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China's data centers are advised to continue using Nvidia chips due to the high costs and complexities of transitioning to domestic alternatives. The country is striving to develop its own GPU market to reduce reliance on Nvidia, especially after US sanctions limited access to advanced chips. Despite progress in local GPU technology, compatibility issues and engineering challenges hinder the shift from Nvidia's widely used hardware.
The rapid growth of China's AI computing power, which increased by 27% year-on-year, highlights the ongoing demand for effective GPU solutions. However, the transition to domestic chips is complicated by significant differences in hardware and software, making Nvidia's offerings more appealing despite export restrictions. The situation underscores the delicate balance between national technological ambitions and the practical realities of existing infrastructure.
• China's AI computing power grew by 27% despite US sanctions.
• Nvidia chips remain preferred due to high costs of domestic alternatives.
Graphics Processing Units are essential for training AI models and performing complex computations.
The capacity of systems to perform AI-related tasks, crucial for model training and inference.
Facilities that house computer systems and associated components, vital for AI processing and storage.
Nvidia is a leading company in GPU technology, crucial for AI model training and development.
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