China May Overtake The US's Early Lead In AI
The US's policy of containing China's AI is failing.
“China’s relentless drive and strategic investments in AI suggest it is only a matter of time before it catches up—if not surpasses—the United States’ early lead in AI.”
The Information Technology and Innovation Foundation (ITIF) think tank in Washington is hardly a shill for China, and their warning that China’s AI program can’t be “contained” is likely too little too late, regardless of elections.
The US continues to underestimate China’s ability to innovate, which is why my favorite line in the report is:
“And the narrative that China is merely a copier is false and outdated.”
The US’s entire AI containment policy for China is based on the outdated notion that China can’t innovate when confronted with chip bans, sanctions and technology blocks.
Rather than “shock and awe,” the bans and blocks aren’t just unsuccessful but also self-injurious. They galvanized China’s AI research and development while costing US companies billions in lost revenue, narrowing the US’s technological lead.
The only way for the US to succeed is through competition and a national AI strategy, which I will cover below.
👉TAKEAWAYS
🔹 China is the global leader in AI research publications and is neck and neck with the United States on generative AI. However, China’s research publications have less impact than U.S. ones, with fewer citations and less private-sector involvement.
🔹 Tsinghua University in Beijing is the breeding ground for China's leading AI start-ups, including four of the country’s “AI tigers.”
🔹 Chinese large language models are closing the performance gap with U.S. models, with some Chinese models outperforming their U.S. counterparts.
🔹 China has less private AI investment than the United States, but foreign investment in China's generative AI sector is growing, with Saudi Arabia’s Aramco leading the way.
🔹 State-directed capital funds and financial aid are proving effective at supporting high-potential firms in regions of China the private sector typically underinvests in.
🔹 China’s open-source LLM ecosystem is rapidly advancing, with models such as Alibaba’s Qwen 1.5 and Zhipu AI’s ChatGLM3 outperforming some U.S. counterparts and gaining recognition for their impressive capabilities.
🔹 U.S. policymakers should not prioritize containing China, but rather craft and fund a comprehensive national AI strategy that addresses the twin goals of increased AI development and increased AI adoption to stay ahead.
👊STRAIGHT TALK👊
The US will be unable to “contain” China’s AI progress, leaving outcompeting China as the only option.
I find it ironic that a think tank is now necessary to teach the US about competition.
The ITIF has a four-part solution to out-competing China, which I fully support:
Stimulate private investment in AI R&D.
Revitalize the federal funding process for AI.
Avoid policies that undermine U.S. AI leadership and bolster Chinese competitors. U.S. policymakers should evaluate the impact of policies that may unintentionally hurt U.S. competitiveness in AI. For instance, overly stringent export controls may undermine U.S. chip competitiveness and inadvertently bolster China’s chip industry.
Develop a national data strategy to dramatically expand the availability of data for training AI models.
I want to call attention to point three which explicitly states that the US’s chip bans are undermining the US chip industry. This is a big problem and the notion that China can be cut off from these chips is absurd.
Sadly, with elections coming in November, neither side is likely to give up on chip sanctions, which will cause further damage.
Meanwhile, this week Huawei will announce its next big AI chip which is widely believed to be superior in performance to the Nvidia chips available in China.
This means that Nvidia’s China sales, once 25% of revenue and now 10%, are likely to fall even further.
How much new R&D could Nvidia have bought with this revenue?
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