[Decoupling of US-China AI Technology? Playground Founder Warns of Open-Source Ecosystem Bifurcation Risk] According to monitoring by Beating, Playground AI founder Suhail Doshi pointed out on X that China's push for self-reliance in computing power could lead to a bifurcation risk in the global AI open-source ecosystem. Doshi warned that as China gradually reduces its dependence on Western hardware and builds its own computing power stack, China's vast and active open-source contributions will shift toward a technical ecosystem that the US either cannot or will not use. Against the backdrop of increasingly closed research and infrastructure from major US AI companies, the fragmentation of the global open-source ecosystem could backfire on the US's own AI innovation capabilities. The tendency toward a bifurcated technology stack has sparked widespread industry discussion. Commentators, including GeekPark, noted that the push for computing power self-reliance is leading to inward-facing parallel technological decoupling. Chinese R&D teams are not only facing more physical barriers to integrating into the global research loop but also struggling to directly use the latest US model products. Industry engineers have 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 is forced to rebuild open-source toolchains from scratch due to export controls, US developers may face a dilemma in the future: either adopt open-source systems led and optimized by China or independently reinvent the entire technological wheel. Although Silicon Valley open-source movement advocate Guillaume Verdon believes that the US computing power stack may soon surpass the traditional paradigm centered on floating-point operations, in the short term, the software ecosystem fragmentation driven by hardware decoupling has already become an unavoidable systemic variable in the US-China AI competition. [Original Link]