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The AI bubble is bigger than you think

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Re: The AI bubble is bigger than you think

#11

Post by mrandish »

nobodywillobsrv wrote: post #3

There is a lot of bubbliness sure but some of the rhetoric is a bit sloppy. Like "swapping money back and forth" arguments is literally was economies and specializing results in. The debt securitization could be an issue but one thing that stands out to me is the if GPUs are really being used as the lein or collateral, these are fundamentally depreciating assets and are marked as such even if the depreciation rates a…

> even if the depreciation rates are slightly wrong.

The TFA cites a linked study which states "CoreWeave, for example, depreciates its GPUs over six years" which is way more than 'slightly wrong'. Just mapping that backward, 2020's hot new data center GPU was the A100 and they are just reaching their 5th year of service. How many large customers are lining up to pay top dollar to rent one of those 5 year-olds for the next 12 months? For most current workloads I think A100s are already net negative to keep operating in terms of opportunity cost. That power, cooling and rack space are more profitably allocated toward 2023's now mid-life H100 GPUs.

The rate of data center GPU progress has accelerated significantly in the last five years. I hardly know anything about AI workloads but even I know that newer GPU capabilities like FP8 are recent discoveries which can deflate the value of older GPUs almost overnight. With everyone now hunting for those optimization shortcuts, it's foolish to think more won't be discovered soon. The odds that this year's newly installed H200 GPUs will keep generating significant rental fees for 72 months are, IMHO, vanishingly small. Over a trillion dollars of loans have been secured by assets actually worth maybe half the claimed value. It's like 2009 sub-prime mortgages all over again.

Re: The AI bubble is bigger than you think

#12

Post by saulpw »

mrandish wrote: post #11
nobodywillobsrv wrote: post #3

There is a lot of bubbliness sure but some of the rhetoric is a bit sloppy. Like "swapping money back and forth" arguments is literally was economies and specializing results in. The debt securitization could be an issue but one thing that stands out to me is the if GPUs are really being used as the lein or collateral, these are fundamentally depreciating assets and are marked as such even if the depreciation rates a…

> even if the depreciation rates are slightly wrong. The TFA cites a linked study which states "CoreWeave, for example, depreciates its GPUs over six years" which is way more than 'slightly wrong'. Just mapping that backward, 2020's hot new data center GPU was the A100 and they are just reaching their 5th year of service. How many large customers are lining up to pay top dollar to rent one of those 5 year-olds for th…

> How many large customers are lining up to pay top dollar to rent one of those 5 year-olds for the next 12 months?

If it's depreciated over 6 years then at 5 years it's valued at 17% of its initial price. That seems kind of reasonable?

Re: The AI bubble is bigger than you think

#13

Post by tim333 »

bgwalter wrote: post #5
biff1 wrote: post #4

Earlier quoted context omitted.

Do the Saudi’s have a trillion to actually invest. It feels like Zalensky’s commitment to Macron, or various other commitments I keep hearing about. All very “check’s in the mail” vibes.

Good question. An NYT article that just came out says no: https://www.nytimes.com/2025/11/19/business/pif-saudi-arabia... According to the article, the sovereign wealth fund PIF has many poor/toy investments and is in need of bailouts itself. The squandering of investment money globally is unprecedented. They could literally just build (not buy!) $200 billion in affordable housing in Berlin or London and rake in 6% a…

It's been rather extraordinary. The Patrick Boyle vid on Neom done about a year ago was entertaining (https://youtu.be/Ak4on5uTaTg). As might be expected that's all ground to a halt now.

Re: The AI bubble is bigger than you think

#14

Post by tim333 »

There seems a bit of a hole in the logic here. The main thesis of the article is:

>I WILL TRY TO EXPLAIN THIS as simply as I can. The build-out of computing power for AI needs about $2 trillion in annual revenue by the end of the decade...

as a source for the it links the Bain article headlined "$2 trillion in new revenue needed..." but reading that their argument is

>... AI’s compute demand grows at more than twice the rate of Moore’s Law ...

>... By 2030, technology executives will be faced with the challenge of deploying about $500 billion in capital expenditures and finding about $2 trillion in new revenue

but demand is a function of price. AI companies could just stop making dumb meme videos, using a lot of compute, for free.

It's like if a food chain gives away a free donut today and two tomorrow it doesn't automatically mean it will give away 2^365 donuts in a years time and crash the economy. They could always stop the free donuts.

Even if the wanted to, they'd run out of donut mix and even if AI companies want to give away infinite compute they'd run out of energy and chips. Energy supplies for AI are pretty maxed out already. No way those are growing at twice the rate of Moore's law.

Re: The AI bubble is bigger than you think

#15

Post by solumunus »

tim333 wrote: post #14

There seems a bit of a hole in the logic here. The main thesis of the article is: >I WILL TRY TO EXPLAIN THIS as simply as I can. The build-out of computing power for AI needs about $2 trillion in annual revenue by the end of the decade... as a source for the it links the Bain article headlined "$2 trillion in new revenue needed..." but reading that their argument is >... AI’s compute demand grows at more than twice…

Exactly. Eventually the real cost to the consumer is going to emerge, demand will decrease and they hope revenue grow. I for one am worried about how much I’ll have to fork out, because I really don’t want to lose my current workflows.

Re: The AI bubble is bigger than you think

#16

Post by nobodywillobsrv »

saulpw wrote: post #12
mrandish wrote: post #11

Earlier quoted context omitted.

> even if the depreciation rates are slightly wrong. The TFA cites a linked study which states "CoreWeave, for example, depreciates its GPUs over six years" which is way more than 'slightly wrong'. Just mapping that backward, 2020's hot new data center GPU was the A100 and they are just reaching their 5th year of service. How many large customers are lining up to pay top dollar to rent one of those 5 year-olds for th…

> How many large customers are lining up to pay top dollar to rent one of those 5 year-olds for the next 12 months? If it's depreciated over 6 years then at 5 years it's valued at 17% of its initial price. That seems kind of reasonable?

Yes, I think it's worth getting details ... like my mental model is that everything within 2x is sort of reasonable error. Looking for 10x errors and cliff edges like in the 2007 crisis where I think a good anecdote is like default prob assumptions being 2% and then realized to 30% (15x).

Is 15x error in realized GPU + the debt AFTER INFLATION? I suppose but feels less likely except in some tail scenarios that have other interesting properties.

This doesn't mean that there isn't a significant possibility of market correction due to other factors but the GPU factor just seems medium sized compared to other scenarios historically. Am I missing anything in the 1st order thinking?

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