High Capacity

Could China break America's dominance in AI chips sooner than expected? What happens when China can produce enough AI chips to meet its own needs—and start exporting them around the world?

In this episode, I speak with Ryan Fedasiuk and Satvik Pendyala of the American Enterprise Institute (AEI), authors of the new report "Voltcraft: Industrial Competition in the Age of AI." We talk about China's push for AI chip self-sufficiency, the global competition over AI infrastructure, and the risks and opportunities of Chinese open-source AI models.

We discuss:

- Could China meet most of its domestic AI chip demand by 2028?

- How is China overcoming bottlenecks in advanced chipmaking, memory, and packaging?

- What happens when China starts exporting AI chips and competing with the US AI tech stack globally?

- Will greater compute capacity help Chinese AI labs catch up with the US frontier?

- Will Beijing continue releasing powerful open-source AI models as security risks grow?

- What are the risks and benefits of American companies building on Chinese open-source AI models?

Links:

- Voltcraft: Industrial Competition in the Age of AI (Ryan Fedasiuk and Satvik Pendyala): https://www.aei.org/research-products/working-paper/voltcraft-industrial-competition-in-the-age-of-ai-aei/

- How to Win Friends and Export AI (Ryan Fedasiuk and Satvik Pendyala): https://pacforum.org/publications/the-pilot-73-how-to-win-friends-and-export-ai/

- The Lithography Loophole: How China Is Printing Its Way to Chip Self-Sufficiency (Ryan Fedasiuk and Julia Torres): https://ctse.aei.org/the-lithography-loophole-how-china-is-printing-its-way-to-chip-self-sufficiency/

- Code Red: Is the Future of American AI Being Built in Beijing? (Ryan Fedasiuk): https://www.aei.org/foreign-and-defense-policy/code-red-is-the-future-of-american-ai-being-built-in-beijing/

Follow:- Ryan Fedasiuk on X: https://x.com/RyanFedasiuk

- Satvik Pendyala on X: https://x.com/Satvik_Pen

- Ryan's newsletter, Choosing Victory: https://www.choosingvictory.com/

For transcripts and more information, check out the High Capacity newsletter: https://www.highcapacity.org/

Follow host Kyle Chan on X: https://x.com/kyleichan

How fast is China moving in space and quantum? Where else is China competing with the US at the technological frontier?

In this episode of the High Capacity podcast, I talk with Michael Kuiken, vice chair of the US-China Economic and Security Review Commission, and Commissioner Leland Miller about US-China competition in space, quantum technology, data, and critical supply chains. We explore China’s push into reusable rockets and satellite constellations, why quantum competition extends far beyond computing, and how Beijing is turning data into an economic and strategic asset. We also discuss hidden supply chain vulnerabilities and where the US government may need to step in.

We discuss:

• How quickly is China advancing in reusable rockets, launch infrastructure, and alternatives to Starlink?

• What are the differences between quantum computing, sensing, and communications—and where does China stand?

• What could quantum breakthroughs mean for encryption, medical imaging, and military capabilities?

• Why is China treating data as an asset, and how is AI making everyday information more strategically valuable?

• Where are the hidden Chinese chokepoints in pharmaceuticals, semiconductors, and other critical supply chains?

• How should the US rethink industrial policy and national security in a competition with no finish line?

Links:

US-China Commission’s 2025 Annual Report to Congress:
https://www.uscc.gov/annual-report/2025-annual-report-congress

Space hearing: “The Rocket’s Red Glare: China’s Ambitions to Dominate Space”
https://www.uscc.gov/hearings/rockets-red-glare-chinas-ambitions-dominate-space

Report: “Vying for Quantum Supremacy: U.S.-China Competition in Quantum Technologies”
https://www.uscc.gov/research/vying-quantum-supremacy-us-china-competition-quantum-technologies

Data hearing: “Taking a Bigger Byte: China’s Expanding Strategy for Data Dominance”
https://www.uscc.gov/hearings/taking-bigger-byte-chinas-expanding-strategy-data-dominance

Report: “The People’s Republic of Data: How China Is Turning Data into Capital”
https://www.uscc.gov/research/peoples-republic-data-how-china-turning-data-capital

Supply chains hearing: “Dominance by Design: China Shock 2.0 and the Supply Chain Chokepoints Eroding U.S. Security”
https://www.uscc.gov/hearings/dominance-design-china-shock-20-and-supply-chain-chokepoints-eroding-us-security

For episode transcripts and more, check out the High Capacity newsletter:
https://www.highcapacity.org/

Kyle Chan on Twitter / X:
https://x.com/kyleichan

China’s robots can dance and run marathons—but can they do useful work? And can China make the core components like actuators, reducers, and chips?

