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Ctrl-F “amortiz”: Not Found Microsoft’s total depreciation and amortization in Q2 2027 was $11B - not clear how much of this is AI related. Apparently they had

by npilk 2mo ago

Ctrl-F “amortiz”: Not Found Microsoft’s total depreciation and amortization in Q2 2027 was $11B - not clear how much of this is AI related. Apparently they had $34B in AI ARR as of May. So let’s say their AI capex amortization and revenue are about equal. Not amazing, obviously they’re relying on continued growth, but doesn’t seem like the end of the world? Compare that to Ed’s framing - Microsoft has $34B in revenue but spent $116B in capex last year to “make it”. They’re doomed! But that capex spend is to make future revenue. Clearly he assumes demand won’t increase in the future, and that future projected revenue is “fake”. And sure, it definitely might not increase enough to make profitability. But his whole analysis hinges on that one assumption. The entire article, all the numbers he gish gallops at you, could basically be replaced with “I don’t think AI demand and revenue will increase much beyond today.” Yeah, we know.

ofjcihen 2mo ago
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.
- 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.
twister2920 2mo ago
> gish gallops this is a funny way of spelling "cites sources" and "does basic math"
- fragmede 2mo ago
  > The Gish gallop is a debate tactic where one person overwhelms an opponent with a massive, rapid-fire stream of many minor, weak, or false arguments https://en.wikipedia.org/wiki/Gish_gallop https://en.wikipedia.org/wiki/Gish_gallop
  - ofjcihen 2mo ago
    What data here is false? How do you gish gallop in writing?
    - npilk 2mo ago
      I would say Ed makes three main claims in this post: 1) Companies are spending a ton on capex for future AI compute 2) Current levels of AI revenue are not enough to recoup that capex spend 3) Revenues won’t increase enough in the future to recoup that capex spend Almost anyone, bubbler or not, would agree with points 1 and 2. But Ed cites dozens of numbers from different sources to repeat and reinforce them. It feels to me like an effort to overwhelm the reader with data to support his overall argument. That’s what I would call a gish gallop. The third point is a prediction. He cites a lot of facts and numbers here too, but ultimately whether you believe his prediction is going to depend on your assumptions. The thing is, I really would love to see a detailed analysis of capex spend and amortization. Capex spent on the future is a big unknown. But the big labs have claimed they are profitable on inference. How much capex was invested to create the capacity to serve current models? How much revenue is coming from serving those models? What does the full profitability picture look like? What does that imply for future demand needs?
      - ofjcihen 2mo ago
        On your last paragraph the simplest answer as to why we haven’t seen that is because they don’t want to show us because it wouldn’t paint a great picture for them. Regarding Gish galloping, I don’t think you can Gish Gallup in writing. The point as you said is to rapidly overwhelm an opponent. That’s not possible in writing as the points can be argued one by one at the responders leisure.

by npilk 2mo ago

ofjcihen 2mo ago

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.
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.

twister2920 2mo ago

> gish gallops this is a funny way of spelling "cites sources" and "does basic math"

fragmede 2mo ago
> The Gish gallop is a debate tactic where one person overwhelms an opponent with a massive, rapid-fire stream of many minor, weak, or false arguments https://en.wikipedia.org/wiki/Gish_gallop https://en.wikipedia.org/wiki/Gish_gallop
- ofjcihen 2mo ago
  What data here is false? How do you gish gallop in writing?
  - npilk 2mo ago
    I would say Ed makes three main claims in this post: 1) Companies are spending a ton on capex for future AI compute 2) Current levels of AI revenue are not enough to recoup that capex spend 3) Revenues won’t increase enough in the future to recoup that capex spend Almost anyone, bubbler or not, would agree with points 1 and 2. But Ed cites dozens of numbers from different sources to repeat and reinforce them. It feels to me like an effort to overwhelm the reader with data to support his overall argument. That’s what I would call a gish gallop. The third point is a prediction. He cites a lot of facts and numbers here too, but ultimately whether you believe his prediction is going to depend on your assumptions. The thing is, I really would love to see a detailed analysis of capex spend and amortization. Capex spent on the future is a big unknown. But the big labs have claimed they are profitable on inference. How much capex was invested to create the capacity to serve current models? How much revenue is coming from serving those models? What does the full profitability picture look like? What does that imply for future demand needs?
    - ofjcihen 2mo ago
      On your last paragraph the simplest answer as to why we haven’t seen that is because they don’t want to show us because it wouldn’t paint a great picture for them. Regarding Gish galloping, I don’t think you can Gish Gallup in writing. The point as you said is to rapidly overwhelm an opponent. That’s not possible in writing as the points can be argued one by one at the responders leisure.