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Dylan Patel — Deep dive on the 3 big bottlenecks to scaling AI compute

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Dylan Patel — Deep dive on the 3 big bottlenecks to scaling AI compute

Dwarkesh Podcast

Mar 13
Dwarkesh Podcast

Dwarkesh Podcast

Mar 13
OverviewShownoteHighlightsTranscriptChaptersPins

Shownote

Dylan Patel, founder of SemiAnalysis, provides a deep dive into the 3 big bottlenecks to scaling AI compute: logic, memory, and power. And walks through the economics of labs, hyperscalers, foundries, and fab equipment manufacturers. Learned a ton about ...

Highlights

Dylan Patel of SemiAnalysis unpacks the fundamental physical and economic constraints shaping the future of AI compute scaling.
14:22
GPT-5.4 is cheaper to run, has fewer active parameters, and is higher quality than GPT-4
30:15
Anthropic saw AI compute demand first and acted before Google realized its own shortfall
34:34
ASML's EUV tools are the biggest bottleneck towards 2030, as there's no more capacity to shift from mobile and PC industries to AI
1:03:54
As advanced packages scale up, constraints like networking, memory, and cooling emerge—not just transistor density
1:11:03
US labs like OpenAI and Anthropic are scaling compute capacity rapidly, while China is not
1:40:16
Silicon Valley should consider paying deposits for future EUV tool purchase rights to arbitrage AI compute capacity
1:47:27
Half of new power capacity for AI by decade-end may be behind-the-meter, despite higher costs
2:12:21
Smaller models enable faster RL feedback loops and increase compute efficiency
2:16:23
Dylan Patel is noted for his conviction on AGI takeoff and successful trades in memory companies
2:20:53
Huawei, if having access to 3nm, could potentially have a better accelerator than NVIDIA
2:29:33
Replicating TSMC's capacity elsewhere would take so long it would cause a near-zero incremental ability to add compute

Chapters

Why an H100 is worth more today than 3 years ago
00:00
Nvidia secured TSMC allocation early; Google is getting squeezed
24:52
ASML will be the #1 constraint for AI compute scaling by 2030
34:34
Can't we just use TSMC's older fabs?
55:47
When will China outscale the West in semis?
1:05:37
The enormous incoming memory crunch
1:16:01
Scaling power in the US will not be a problem
1:42:34
Space GPUs aren't happening this decade
1:54:44
Why aren't more hedge funds making the AGI trade?
2:14:07
Will TSMC kick Apple out from N2?
2:18:30
Robots and Taiwan risk
2:24:16

Transcript

Dwarkesh Patel: All right. This is the episode of My Roommate Teaches Me Semiconductors. Dylan Patel: It's also the send-off for this current set. Dwarkesh Patel: Yeah. After you use it, I'm like, I can't use this again. I got to get out of here. Dylan ...