In this episode of the High Capacity podcast, I talk with Sunny Cheung, a fellow in China Studies at the Jamestown Foundation, about China’s push into humanoid robots and physical AI. We explore how China is turning its EV supply chains into a robotics ecosystem, how state-owned enterprises create demand for robots, and where China still depends on foreign technology. We also discuss what the US and its allies can do to compete.

We discuss:

• How much progress has China made beyond dancing robots and impressive demonstrations?

• Why are Chinese EV companies moving into humanoid robotics?

• How do state-owned enterprises help robotics companies scale production and gather training data?

• Which components can China produce domestically—and where does it still rely on Japan, Germany, and the US?

• Can world models and simulation provide enough data to train useful robots?

• Could general-purpose AI models like Fable or Astra end up powering the next generation of robotics?

• How can the US and its allies build competitive robotics supply chains?

Links:

Sunny Cheung at the Jamestown Foundation: https://jamestown.org/analyst/sunny-cheung/

DSET report: “The Age of Robotics: China-West Competition and Taiwan’s Indispensable Role in the Non-Red Supply Chain”

https://dset.tw/en/research/000500-1/

Wilson Center: “The Deployment Gap: Why America Risks Losing the Robotics Race”

https://acrosskarman.wilsoncenter.org/article/deployment-gap-why-america-risks-losing-robotics-race

Jamestown Foundation: Embodied Intelligence: The PRC’s Whole-of-Nation Push into Robotics

https://jamestown.org/embodied-intelligence-the-prcs-whole-of-nation-push-into-robotics/

Sunny Cheung on Twitter / X:

https://x.com/sunnycheungky

Sunny Cheung on LinkedIn:

https://www.linkedin.com/in/sunnycheungcky/

For episode transcripts and more, check out the High Capacity newsletter:

https://www.highcapacity.org/

Kyle Chan on Twitter / X:

https://x.com/kyleichan

Can the US and China agree to slow down AI development—or even agree on what counts as an AI risk?

In this episode of the High Capacity podcast, I talk with Kendra Schaefer, partner and head of tech policy research at Trivium China, about China’s approach to AI safety. We discuss AI service registration, the regulatory gaps around open-weight releases and AI agents, and why Chinese policymakers may see some risks differently from their US counterparts. We also explore where US-China cooperation on AI safety might begin.

Topics covered:

• Why China does not necessarily see regulation as a slowdown

• Anthropic’s calls to slow frontier AI development

• China’s AI service registration and safety testing process

• The challenge of regulating open-weight model releases

• AI agents, incident reporting, liability, and traceability

• How China assesses technical, social, and geopolitical AI risks

• What the US and China could discuss in an AI safety dialogue

  
  

Follow Kendra Schaefer and explore Trivium Tech. You can also sign up for Trivium’s free daily brief.

For episode transcripts and more, check out the High Capacity newsletter.

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.

How do users in China get access to Claude and ChatGPT through the gray market? What’s really driving China’s apparent “AI optimism”? How is China trying to deal with deepfakes and AI-generated content?

In this episode, I speak with Zilan Qian, a researcher at the Oxford China Policy Lab about the hidden side of China’s AI boom, including:

• How Chinese users use “transfer stations” to access American AI models like Claude and ChatGPT
• Why Chinese users still want to use Claude and ChatGPT even though there are strong Chinese mode
• Why China’s apparent AI optimism is really driven by anxiety about falling behind
• China’s push to label AI-generated content—and the problems with watermarks, detection, and false positives

Links:

• Zilan’s Oxford page
• Zilan on Substack and Twitter / X
• How to Buy Cheap Claude Tokens in China
• China’s AI optimism isn’t what it seems
• Labelling AI-Generated Content in China

How did China build a world-leading EV industry? China didn't just pick winners. Local governments and private entrepreneurs played a critical role alongside a broader national push into batteries and electric vehicle technology.

In this episode, I talk with Fengming Lu, an assistant professor at Australian National University, about China's decades-long effort to build a world-class auto industry, its pivot to EVs, and what lessons other countries might learn.

