7 ms·

The Teaser Period: Why the AI Boom Is Hitting a Reset Wall

95 points by gtzi 1mo ago

jumanji493 1mo ago
wow excellent piece. Gary Marcus had a long post about this article on his substack. scary stuff "And look at what this implies about OpenAI’s valuation as it moves toward an IPO: OpenAI’s equity - valued north of $850 billion - is functionally the junior tranche of a capital structure whose senior claims, the take-or-pay compute obligations, exceed any revenue path management itself has articulated. On those numbers, the equity is effectively underwater, and the market has not priced it that way because it still treats those obligations as service agreements rather than what they are economically: debt. Even if OpenAI can meet those obligations, OpenAI’s unaudited financial statements - as of March 31, 2026 - disclose $665 billion in non-cancellable compute commitments (management’s more recent plan runs to $750 billion). These commitments are take-or-pay in structure - which, as established above, is debt. Carry the net present value of those obligations as senior debt - roughly $450–500 billion, the same methodology rating agencies have used for decades to capitalize take-or-pay contracts as debt - and a company the market prices as debt-free carries a senior claim worth more than half its entire equity value." and the 2008 analog "Millions of subprime borrowers were, at that moment, paying the low introductory rate on a two-year adjustable rate mortgage - the 2/28 ARM. A low fixed-rate for two years, then the rate reset to a payment 30% to 50% higher. During those first two years the loan performed beautifully: the borrower paid, the servicer collected, and the bond paid its coupon. Nothing looked wrong because the whole complex - housing, mortgages, securitization - was sitting inside the teaser period. The AI boom has rebuilt this exact structure, and the market is once again underwriting the teaser. It has a reset wall of its own - a schedule of dated, contractual, non-negotiable payment shocks - hiding inside the trillions of dollars of compute contracts signed by OpenAI and other frontier labs since 2024."
- ameliaquining 1mo ago
  Marcus believes that the underlying technology doesn't work. If that's true, then of course the whole thing will crash as soon as everyone realizes this. This article is mostly making a different argument (though it contradicts itself in some places), which is that even if the underlying technology does work, and is ultimately going to create quadrillions of dollars of value and transform society, if it takes more than another 1–2 years for that to happen, then there'll still be a crash, because that's when the data center construction bills come due and the labs (especially OpenAI) don't yet have the money to pay them. It argues primarily against a hypothetical optimist who believes that everything is fine because the cash flow numbers currently work out, on the grounds that this hypothetical optimist hasn't realized that the labs' recurring expenses are scheduled to spike in 1–2 years when the data centers come online and the labs have to start paying for them. It also spends a lot of words comparing the situation to the 2008 financial crisis, because that's everyone's favorite morality tale. I am not sure that anyone is actually making this mistake (i.e., trying to predict the future by looking at labs' present cash flows). The better counterargument is what Matt Levine used to call "Netflix Theory": if the large capital investors who own stakes in the labs still believe in their valuations (which they should, if the technology works and the quadrillions are coming, which we're assuming here for the sake of argument), then they will be very highly motivated not to let their investment be seized by the labs' creditors. So the labs will not have too much difficulty raising or borrowing enough money to pay the bills.
  - michaelchisari 1mo ago
    There's a third possibility between works and doesn't work: Works but not quite good enough to make the case against commoditization. If open source or on-device AI gets good enough for 80% of consumers, then this stops being a consumer product and the only real market is people who need the high-end models. If those models are slow and expensive, certain tasks like scientific and math research can tolerate slowness, but they run up against the costs. If they're expensive, the tech industry can afford them but runs up against their inefficiencies. We need to talk about how well these improving models work in multiple dimensions: Accuracy, performance and cost. All three have to improve considerably before the debate dies down.
    - ameliaquining 1mo ago
