China has spent years pouring money and political capital into building a homegrown semiconductor industry. Yet when its AI companies need to train their most sophisticated models, many still turn to Nvidia, according to South China Morning Post.
The biggest obstacle may no longer be the chips themselves. It is everything developers have built around them.
Nvidia’s CUDA software has become deeply woven into the way AI labs operate. Models, training tools and internal workflows have been designed around the platform, meaning switching to Chinese hardware can resemble rebuilding part of the factory rather than simply swapping out a machine.
SCMP writes that Huawei’s Ascend processors are among the leading domestic alternatives, but moving an established operation onto them can require substantial engineering work. One researcher estimated that doing so could increase the time and expense of a project by at least 50%.
How painful that transition becomes depend
