The Beijing government plans to provide subsidies to companies that buy domestic chips to “accelerate the delivery of managed smart computing resources.”
Particular attention is paid to GPU processors, the production and sales of which were negatively affected by export controls from the US side. In addition, China continues to advance initiatives in the field of artificial intelligence. Subsidies will be allocated to companies that are willing to buy graphics processors from domestic manufacturers. And don’t forget about the several trillions of dollars that have been allocated to the manufacturers themselves in recent years.
What kind of plans are there?
According to the Beijing Municipal Bureau of Economics and Information Technology, the country should achieve self-sufficiency in this field by 2027, with a leading level of productivity at par with domestic standards. The program is centered around chips and systems used in data centers for artificial intelligence development projects.
The US administration has introduced export control changes that affect access to advanced artificial intelligence processors, semiconductor manufacturing equipment and even laptops built on these chips to Chinese businesses. Exporting advanced GPUs such as the A100 and H100 from Nvidia to China is also difficult. The A800 and H800 chips, designed as alternatives for Chinese customers, were blocked from sale by updated US export restrictions last October. This has led to the emergence of new alternative solutions such as processors H20.
At the end of 2022, experts analyzed global GPU market and found that the number of manufacturers from China is growing rapidly. However, Chinese companies often make claims about the high performance and efficiency of their products even before they hit the market. Sometimes after sales launch it turns outthat they do not always meet the stated characteristics or user expectations. Similar situations also occur among Western manufacturers, but companies such as AMD and Nvidia have an established position in the market and produce products that are recognized as one of the most the best in branch.
Technology research and development continues to be active in China. More than half of the LLM programs are developed in Beijing, and selected projects will be tasked with teaching large language models. In addition, Chinese companies are working on other areas, including specialized artificial intelligence processors, silicon photonics and quantum computing components.
What else?
The government’s plan aims to boost research and development of technologies such as artificial intelligence processors, operating systems and databases. Without such technologies, it is impossible to train artificial intelligence systems. The program also explores the possibility of achieving breakthroughs in new areas, such as silicon photonics and quantum computing systems, where there are currently no dominant players in the market.
Notably, a public computing platform was launched in December to help higher education institutions, research institutions and small and medium-sized enterprises address computing resource constraints and support artificial intelligence projects. China is also looking to create and implement a national standard for large language models (LLM) as part of its AI regulation, using its resources to transform industries. LLM is the technology used in ChatGPT and other generative AI services.
There is also outside support
Nvidia’s Ampere A100 is the most powerful AI accelerator until the Hopper H100, not to mention the H200 and the upcoming Blackwell GB200. But, as it turned out, there is a more advanced version of the A100, it is improved compared to the regular model. The accelerator is freely sold in China, despite US sanctions. Perhaps Nvidia experimented with the accelerator, or it was modified specifically for China.
Last year, Reuters journalists managed to find information about the supply of small quantities of AI accelerators to the country. For example, the Harbin Institute of Technology purchased six Nvidia A100 chips to create and develop a “deep learning model,” and in December 2022, the China University of Electronic Science and Technology purchased one A100 for as yet unknown purposes. This is only what “lies on the surface”, but there are probably shadow supply channels through which larger quantities arrive in China. By the way, Tsinghua University managed to purchase over 80 A100 chips after the 2022 sanctions. In addition, Tsongqing University, Shandong Chengxiang Electronic Technology and others also purchased chips.
Overall, China has every opportunity to resolve its domestic crisis of shortages of modern electronic components. The country is likely to be able to do this in the near future due to a number of factors including domestic investment, domestic and foreign procurement, a large number of players and a large domestic market.
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