by jsnell | 2025-07-22 19:58:50+00:00
The analysis is just bogus. He is basically comparing two years of inflated AI capex estimates to a low-ball estimate of one year of trailing revenue.

Let's unpack that a bit.

Capex is spending on capital goods, with the spending being depreciated over the expected lifetime of the good. You can't compare a year of capex to a year of revenue: a truck doesn't need to pay for itself in year 1, it needs to pay for itself over 10 or 20 years. The projected lifetime of datacenter hardware bought today is probably something like 5-7 years (changes to the depreciation schedule are often flagged in earnings releases, so that's a good source for hard data). The projected lifetime of a new datacenter building is substantially longer than that.

Somehow Zitron manages to not make a comparison that's even more invalid than comparing one year of Capex to one year of revenue: he basically ends up comparing a year of revenue to two years of Capex. So now the truck needs to pay for itself in six months.

They way you'd need to think about this is to for example consider what the return on the capital goods bought in 2024 was in 2025. But that's not what's happening here. Instead the article is basically expecting a GPU that's to be paid for and installed in late 2025 to produce revenue in early 2025. That's not going to happen. In a stable state, this would not matter so much. But this is not a stable state. Both capex and revenue are growing rapidly, and revenue will lag behind.

What about the capex being inflated and the revenue being low-balled?

None of us really know for sure how much of the capex spending is on things one might call AI. But the pre-AI capex baseline of these companies was tens of billions each. Probably some non-AI projects no longer happen so that the companies can plow more money into AI capex, but it absolutely won't be all of it like the article assumes. As another example, why in the world is Tesla being included in the capex numbers? It's just blatant and desperate padding of the numbers.

As for the revenue, this is mostly analyst estimates rather than hard data (with the exception of Microsoft, though Zitron is misrepresenting the meaning of run rate). Given what he has to say about analysts elsewhere, seems odd to trust them here. But more importantly, they are analyst estimates of a subset of the revenue that GPUs/TPUs would produce. What happens when Amazon buys a GPU? Some of those GPUs will be used internally. Some of them will be used to provide genai API services. Some might be used to provide end-user AI proucts. And some of them will be rented out as GPUs. Only the two middle ones would be considered AI revenue.

I don't know what the fair and comparable numbers would be, am not aware of a trustworthy public source, and won't even try to guess at them. But when we don't know what the real numbers are, the one thing we should not do is use obviously invalid ones and present them as facts.

> I am only writing with this aggressive tone because, for the best part of two years,

Zitron's entire griftluencer schtick has always been writing aggressive and often obscenity-laden diatribes. Anyway, please don't forget to subscribe for just $7/month, and remember that he just loves to write and has no motive for clickbait or stirring up some outrage.