Fact◆Audio · 8:29 — 11:23
Everything in this AI market is power constrained — the reason companies miss forecasts is entirely about supply of power, not demand.
Chamath argues that OpenAI and Anthropic's growth issues are not demand problems but power supply constraints — access to electricity for token generation is the single choke point, and the situation is worsening as most announced data center projects face delays from red tape and supply chain issues. ✦ AI generated
Chamath Palihapitiya · All-In Podcast · 2026-05-01 · original ↗
plays this moment only · 8:29 — 11:23
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“Are they going to run off the cliff or will it wind up being brilliant even if it wasn't strategically for the exact reasons?”
I think they're going to be fine. I think this is a multi-trillion dollar company. I think Anthropic is a multi-trillion dollar company. I think the thing that's happening right now is a complete misunderstanding of what's actually happening inside of the world of AI. And there is one very specific choke point that is constraining everything, which is access to the power that's necessary to drive these tokens. To the extent that OpenAI missed, I think what that is, an insight to not enough compute capacity today. And that problem is only getting worse. You've already seen that with Anthropic as well, where they just found a way to economically induce Amazon to give them enough capacity so that you don't have to route through bedrock to get to the Anthropic models. You're also seeing them do differentiated deals now with economic participation on top of what they already had from folks like Google to give them more capacity. What is my point? Everything in this market is power constrained. The reason that these folks may miss a number or a forecast have nothing to do with demand. It is entirely 100% due to the supply of the power necessary to generate the output token. There was a really interesting thing that was just announced today that will make this problem even worse, which is what you're starting to see now is backlogs build up of not just the access to the power, but then the componentry that's actually necessary, not just recips and not just nat gas turbines, but now you're talking about transformers and all the actual tactical grid infrastructure. Why is this important? If you look at the actual amount of gigawatts that are under construction, we have a huge mismatch now. People have announced all these projects, Jason, but less than half of it is actually being built. Less than half. Most of it is stuck in red tape. Most of that is because there are these supply chain delays. So there's no credible strategy to turn any of this stuff on. Who will this hurt? It will hurt Anthropic and OpenAI the most. Who will this benefit? It will benefit the hyperscalers, specifically Oracle, Amazon, Meta, Microsoft, and Google. And now what you're going to see is a negotiation and a trade back and forth. How much equity do I have to give up? How much control do I have to give up to get access to the compute versus how badly will I miss my growth forecasts if I don't? And now what that means is, and we spoke about this last week, that's a huge lane for Grok to just run through and SpaceX to run through, because they have a ton of excess capacity. And so I think the cursor deal was the appetizer. But if I were Elon now, I'd be running all over this market because if the models catch up in quality, I think he could also do something really crazy with Anthropic or OpenAI right now.
verbatim transcript · starts at 8:29
- ·OpenAI & Anthropic growth misses stem from power supply, not demand
- ·Access to electricity for token generation is the single choke point
- ·Data center projects face delays from red tape and supply chain issues
- ·Problem is worsening as grid infrastructure (transformers, turbines) lags
- ·OpenAI and Anthropic hurt most by power constraints
- ·Hyperscalers (Oracle, Amazon, Meta, MS, Google) benefit from capacity
- ·Grok and SpaceX positioned to exploit their excess capacity
- ·Companies must trade equity/control for compute access
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supports → Microsoft's real supply constraint today is power and the ability to build out data centers fast, not a shortage of chips — chips are actually sitting in inventory unable to be plugged in.Satya Nadella · BG2 Podextends → The MIT paper on pruning techniques shows you can reduce neural network size by 90% with the same accuracy, achieving 10x inference per energy unit — this is where the real efficiency gains will come from.David Friedberg · All-In Podcast