Lennart Heim, a researcher and information scientist at RAND Corporation, joins Azeem Azhar to unpack a provocative claim: China is catching up with US AI capabilities, but it doesn't matter. Timestamps: (00:00) Episode trailer (01:19) Lennart’s core thesis (03:26) Why compute matters so much (07:31) The investment split between model R&D and model execution (11:18) How test-time compute impacts costs (16:14) The geopolitics of compute (21:32) Why does the U.S have more compute capacity than China? (25:01) The trade-off between economic needs and national-security needs (31:54) How technology change might shift the battlegrounds (35:33) Dealing with compute and power concentration (48:19) Concluding quick-fire question Lennart's links: Twitter/X: https://twitter.com/ohlennartPersonal blog: https://heim.xyz/Azeem's links:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azharTwitter/X: https://x.com/azeemThis was originally recorded for "Friday with Azeem Azhar", a new show that takes place every Friday at 9am PT and 12pm ET. You can tune in through Exponential View on Substack. Produced by supermix.io and EPIIPLUS1 Ltd Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Full Episode
We are really lucky to be joined by Lennart Hein. He said China is catching up with the US in AI capabilities and that it didn't matter. What's America's big advantage? Having eight times more of the resource, which is the most important. Let's start on why compute matters and what it drives.
I think it's fair to say compute is like the currency of AI. Every time it's being produced requires computing power. If you have less compute, you've got less AI workers and population size is pretty important for economic growth.
There is this question about a world where compute resources are highly concentrated. Typically in political systems, we don't like concentration of power.
Let's look at the status quo. I think like 60 to 70% of all supercomputers are in the US. I'm not an anti-trust lawyer, but I think this is at least something one should look into.
This also explains in a sense why the EU and why India and also the UAE are pushing for their own compute infrastructure. So this sense of this concentration risk is really being noticed increasingly over the last five years. How do you imagine it plays out?
I don't think the plan is like every country is going to like redevelop the whole tech stack and come up with their own solution. Again, maybe I'm a little bit too much kumbaya. It would be nice if we can just get together and just say like, here are the standards, here's how the democratic world is doing AI.
We are really lucky to be joined by Lennart Heim. He is a researcher and information scientist at RAND, the OG of think tanks. He's been an advisor of EPOC, which is an AI research group, which readers of Exponential View know that we rather like. I have been following his work for a long time, and he recently wrote an essay on the China Talk substack. arguing two things.
He said China is catching up with the US in AI capabilities, and that it didn't matter. So that is something to talk about. Let's get into that key claim. China may match individual US model capabilities this year, but that won't matter for America. What's America's big advantage?
So the argument which I'm putting forward in this essay is basically inspired what happened with DeepSeek. Everybody freaked out. Some people were just expecting there's like this really big lead and it's like really, really hard to build competitive AI. Don't get me wrong. Not everyone can do it. But I think like actually more actors than many people assume can build competitive models.
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