Where are you getting the 20% and 80% split? The epoch.ai link suggests 60% is servers, which includes a lot more equipment than GPUs, so the 80% number is already off. It’s also unclear how power commitments is being included in that 80% with a 3-year lifetime.

In fact, to focus on the short lifetime assets alone, this more recent link suggests servers are 50% of CapEx, and GPUs are about 25 percentage points.

https://cib.bnpparibas/ai-infrastructure-investment-2026/

So already about 50% of CapEx spend is one-off construction / installation with a very long lifetime.

That leaves servers and GPUs. There is a ton of evidence out there that even chips from multiple generations ago, ie way more than 3 years old, are commanding pretty high rates. So even if they are replaced by newer chips every year, the older chips still hold a lot of value and can’t simply be written off to 0.

I think this is the most comprehensive look at the AI economy so far, probably a better source than the rest: https://www.exponentialview.co/p/the-state-of-the-ai-economy — it suggests everything is walking a tightrope but still sustainable for now.

> Where are you getting the 20% and 80% split?

Like I said, it's a heuristic, and the error bar on that opinion is... "50/50 split is also bad", for debt financing reasons. I'm skewing my guesstimate toward a pareto-split bear case, because 50/50 is the rosy-eyed best-ever case being proffered by parties who need the story to remain believable. I doubt anyone has a true grasp of the opaque financin.

In any case, I'm trying to reason from first principles.

A) The sheer quantum of debt financing skews the whole US economy, and that is a hard thing to skew. This means debt will keep getting repriced, higher interest rates, because risk exposure to financiers increases non-linearly when said risk becomes industry-wide.

B) Compute and power become inelastic, at the scale and rate of expansion of LLM datacenter. The become highly contested practically fixed resources. Prices will go up, and they are likely to go up faster with every marginal increase in demand.

C) Far better informed parties have been warning about severe under-quoting of liabilities for a while now. e.g. Some of the resources informing my opinion include publishing by Asad Ramzanali / Vanderbilt Policy Accelerator and Michael Burry / Cassandra Unchained. Worth reading their stuff:

After the AI Crash, by Asad Ramzanali, Vanderbilt Policy Accelerator (March 2026): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6476159

Michael Burry Warns: AI Infrastructure Depreciation Is Masking Billions in Costs https://nova.kapualabs.com/goog-sys_onboarding/michael-burry...

(To be clear, just because Burry was spectacularly on the money that one time about CDOs, doesn't automatically mean he is right about this, but he does have a habit of calling out bullshit as he sees it, particularly dodgy financial engineering of the kind these people are doing... Corroborated by others like Asad Ramzanali.)

Ah, maybe "heuristics" is not an accurate word here, because it usually indicates something based in observation of empirical evidence or trial and error, even if its typically unscientific, so I was curious about the inputs to the 20/80 split.

I skimmed through the "After the AI Crash" paper, and it is really not an analysis but a policy brief that mostly reiterates, and uncritically accepts, a lot of the large numbers thrown about in other media sources. There is no analysis of the demand side and cash flows and timelines involved, and spends a lot of time on the circular investment issue with any attempt to unravel it.

The exponential view analysis is much more methodical and finer-grained in its approach, and it addresses a lot of the aspects you mentioned, including prices and demand.

As for whatever Michael Burry has said, I've looked into it a bit (as an outsider, no inside knowledge) and I don't quite buy his thesis. There are indications from too many different sources that GPUs are economically valuable for much, much longer than the timeline he assumes.

A good thing to Google AI Overview would be "How many market crashes has Michael Burry predicted?", and wonder why all those other predictions didn't get the airtime this one is. I have a theory: https://news.ycombinator.com/item?id=50421245 ;-)

Well, I'm glad to be wrong on the Internet :D

Apropos schadenfreude, I don't have a dog in the fight---I don't even actively use LLMs, because they don't work for how I'm wired.

I'd like to have a future-dog in the fight though. I want the LLM-hyperscaler bear case to happen because I want access to dirt-cheap compute, which I hope will be the aftermath of a financial failure of the hyperscaler junta. What will be left is industrial capacity to make tons of chips and computers, which I hope translates in to dirt-cheap retail compute. eCoin-world is unlikely to absorb all that because mining unit economics and coin volatility are both significant enough to make people consider the bet.

And like, LLM tech is quite cool and useful and all (ignoring for the moment, the planet-scale piracy by the hyperscalers), but the other "normal" stuff is so much more so.

As for the odds of them making a God, I'm taking an inverse Pascal's wager, as I wrote here: https://news.ycombinator.com/item?id=50427160

Oh I did not mean to attribute "SchadenFraud" to you! Rather I meant I suspect that's the reason Burry's current AI bear thesis is catching on way more than his previous bearish calls.

I would like a world of cheap compute too really, but I fear at this point it could only happen if all AI demand suddenly disappeared and never came back. Given how fast it is growing and how far it still has to grow, compounded by the limited rate at which new capacity is being built, it seems unlikely we'll get to an overbuilt state for an extremely long time... unless, like you said, there are dramatic breakthroughs in computation efficiency.