China’s push for technological self-sufficiency in artificial intelligence (AI) is gaining momentum, with leading AI experts calling for homegrown alternatives to US-based platforms such as Nvidia’s CUDA. Computer scientist Li Guojie, a senior AI researcher at the Chinese Academy of Sciences, recently highlighted the need for China to break away from Nvidia’s AI ecosystem to achieve true technological independence.
Li’s remarks come in the wake of DeepSeek’s advancements in AI model efficiency and performance. The Chinese AI company has made headlines for developing cost-efficient, high-performance models that have given China a competitive edge in the global AI race. However, despite DeepSeek’s success, Li emphasized that its models still rely to some extent on Nvidia’s CUDA ecosystem, an area where China remains dependent on American technology.
“DeepSeek has made an impact on the CUDA ecosystem, but it has not completely bypassed CUDA, as barriers remain,” Li was quoted as saying in a report by the South China Morning Post. “In the long run, we need to establish a set of controllable AI software tool systems that surpass CUDA.”
CUDA (Compute Unified Device Architecture) is Nvidia’s proprietary parallel computing platform and application programming interface (API), widely used in AI research and machine learning. It plays a crucial role in AI model training and deployment, making Nvidia a dominant force in the industry. Given ongoing US-China tech tensions, there is increasing urgency within China to reduce reliance on American chipmakers and software platforms.
Chinese companies and research institutions have been accelerating efforts to develop domestic alternatives to Nvidia’s AI ecosystem. Companies such as Huawei and Biren Technology have been working on AI chips to rival Nvidia’s GPUs, while researchers explore open-source AI frameworks as substitutes for CUDA.
The call for an independent AI software ecosystem aligns with China’s broader strategy to achieve technological self-reliance. With US export restrictions limiting China’s access to cutting-edge AI hardware and software, the development of indigenous solutions has become a national priority.
As China continues its push for AI leadership, the ability to establish a robust, self-sufficient AI infrastructure will be a decisive factor in determining its long-term success in the field.
