster a stronger innovation ecosystem. It advocates for talent development, increased basic research investment, support for startups, more open international collaboration, and the promotion of Chinese AI technologies abroad, aiming for global leadership by 2030. [para. 10-31]

The global launch of GPT-5 marks not just technological progress but signals an accelerated international race in AI competitiveness, with both the U.S. and China intensifying their efforts to lead in this transformative field. [para. 32]