A ChinaTalk investigation has identified at least nine American data brokers selling roughly $500 million worth of reinforcement learning environments to Chinese AI laboratories.
These simulated worlds allow models to practice coding, financial analysis, and office tasks. Chinese buyers purchase the same products previously sold to Anthropic and OpenAI. This approach lets them skip costly in-house development and wasted training runs.
Because Chinese chips face acute memory bottlenecks, the savings from using existing data are particularly valuable for labs there.
There is also the issue of distillation. Chinese labs use powerful US models like GPT or Claude as teachers, using their outputs as training examples. Combined with purchased reinforcement learning environments, this creates a two-pronged advantage that lets Chinese labs close the gap with less compute of their own.
At least nine firms identified
The authors identified at least nine US data firms selling to Chinese customers. AfterQuery reportedly draws a significant share of its annual recurring revenue from Chinese customers. ChinaTalk points to Forbes reports of about $100 million in ARR but could not independently verify the sales.
Surge AI openly advertises on its website that its products are built by the same experts behind our frontier-lab work. The deals also run through offshore structures. ByteDance maintains procurement offices in Singapore and San Jose.
These business relationships came to light through a combination of anonymous sources and sloppy operational security among subcontractors, according to ChinaTalk. The US data firms outsource much of the actual reinforcement learning environment creation and data curation to low-paid workers in developing countries, especially India.
Those subcontractors then sometimes post client names on LinkedIn or in résumés, even though they are supposed to use only code names. Export controls barely apply because reinforcement learning environments remain largely unregulated.
Coding and biology raise dual-use concerns
Domains with dual-use potential pose particular risks. Coding environments improve software development but can also sharpen offensive cyber capabilities. Biology environments could improve gene synthesis capabilities and potentially enhance bioweapons-relevant applications.
The ChinaTalk authors argue that the Bureau of Industry and Security should subject these dual-use environments to existing export controls.
At the same time, the authors stress that these relationships are not apocalyptic. By piggybacking on US work, Chinese labs still trail their US peers by at least a few months as a structural matter. Sensitive environments in areas like biology, chemistry, cybersecurity, chip design, and investment banking are increasingly being built in-house at American frontier companies, the authors say.
