Ashwin

@databricks @ucberkeley

[Ashwin @ashchirum]

This leaves a few questions: Why isn’t ASML taking ~70% margin like $NVDA or $MU? These machine’s manufacturing is artisan-like and are not scalable commodities like DRAM or even GPUs, but as an SPOF monopoly why not take advantage of this unprecedented spend by hyperscalers?

[Ashwin @ashchirum]

If these estimates from McKinsey hold true, we will be spending approx $7T for ~216 GW of incremental compute by 2030. For us to keep pace with this unprecedented buildout, walking down the full supply chain picture gets pretty insane

[Ashwin @ashchirum]

The margin of error on these machines is quite thin, and as advanced packagers like TSMC are forced to upgrade to newer machines, I believe these fab machine players will experience a similar crunch memory players are seeing today, but with much much stronger pricing power.

[Ashwin @ashchirum]

thoughts + leaders hike

[Shishir Patil @shishirpatil_]

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