US-China AI race: Rivals compete for influence while seeking common ground on risks
Washington and Beijing are competing across AI models, chips and supply chains, even as they explore ways to manage the technology’s growing risks. Southeast Asia is increasingly becoming a focus of their efforts to build international AI partnerships.
U.S. and China are engaged in a fierce rivalry in the artificial intelligence (AI) sector, competing for dominance in AI models, chips, and supply chains. However, both nations are also exploring ways to manage the potential risks associated with this rapidly evolving technology, particularly in Southeast Asia. As the United States prepares to meet with China's president, Xi Jinping, in Washington, the two nations are reportedly considering establishing a dialogue to address AI risks.
While Washington has been restricting China's access to advanced chips from U.S. companies like Nvidia, Chinese firms have been developing open-source models and optimizing hardware efficiency. The race for advanced AI models and chips continues, with the U.S. still leading in this area. However, China is rapidly closing the gap.
Concerns about the potential misuse of AI technology have grown, with both the U.S. and China recognizing the need for international cooperation to prevent such misuse. The U.S. has launched Pax Silica, an initiative aimed at building secure technology supply chains among partner countries, while China has established the World Artificial Intelligence Cooperation Organization (WAICO) to promote AI development and governance, particularly in developing countries.
Southeast Asia is emerging as a key focus for both efforts, with the U.S. supporting AI SPARK and China seeking to build a broader digital ecosystem and promote affordable open-source AI models. While both initiatives are still in their early stages, they highlight the global interest in harnessing AI's potential while mitigating its risks.
Written by urgent.news from Channel News Asia's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
