ChinaTalk

Nick Brown is a co-founder of the Center for Technology and Statecraft (CTS), a new think tank spun out of IFP, that looks at long-term technology challenges and opportunities facing the US. Nick was a physics major, spent a while as a software engineer in and around government, and had an arc as an aspiring concert violinist. But we’re here to talk about what is in pole position for my paper of the year: his master class on what would happen if the US cut off DUV exports to China: DUV Immersion Lithography: The Foundation of US AI Compute Advantage. Co-hosting is ChinaTalk’s Aqib Zakaria.We discuss:

The case for banning DUV exports to China: Why lithography is the hardest part of the semiconductor manufacturing stack for China to replicate/indigenize and the strongest point of leverage the US and its allies have over China’s future AI compute.

The cannonball-sized hole in US export controls: China imported roughly 90 immersion lithography systems a year in 2024–25, nearly two-thirds of ASML’s immersion exports. If imports continue at this rate, China could approach or even reach parity with the US in AI chipmaking within a decade.

What the MATCH Act would do: How Congress could close this gap by restricting DUV immersion exports and servicing, and whether the US can get its allies on board.

Will Beijing retaliate? Why a gradual, long-term restriction may be less likely to provoke another rare-earths crisis

Buying time for AGI: How cutting off DUV imports could preserve America’s AI compute advantage into the 2030s, giving the US more time to navigate the technological, geopolitical, and societal implications of increasingly powerful AI.

Timestamps:

00:00:00 Intro

00:07:11 EUV vs. DUV

00:21:55 What the MATCH Act does

00:41:24 Would Beijing retaliate?

00:58:59 Japan, the Netherlands, and the light-source option
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He was recently promoted to DIU’s acting director after spending the past year running the Drone Dominance Program. Co-hosting are Brian Clark, senior fellow at Hudson Institute and a retired submariner, and Justin McIntosh, a twenty-year retired Green Beret who served in the 1st and 5th Groups, who now works in defense tech and writes a Substack called Mind of Things.

We discuss:

Why the Department of War isn’t going fast enough to procure, scale, and field drones, and how the DIU’s Gauntlet competition is using real orders, competition, and falling prices to build a drone industry capable of producing at scale.

What American drone makers can learn from Ukraine’s battlefield laboratory and how the Pentagon is trying to replicate the conditions of electronic warfare in its evaluations.

Why the US drone industry is “wide but not deep,” how the first orders banning Chinese motors and battery packs are testing the limits of supply-chain decoupling, and why Drone Dominance alone can’t solve dependencies in battery chemistry and rare-earth refining.

Why the future of drone warfare depends on systems that can operate autonomously under electronic attack, and how Metz thinks mass-produced, increasingly autonomous drones will reshape military procurement, training, and force structure.

Timestamps:

00:00:00 Intro

00:01:27 How Drone Dominance works

00:08:36 Ukraine, jamming, and the Gauntlets

00:32:41 Component supply chain

00:47:37 Doctrine and forcing functions

01:03:11 Bombers, pilots, and autonomy
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Richard Bian is the head of product operations for Ant Ling, the foundational LLM at Ant. If you don’t know Ant, they most famously make Alipay, which makes your money and your world run when you’re in China and sometimes beyond. Richard is a former software engineer at Microsoft and Square, and he previously served as head of open source at Ant, where he scaled the open source initiative into a dedicated team. He’s lived and worked in Singapore, Canada, the US, and China, and he loves to build products.

Topics covered:

The Hugging Face hack as a sign of progress? Why Richard sees the incident involving OpenAI research agents as an inevitable discovery rather than simply a disaster, and why finding a solution now is a positive development.

AGI is coming, but nobody knows what it will look like. AGI is inevitable, and we’re still in the early stages of figuring out what these models can do. Rather than obsessing over leaderboards, we need better evaluations and a more open-minded approach to judging models.

Open source as a product strategy, not just a way to give things away. How open-weight models can harness global talent, accelerate development, and support a diverse ecosystem of products, and why the real business challenge is gross margins rather than capex.

Why the AI conversation needs more voices. Why we need to pay attention to diverse perspectives on where AI is going, and be more willing to explore rather than declare the endgame.

AI moves fast: since we recorded, Ant Ling has announced its latest LLM, Ling 3.1 Flash, which was open-sourced on October 14 with 560B parameters and up to a 1M-token context window.

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Saif Khan makes his ChinaTalk debut. He is perhaps my favorite example of posting-to-policy that I’ve seen over the course of my time following Washington. Saif wrote some truly excellent deep dives into AI and semiconductors during his time at CSET, then went into the NSC and Commerce in the early-to-mid 2020s, across both the Biden and Trump II administrations, to help manifest the export control regulatory regime we have today. He is now out of government and launching the Center for Technology and Statecraft, an IFP-affiliated think tank, which is already producing excellent, grounded, technical, forward-looking work that will certainly shape many an AI policy discussion in the years to come.

We discuss:

Why Saif started a new think tank, and the value of deep, forward-looking policy research in an AI world moving at breakneck speed;

CTS’s landmark DUV report, which projects that stopping tool exports today could leave China producing roughly 100x fewer AI chips than the US by the mid-2030s, making DUV controls the US’s most consequential lever over the AI balance;

How rigorous research actually translates into government policy, and why think tank experience is valuable before working in government;

Robotics as the next frontier of US-China AI competition, and the security vs. diffusion mindsets shaping AI policy;

How AI is changing policy research itself, the challenge of bringing AI into government, and what AI-driven economic and social change could mean for humans.

Plus, why everyone should read Lu Xun, why AI might socialize like insects, and AI-nannying.
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I join Matt and Jerusalem for an unhinged conversation (most entertaining of the year?) about China, AI, corruption, politics, and various other things.

Check out their show The Argument, it's good.
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