China's Ministry of Industry and Information Technology and the State Administration for Market Regulation jointly issued an action plan earlier this year to stabilize growth in the electronic information manufacturing sector between 2025 and 2026.

For the first time, this plan identifies compatibility testing between AI chips and large models as a core task. It also emphasizes the importance of promoting industry-education integration and enhancing talent development.

Recent years have seen a profound and continuous transformation of artificial intelligence, with young researchers playing a pivotal role in driving this progress.

During his opening address at a plenary session of the 14th committee of the All-China Youth Federation in July, Li Shulei, head of the publicity department of the Communist Party of China (CPC) Central Committee, emphasized that young people should leverage their creative thinking and broad perspectives to become pioneers and contributors in the new era.

This statement highlights the CPC Central Committee's emphasis on cultivating young talent in cutting-edge fields such as AI.

As AI technology experiences explosive growth, efforts to train young professionals in AI chip research have intensified to ensure that hardware innovation keeps pace with software advances.

Back in 2020, we launched China's first dedicated course on AI hardware and chips. This course systematically covers the fundamental hardware and software technologies that underpin AI chips.

Since then, over 100 universities — including top institutions like the University of Chinese Academy of Sciences, Peking University, and Beihang University — have introduced similar courses on intelligent chips.

As a result, China is now capable of nurturing hundreds of thousands of professionals each year who possess comprehensive expertise in AI hardware technologies.

China's engagement with the global academic community in AI chip research also remains strong. According to preliminary statistics, research papers from Chinese teams have been cited by more than 1,000 organizations across 80 countries, including industry leaders like Nvidia.

This not only reflects the international recognition of China's contributions but also underscores the significant impact young Chinese researchers are making on the global academic landscape.

In recent years, there has been a growing trend of young talent devoting themselves to AI chip research. For instance, the research team behind Loongson — China's first independently developed general-purpose CPU — has seen a surge in postgraduate applications from top-tier universities. When asked, many young applicants offer a simple yet powerful reason: they believe this work holds great significance for the country.

Twenty years ago, the idea of homegrown chips was widely regarded as an unattainable goal for China. However, researchers persevered, driven by a commitment to national development. Today, more and more young people are following in their footsteps, motivated by the same sense of purpose.

In my opinion, young people should choose careers that not only align with national interests but also contribute to the greater good of humanity. I believe such careers can unlock one's full potential — and AI chip research is one of them.

We are living in an era of rapid AI development. In chip manufacturing, AI is already being used to design CPU chips autonomously, greatly empowering the industry. It will also continue to play an increasingly integral role in our daily lives.

In the future, regardless of their career paths, everyone will need to adapt to shifts in production methods. As AI becomes an essential tool across all sectors, every young person should acquire at least some knowledge of AI technology.

Written by Chen Yunji, vice-chairman of the All-China Youth Federation, deputy director of the Institute of Computing Technology at the Chinese Academy of Sciences, and director of the State Key Lab of Processors. He has long been engaged in interdisciplinary research on processor chips and AI, and developed the world's first deep learning processor chip, Cambrian-1.