18 Comments
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David Wilkens's avatar

On Memory. I too agree that this is a cyclical phenomenon albeit super-cyclical. The current demand for HBM has no prior analog. It's as if a multi-trillion market was created out of nowhere because the hypercalers have converted their savings into CapEx. In and of itself this action should give us all some pause. Given the long lead times on building new capacity, the multiyear agreements signed by Micron that lock in pricing and estimates that there will be no relief till at least 2028. do you sense that the typical 4-year cycle is shorter than we should expect and this sell-off is a bit premature?

Habanero's avatar

Good analysis and worth a read and re-read. The HBM cycle I am questioning a bit given the reported HBM is sold out already for 2027 and that the industry is moving towards long term agreements. The cyclical dynamics in memory may be less pronounced going forward if LTA are the future of the industry which Micron has also announced in their earnings call. Disclosure I am long SK Hynix and NVIDIA.

Chris Zeoli's avatar

I tend to agree! I am bullish as well. The pricing power currently is extreme. Let's see how long it lasts!

Neil Irving's avatar

Really interesting.

I’ve been thinking about the operations layer and where value accrues. In construction, if productivity is increased by leveraging AI who wins? My gut feel is because of competition in the contractors, designers, and supply chain the value will end up with the clients and developers.

This isn’t my wheelhouse, interested in other views.

Chase Seklar's avatar

This was great

Feisal Nanji's avatar

Brilliant. Real analysis . Thoughtful . Totally agree with your thesis .

Dorian's avatar

The important distinction is between capex intensity and value capture.

The companies spending the most on AI infrastructure are not necessarily the ones earning the highest returns from it. Profit accrues where substitution is hardest: advanced chip design, leading-edge foundry capacity, HBM, lithography and high-speed networking.

That means the AI stack should be analyzed less like a software market and more like an industrial bottleneck map.

The strategic question is not who spends the most.

It is who controls the layer everyone else cannot bypass.

Arsham Mirshah's avatar

Harder they rise harder they fall. Durable layer is cyclical… clouds will continue to grow as demand and AI usage grows… a token costs the same to generate per watt - no matter what it’s sold for.

Tony Ferreira's avatar

The key question is not just who captures the most revenue, but where pricing power sits across the AI infrastructure stack. The margin versus growth split makes that especially clear.

Rameez MeeraSahib's avatar

NVIDIA's moat is beyond CUDA these days? They are delivering the highest value and capturing maximum margin. It would be interesting to see how that moat appears now and the competitive threats surrounding it.

Robert Marsh's avatar

Useful framing, thank you. Curious as to why AMD wasn’t included? Also, you call out the critical if often overlooked role of optics, but don’t include Corning or the like. Best

Chris Zeoli's avatar

Great points. AMD definitely deserves a spot as do optics players. I have covered some of the optics players in other posts on networking and should do more!

Julia Musson's avatar

Tremendous effort.

Dean's avatar

Who’s buying the end product that enables a return on this capital investment?

Chris Zeoli's avatar

The labs are the biggest buyers but also AI apps, enterprises, etc.

Dean's avatar

Understood. But currently the labs and so on are spending using capital raises , not from recurrent cash from sales of and end product to customers…