We discuss:

• How Chinese local governments act like VC investors

• What China learned from foreign automakers like GM, Volkswagen

• The rise of upstarts like Geely, Chery, and BYD

• What caused a wave of Chinese EV startups like NIO, Xpeng, Li Auto

• The "Hefei model"

Links:

• The Rise of China’s Electric Vehicle Industry: Strategic Alliances Between Local Governments and Private Capital

• Fengming's personal website

• Fengming on Twitter / X

For transcripts and more information, check out the High Capacity newsletter.

Follow host Kyle Chan on Twitter / X

Why is China’s biotech industry advancing so quickly? I talk with Abigail Coplin of Vassar College to unpack China’s biotech strategy, BGI, genomics, AI-driven drug discovery, gene therapies, biotech regulation, and what the U.S.-China biotech race means for innovation, national security, and the future of medicine.

• Why has China emerged so quickly as a global biotech powerhouse?
• What gives Chinese biotech companies an edge over their Western competitors?
• How did BGI become one of the world’s most influential genomics companies?
• Why are China’s gene and cell therapies advancing so rapidly?
• What should U.S. policymakers know about China's biotech industry?

Links:

• Abigail’s academic profile
• Abigail’s policy paper for the Penn Project on the Future of U.S.-China Relations: “Getting Biotechnology Right: Managing Risk and Reward Between the U.S. and China in the Life Sciences”
• Yu Zhou and Abigail Coplin. 2022. “Innovation in a Science-Based Sector: The Institutional Evolution behind China’s Emerging Biopharmaceutical Innovation Boom.” The China Review.

For transcripts and more information, check out the High Capacity newsletter.

Follow host Kyle Chan on Twitter / X.

What happened with Anthropic's Mythos and Fable models? Why did Anthropic's approach to AI safety trigger such strong backlash? What does this mean for the future of AI regulation? What role does open-source AI play in this new era of AI control? How will this impact Chinese AI labs and open-source AI models?

In this episode, I talk with Nathan Lambert, a leading expert on open-source AI. He previously led post-training at Ai2, founded The ATOM Project, and writes the popular Interconnects AI newsletter.

Topics covered:

- Anthropic, Mythos, Fable, and the Claude controversy

- Are Anthropic’s AI safety claims sincere?

- Silent degradation, trust, and researcher backlash

- Open science, open-source AI, and safety

- How will Anthropic's new safety features impact Chinese AI labs?

- The “AGI era” of AI governance

- Is open-source AI safer or riskier?

- Why US developers use Chinese open-source models

- What Nathan learned from visiting China’s AI labs

- Are Chinese AI labs AGI-pilled?Follow Nathan Lambert:

• Interconnects newsletter
• The ATOM Project
• X/Twitter: @natolambert

Follow Kyle Chan:

• High Capacity newsletter
• X/Twitter: @kyleichan

#AI #ArtificialIntelligence #Anthropic #mythos #fable #Claude #OpenSourceAI #ChinaAI #AIGovernance #AISafety

In this episode of the High Capacity podcast, I talk with Matt Sheehan, Senior Fellow at the Carnegie Endowment, about the next phase of the US-China AI race: AI safety, open-source models, AI agents, job displacement, and what the US and China might discuss with each other.

As the U.S. and China prepare for formal talks on AI, both sides are wrestling with a fast-changing technology landscape. The U.S. is increasingly worried about frontier model risks, cyber threats, non-state actors, and pre-release testing. China, meanwhile, is becoming more concerned about AI’s impact on jobs, social stability, political control, and the rise of autonomous AI agents.

We discuss what China really fears about AI, why Beijing’s AI governance strategy is shifting from control to deployment to broader regulation, how open-source AI might complicate safety talks, and what realistic US-China talks on AI might look like.

Topics covered:

U.S.-China AI talks, AI safety, Chinese AI policy, AI agents, OpenClaw, open-source AI, frontier models, cyber risk, AI job displacement, China’s AI regulations, autonomous weapons, AI hotlines, and the future of AI governance.

Links:

- Matt Sheehan’s Substack

- Matt Sheehan’s Carnegie page

- “China is getting worried about AI & jobs”

- “China Is Worried About AI Companions. Here’s What It’s Doing About Them.”

- Matt Sheehan on Twitter: @mattsheehan88

For transcripts and more, check out the ⁠High Capacity newsletter⁠

More about the host, Kyle Chan, fellow at Brookings