The US and China Are Collaborating More Closely on AI Than You Think

The US and China are, by many measures, archrivals in the field of artificial intelligence, with companies racing to outdo each other on algorithms, models, and specialized silicon. And yet, the world’s AI superpowers still collaborate to a surprising degree when it comes to cutting-edge research.

A WIRED analysis of more than 5,000 AI research papers presented last month at the industry’s premier conference, Neural Information Processing Systems (NeurIPS), reveals a significant amount of collaboration between US and Chinese labs.

The analysis found that 141 out of the 5,290 total papers (roughly 3 percent) involve collaboration between authors affiliated with US institutions and those affiliated with Chinese ones. US-China collaboration appears fairly constant, too, with 134 out of 4,497 total papers involving authors from institutions in both countries in 2024.

WIRED also looked at how algorithms and models developed in one country are shared and adapted across the Pacific. The transformer architecture, developed by a team of researchers at Google and now widely used across the industry, is featured in 292 papers with authors from Chinese institutions. Meta’s Llama family of models was a key element of the research presented in 106 of these papers. Meanwhile, the increasingly popular large language model Qwen from Chinese tech giant Alibaba appears in 63 papers that include authors from US organizations.

Jeffrey Ding, an assistant professor at George Washington University who tracks China’s AI landscape, says he is not surprised to see this level of teamwork. “Whether policymakers on both sides like it or not, the US and Chinese AI ecosystems are inextricably enmeshed—and both benefit from the arrangement,” Ding says.

The analysis no doubt simplifies the degree to which the US and China share ideas and talent. Many Chinese-born researchers study in the US, forging bonds with colleagues that last a lifetime.

“NeurIPS itself is an example of international collaboration and a testament to its importance in our field,” Katherine Gorman, a spokesperson for NeurIPS, said in a statement. “Collaborations between students and advisors often continue long after the student has left their university. You can see these kinds of signals that indicate cooperation across the field in many places, including professional networks and past collaborators.”

The latest issue of WIRED explores the many ways in which China is shaping the current century. But with US politicians and tech executives using fears over China’s rise as a justification for ditching regulations and fueling staggering investments, our analysis is a good reminder that the world’s two AI superpowers still have a lot to gain from working together.

A Note on Methodology

I used Codex, OpenAI’s code-writing model, to help analyze NeurIPS papers. After writing a script to download all the papers, I used the model to dip into each one and do some analysis. This involved having Codex write a script to search for US and Chinese institutions in the author field of each paper.

The experiment offered a fascinating glimpse into the potential for coding models to automate useful chores. There’s plenty of panic about AI replacing coding jobs, but this is something that I normally wouldn’t have had the time or budget to build. I started out writing scripts and having Codex modify them before just asking Codex to do the analysis itself. This involved the model importing Python libraries, testing different tools, and writing scripts before producing reports for me to vet. The process involved a fair bit of trial and error, and you have to be very careful, because AI models make surprisingly stupid mistakes even when they’re being quite smart. I had to make sure that each report included a way for me to go through the results, and I checked as many as possible manually.

This is an edition of Will Knight’s AI Lab newsletter. Read previous newsletters here.