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ClaimVideo · 24:41 — 26:11

The AI industry is currently supply constrained rather than demand constrained — scarce compute, memory, data centers, and power — which makes a bubble less likely right now, though that could change with an algorithmic breakthrough enabling far smaller, more efficient models.

David argues that unlike classic bubbles driven by oversupply, AI today is bottlenecked by scarce data center capacity, power, and hardware — data center capacity at scale won't be available until late 2028/early 2029 — which makes a bubble unlikely in the near term, barring a breakthrough that shrinks model compute needs. ✦ AI generated

David · a16z Podcast · 2026-05-29 · original ↗

starts at this moment · 24:41

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Um and and do you know how how do you think that kind of changes the the shape of the the sort of cycle?

We're massively supply constrained. You can't get data center capacity at scale until late '28, early '29 right now... I think we're probably a year behind schedule of what people would expect for data center buildout in the US.

verbatim transcript · starts at 24:41

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24:41won't be in a bubble 3 years from now. But all all I can speak to is where we are right now. >> Yeah. >> Um we're massively supply constrained. You can't get data center capacity at scale until late '28, early '29 right now. And that's just a the Um I think that's going to get harder. I think we're probably a year behind schedule of what people would expect for data center

25:03buildout in the US. Um, you know, so we're already behind. We're supply constrained in pretty much everything in the supply chain for the data center. Um, part of that is, you know, TSMC showing restraint and, you know, trying to be balanced. Um, you know, but part of that is just other components that are hardware that are hard to manufacture and spin up to meet demand. Um, I think

25:25this data center resistance stuff is absolutely crazy. Um, you know, the the arguments that I see are are just wild. Um, you know, the best data center operators are going into communities and saying, you know, we're going to fund a nature preserve and we're going to fund high-speed internet in your school and, um, you know, we're going to make it beautiful and we're going to create a

25:46bunch of jobs and we're going to create a bunch of tax revenue and like that should all be good things and then, you know, we're we're met with resistance like, oh, it consumes too much water. And I'm like, well, I'd rather eat four or five fewer almonds and [laughter] like make sure that I have capacity to do all the things uh that that I need to do. Um, you know,

26:03my my yard consumes a lot more water than data centers. And so, um, we'll see if there's, um, you know, sort of melting resistance to this and it and it has an effect on the ecosystem, but I think it's more likely we remain supply constrained for the next 3 years than, um, than we end up in bubble territory. I would say the one thing that could shift that would be, you know, massively

26:23smaller models. You know, probably comes from like an algorithmic breakthrough of some sort. Um, you know, we do have companies that are working on that. You know, if you just start with the human brain, like the human brain is just far more efficient at learning, um, and, you know, requiring context for intelligence than than models. And so, I would expect there to be some shift in that.

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