Chinese Hyperscalers' AI Ambitions Face GPU Shortage Despite Export Restrictions

Chinese hyperscalers Huawei, Baidu, Alibaba, ByteDance, Tencent, NAVER, and SK Telecom Enterprise have commercialized AI despite export restrictions. However, modern GPUs remain limited, with NVIDIA H800 and H20 GPUs difficult to find in Chinese cloud services. Chinese hyperscalers have advanced in adopting best practices and publishing AI research, but training runs often use Western GPUs. Chinese Arm-based CPUs are in production at scale and offer an economically attractive solution for serving small AI models.

Title: Navigating China's AI Chip Shortage: Opportunities for Chinese Hyperscalers

As China pushes forward with its AI ambitions, it faces significant challenges, particularly in the realm of semiconductor technology. Despite the country's rapid progress in AI research and application, the shortage of modern GPUs, like NVIDIA's H800 and H20, remains a critical bottleneck. This article explores the current landscape, the role of Chinese hyperscalers, and the potential opportunities for economic growth.

# The AI Chip Shortage

China's AI stack is composed of three layers: chips, machine learning frameworks, and applications. The bottom layer, which includes AI chips, has seen significant investment. However, the performance of Chinese-made chips still lags behind international standards, particularly those set by NVIDIA. The U.S. export controls on advanced semiconductors have exacerbated this issue, making it difficult for Chinese companies to access high-performance GPUs [1].

# Chinese Hyperscalers' Response

Chinese hyperscalers, including Huawei, Baidu, Alibaba, ByteDance, Tencent, NAVER, and SK Telecom Enterprise, have found innovative ways to commercialize AI despite these restrictions. They have adopted best practices and published extensive AI research, demonstrating their commitment to advancing the field. However, training runs for AI models often rely on Western GPUs due to the lack of domestic alternatives [1].

# The Rise of Chinese Arm-Based CPUs

One notable development is the production of Chinese Arm-based CPUs at scale. These CPUs offer an economically attractive solution for serving small AI models. While they may not match the performance of modern GPUs, they provide a viable alternative for many applications, reducing the dependency on foreign technology [1].

# Government Support and Future Prospects

The Chinese government has been proactive in supporting the development of domestic AI technology. The "Big Fund" initiative, which has invested billions in chip development, is a testament to this commitment. While the fund has seen mixed results, it has helped establish key players like SMIC and YMTC [1].

# Opportunities and Challenges

The shortage of modern GPUs presents both challenges and opportunities. On one hand, it forces Chinese companies to innovate and find alternative solutions. On the other hand, it creates a significant barrier to the widespread adoption of advanced AI technologies. As Chinese hyperscalers continue to develop and deploy AI solutions, they will need to balance the need for high performance with the constraints imposed by export restrictions.

# Conclusion

China's AI stack is a complex ecosystem with distinct layers, each facing unique challenges and opportunities. While the shortage of modern GPUs is a significant hurdle, Chinese hyperscalers have demonstrated resilience and innovation. The future of China's AI development will depend on its ability to overcome these challenges and integrate domestic solutions into its AI stack. As the global competition for AI supremacy intensifies, understanding China's progress and strategies will be crucial for investors and financial professionals.

References

[1] https://merics.org/en/report/chinas-drive-toward-self-reliance-artificial-intelligence-chips-large-language-models