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So where would this increased demand come from? We see that these companies have no moat. We see that companies are already balking at the cost and are increa

So where would this increased demand come from? We see that these companies have no moat. We see that companies are already balking at the cost and are increasingly looking at what the actual return of their current spend is, let alone when these prices have been increasing. Where is the increase in demand going to be coming from? Especially the increase needed to make this make sense?

npilk 2mo ago
My personal hunch is that the “diffusion curve” for AI is slower than most people in this space think. Most businesspeople I talk to have only tried a basic Copilot chat and/or free ChatGPT. Many still haven’t used anything “AI” at all. As more use cases become practicable and cost-effective, more software will include AI, and more people will use AI with or without knowing. Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. Of course they could be wrong, but they’re not made up.
- cogman10 2mo ago
  > Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. I think Ed is wrong. But I have to push back. Wall street analysts are more likely to misrepresent precisely because they have money at stake. Much like ed has a pretty vested interest in saying the sky is falling (that's his brand at this point) the analysts have vested interests in saying everything is fine and keep investing. We can see similar behaviors with analysts like zero hedge, which every week write a new "the bubble is about to pop" article. A lot of this, IMO, is similar to a fact about the weather I'm probably misremember from stats. If you always predict "it will be sunny tomorrow" almost anywhere in the world you'll be right something like 80 to 90% of the time (citation needed). Analysts who always say "things are great and stocks will go up" will be right most of the time. The tricky thing has always been predicting when and if a pop will happen.
  - npilk 2mo ago
    Yes, fair point, analysts tend not to be too critical. But they are still developing more detailed models to understand and project things like revenue and profit, so there's some rigor - at least more than company leadership just giving takes or stating platitudes.
- deleted 2mo ago
  [deleted]
- ragall 2mo ago
  Here's from a VC: https://x.com/bryce/status/2080766415716692385 https://x.com/bryce/status/2080766415716692385 "Have lost count of the number of CEOs I’ve talked to this week that are planning to be moved off OAI and Anthropic entirely by years end."
  - npilk 2mo ago
    Interesting. I wonder what they will move to, and where it would be hosted.
    - ragall 2mo ago
      Self-managed open models hosted on GPU clouds.
      - npilk 2mo ago
        A lot of that demand could still flow through to AWS, Azure, etc. Maybe not at some startups, but I'd expect bigger companies would still use the hyperscalers even if they move off OAI/Anthropic. The real problem for the hyperscalers would be demand stalling out entirely (or maybe small local models getting good enough that people don't use the cloud).
        ragall 2mo ago
        The infra expansion of the hyperscalers is predicated on, and financially justified by, the presumed future growth of OpenAI and Anthropic, and their projected revenue. If the latter is not going to happen, I expect OpenAI and Anthropic to go bankrupt, which will trigger a restructuring of the hyperscalers, which should flood the market with either training HW or training capacity at very low cost, and it's not necessarily the hyperscalers that will benefit the most: I believe some of the GPU clouds are using HW leased or bought form NVidia, and running inside second-tier datacenters, not the hyperscalers.
fragmede 2mo ago
If you believe in the notion that the technology will improve to the point of being able to replace a human employee, the increase in demand is going to come from businesses that choose AI employees over human ones. Even if the AI employee costs more than human one, it's like a car vs a horse. The AI employee doesn't get sick, doesn't get into trouble with HR for sexual harassment, never comes into work hung over. You can hire 100 AI employees for a week and them fire them the next and not feel bad about it. Whether this comes to pass is anyone's guess, but that's the theory.

npilk 2mo ago

My personal hunch is that the “diffusion curve” for AI is slower than most people in this space think. Most businesspeople I talk to have only tried a basic Copilot chat and/or free ChatGPT. Many still haven’t used anything “AI” at all. As more use cases become practicable and cost-effective, more software will include AI, and more people will use AI with or without knowing. Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. Of course they could be wrong, but they’re not made up.

cogman10 2mo ago
> Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. I think Ed is wrong. But I have to push back. Wall street analysts are more likely to misrepresent precisely because they have money at stake. Much like ed has a pretty vested interest in saying the sky is falling (that's his brand at this point) the analysts have vested interests in saying everything is fine and keep investing. We can see similar behaviors with analysts like zero hedge, which every week write a new "the bubble is about to pop" article. A lot of this, IMO, is similar to a fact about the weather I'm probably misremember from stats. If you always predict "it will be sunny tomorrow" almost anywhere in the world you'll be right something like 80 to 90% of the time (citation needed). Analysts who always say "things are great and stocks will go up" will be right most of the time. The tricky thing has always been predicting when and if a pop will happen.
- npilk 2mo ago
  Yes, fair point, analysts tend not to be too critical. But they are still developing more detailed models to understand and project things like revenue and profit, so there's some rigor - at least more than company leadership just giving takes or stating platitudes.
deleted 2mo ago
[deleted]
ragall 2mo ago
Here's from a VC: https://x.com/bryce/status/2080766415716692385 https://x.com/bryce/status/2080766415716692385 "Have lost count of the number of CEOs I’ve talked to this week that are planning to be moved off OAI and Anthropic entirely by years end."
- npilk 2mo ago
  Interesting. I wonder what they will move to, and where it would be hosted.
  - ragall 2mo ago
    Self-managed open models hosted on GPU clouds.
    - npilk 2mo ago
      A lot of that demand could still flow through to AWS, Azure, etc. Maybe not at some startups, but I'd expect bigger companies would still use the hyperscalers even if they move off OAI/Anthropic. The real problem for the hyperscalers would be demand stalling out entirely (or maybe small local models getting good enough that people don't use the cloud).
      - ragall 2mo ago
        The infra expansion of the hyperscalers is predicated on, and financially justified by, the presumed future growth of OpenAI and Anthropic, and their projected revenue. If the latter is not going to happen, I expect OpenAI and Anthropic to go bankrupt, which will trigger a restructuring of the hyperscalers, which should flood the market with either training HW or training capacity at very low cost, and it's not necessarily the hyperscalers that will benefit the most: I believe some of the GPU clouds are using HW leased or bought form NVidia, and running inside second-tier datacenters, not the hyperscalers.

fragmede 2mo ago

If you believe in the notion that the technology will improve to the point of being able to replace a human employee, the increase in demand is going to come from businesses that choose AI employees over human ones. Even if the AI employee costs more than human one, it's like a car vs a horse. The AI employee doesn't get sick, doesn't get into trouble with HR for sexual harassment, never comes into work hung over. You can hire 100 AI employees for a week and them fire them the next and not feel bad about it. Whether this comes to pass is anyone's guess, but that's the theory.