Is the US-China AI technology decoupling? Playground founder warns of the risks of dual-track split in the open-source ecosystem

According to Beating monitoring, Playground AI founder Suhail Doshi pointed out on X that China’s push toward independent computing power will create a dual-track split risk for the global AI open-source ecosystem. Doshi warned that as China gradually moves away from reliance on Western hardware and builds its own autonomous computing stack, China’s large and active open-source contributions will shift toward a technical ecosystem that the United States is either unwilling or unable to use. Against the backdrop of mainstream U.S. AI giants increasingly closing their research and infrastructure, the division of the global open-source ecosystem will rebound against the United States’ own AI innovation capabilities.

The dual-track split tendency of the technology stack has sparked widespread industry discussion. In their comments, outlets such as GeekPark pointed out that computing power autonomy is driving a decoupling of inward, parallel technologies. They noted that Chinese R&D teams not only face more physical barriers when trying to integrate into the global research cycle, but also find it difficult to directly use the latest American model products. Industry engineers also mentioned that the promotion of open-source software stacks—such as Huawei’s CANN heterogeneous computing architecture—is enabling more chip manufacturers to achieve unified interfaces, thereby accelerating the formation of a parallel hardware ecosystem outside of NVIDIA’s CUDA.

As China, due to export controls, is forced to rebuild its open-source toolchain from scratch, U.S. developers may face a dilemma in the future: either be forced to adopt open-source systems led and optimized by China, or have to independently recreate all the technical “wheels.” Although Guillaume Verdon, an advocate for the open-source movement in Silicon Valley, believes the U.S. computing stack may soon surpass the traditional paradigm centered on floating-point operations, the short-term software ecosystem divergence driven by hardware fragmentation has become a systemic variable that cannot be ignored in the AI competition between China and the United States.