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Training machine learning algorithms on large data sets is very computationally intensive.

Running simulations to generate synthetic data is, for many applications, even more computationally intensive. For the large and growing set of AI applications where massive data sets are needed or where synthetic data is viable, AI performance is often limited by computing power. Chinese companies and government laboratories are strong in high performance computing and specifically on efficient high performance AI computing.

At the moment, China does not have a major manufacturer or designer of advanced GPUs. These chips can offer dramatically superior performance over GPUs for AI applications even when manufactured using older processes and equipment. Google claimed in that its first generation TPU was 15—30 times faster and 30—80 times more power efficient for AI workloads than contemporary GPUs. Chinese firms Baidu in partnership with Intel , 75 Alibaba via a new subsidiary, Pingtouge , 76 and Huawei via its HiSilicon subsidiary have all established semiconductor design divisions focused on developing AI accelerator chips.

AI chips offer Chinese manufacturers a uniquely attractive opening for their older process technology.

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As mentioned above, AI chips can offer potentially superior performance and cost than state-of-the-art GPUs even while using less advanced manufacturing processes. Though flagship mobile phones likely will always demand the most advanced generation of semiconductor manufacturing processes, many applications can be addressed with older technology nodes.

With low-cost AI chips, this could be a uniquely attractive, diverse, and rapidly growing set of applications. One Chinese industry observer has openly promoted this exact strategy. That report strongly emphasizes the strategic importance of AI chips:. Whether it is the realization of algorithms, the acquisition and a massive database, or the computing capability, the secret behind the rapid development of the AI industry lies in the one and only physical basis, that is, the chips. At the same time, China hopes to use success in AI chips to build an enduring competitive advantage in the overall AI industry, underpinned by superior computing capacity, larger datasets, and a more favorable regulatory environment.

In both AI and semiconductors, China has dramatically shrunk the gap between its domestic firms and leading international ones. Absent some kind of major change in U. The first fund ultimately invested Chinese design firms benefit from access to world-leading Taiwanese semiconductor foundry companies that manufacture semiconductors but do not design them. The primary barriers to additional Chinese semiconductor manufacturing progress are access to the most advanced semiconductor manufacturing equipment and access to skilled workers with the knowledge of and training in how to effectively implement the most advanced manufacturing processes.

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Semiconductor manufacturing equipment sales in China represented Chinese AI startups increased their share of global AI equity investment to 48 percent in , while U. Historically, governments would dominate nuclear, rocket, and comparable technologies and not trust private companies.

In my interactions with Chinese government officials, they demonstrated remarkably keen understanding of the issues surrounding AI and international security. This includes knowledge of U. AI policy discussions. I believe it is vital that the U. I hope this report has helped contribute to that objective. If the United States wants to lead the world in AI, it will require funding, focus, and a willingness among U. They should prioritize accordingly. I would like to thank the following institutions for their invitations to participate in conferences and meetings in China and Hong Kong on Artificial Intelligence:.

Finally, I would like to thank the dozens of individuals with whom I met on trips to China. Their willingness to engage was critical to this report. Where they engaged with an expectation of anonymity or non-public disclosure, I have made sure to respect that here. CNAS does not take institutional positions. Download PDF.

Understanding China's AI Strategy

Gregory C. Allen focuses on the intersection o By Elsa B. Introduction In the second half of , I traveled to China on four separate trips to attend major diplomatic, military, and private-sector conferences focusing on Artificial Intelligence AI. Chinese Views on the Importance of AI 1. Recently, Chinese officials and government reports have begun to express concern in multiple diplomatic forums about arms race dynamics associated with AI and the need for international cooperation on new norms and potentially arms control.

Chinese Views on the Importance of AI

China already exports armed autonomous platforms and surveillance AI. Weaknesses in Top Talent The Tsinghua University China AI report did a remarkable study of the global AI talent distribution, concluding that by the end of , the international AI talent pool comprised , individuals, with the United States having 28, such individuals and China in second place with 18, Why China's Tech Sector is Unlikely to Face Soviet-Style Stagnation Like the Soviet Union during the Cold War, China today is engaged in an extensive campaign to harvest technological and scientific information from the rest of the world, using both legal and illegal means.

China's leaders seek to preserve access to foreign technology in the short term but believe that they must promote domestic independence in the longterm. This has long been China's goal, but it has taken on new urgency. China's pursuit of reducing foreign dependence is bearing fruit, as show by increasing value capture share by Chinese suppliers in the global smartphone market supply chain and China's success in advanced semiconductor design. Other than military AI applications, the future focus of strategic national AI competition is likely to be the semiconductor industry, 68 because the cutting edge of AI technology increasingly depends on custom computer chips.

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