Is the U.S.–China AI competition really a winner-take-all race to AGI? Why has China embraced open-source AI? And are the biggest frontier models actually the greatest security threat?

In this episode, I speak with Alvin Wang Graylin, a Digital Fellow at the Stanford Digital Economy Lab, a Senior Fellow at the Asia Society Policy Institute’s Center for China Analysis, a professor of AI and technology policy at the University of Washington, and co-author of Our Next Reality.

We discuss:

• China’s AI strategy and its focus on spreading AI throughout the economy
• Why the “decisive strategic advantage” theory may misread the U.S.–China AI relationship
• The prisoner’s dilemma, the stag hunt, and the case for cooperation on AI safety
• China’s open-source AI ecosystem and the debate over open versus closed models
• Why small, specialized AI systems may pose greater security risks than frontier models
• How export controls may be accelerating Chinese AI innovation
• China’s push into robotics, manufacturing, and physical AI
• How China’s technology industry has changed over the past three decades

Read Alvin’s essays, “Misdiagnosing the U.S.–China AI Race” and “The Biggest AI Models Are Not the Biggest Threats.”

You can also follow Alvin on X and LinkedIn, or read his Substack, The Abundanist.

For transcripts and more information, visit the High Capacity newsletter.

Follow host Kyle Chan on X.