      Yes, if the tech works but in a way that doesn't let the labs command premium prices for inference, then that also means a crash. But that's a fundamentals-based argument like Marcus's (despite being based in economics rather than ML science), so distinct from the one the article's mostly making.
  - dumberquestions 1mo ago
    Yes, the labs will be fine as long as investors believe in them, and they overwhelmingly do, trying to draw comparisons based on traditional market wisdom will fail because none of this is precedented.
  - w10-1 1mo ago
    > large capital investors [...] will be very highly motivated not to let their investment be seized [...] So the labs will not have too much difficulty raising or borrowing enough money to pay the bills So: sunk costs of large investors mean they'd be willing to pay high interest costs? Thus small investors can rely on this dynamic, shielded by big ones? Remember, the large investors got large in a near-zero interest rate environment (where exact timing doesn't matter as much), but those days are not coming back. Soon margins will matter most, and while NVDA and Apple have the internal discipline for that, OpenAI et al do not.
NDlurker 1mo ago
So, start selling risky assets for bonds and wait for the crash to buy back in to stocks?
- CBLT 1mo ago
  If you can actually time the market, sure. I cannot, so I don't pull money out of my stock indexes; I just send a larger fraction of my new investments into bonds.
  - NDlurker 1mo ago
    That's a smarter idea. I've tried timing the market in the past and have been very wrong.
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- lesuorac 1mo ago
  Who are you going to sell the bonds to? People only want cash during the crash so the value of everything goes down. It doesn't matter if you bond has a known 8% yield when held to maturity; the market can't hold it to maturity so its current value drops. Like go find 2008 in the graph of BND (Vanguard Bond ETF) vs SPY (SNP500) [1]. Let me know how you'd know when to sell your bonds for stocks. [1]: https://www.google.com/finance/beta/quote/SPY:NYSEARCA?keymoments=false&comparison=BND%3ANASDAQ&type=line&window=MAX https://www.google.com/finance/beta/quote/SPY:NYSEARCA?keymo...
firmretention 1mo ago
Sloppity slop.
- NDlurker 1mo ago
  That was the impression I got too, so I just skimmed it
awongh 1mo ago
I get the structural comparison they are trying to make. But mortgages are not a frontier AI lab. They try to draw a comparison to the valuation of the real estate and the valuation of the hyper scalers in the markets. I would argue that the demand and valuation of a house is less elastic than AI. While a house’s value may continue to appreciate in the market there is an upper bound for the price of a house set by people’s income. We don’t know yet what the value of AI is. The underlying product, the model keeps improving and therefore increases its value. A house is still fundamentally a house a year later and doesn’t intrinsically appreciate in value. From gpt-3 to gpt-5.5 there’s been a massive change in the underlying value of the product and company in a way that simply doesn’t happen with a house. That’s where the analogy breaks down.
- tyromaniac 1mo ago
  I think its well corrected by the increase in competition that meets or exceeds the quality. The house may have gotten nicer but now you are selling a single room
- vmg12 1mo ago
  The dynamics are interesting. If all businesses get productivity increases from AI, the margins they could have claimed are competed away. The model companies also have their margins competed away because of open models. The only companies that have a moat are the ones with capital as a barrier to entry and even then there is cut throat competition. We might end up with massive consumer surplus from AI because no business will be able to raise prices due to competition. This is why it's so important that we don't allow for regulatory capture in this space.
  - plasticchris 1mo ago
    Yes and much like the technological leaps of the past, everyone’s standard of living goes up.
- rootusrootus 1mo ago
  The value is going up, but the pricing is going down, right? At least at the token level. So the usage would have to go up dramatically to compensate for that. > there is an upper bound for the price of a house set by people’s income Isn't that essentially true here too? The money to pay these expected future AI prices is coming from someone's income. Sure, the pie will be growing at the same time, but enough?
alexpotato 1mo ago
> Every ARM reset was known, dated, and contractually inevitable from the moment of origination. Aggregate those reset schedules and you get the most damning exhibit of the era: the reset wall. One of my distinct memories from this era is watching CNBC where a guest said exactly the same thing. As the interview went on, he became more animated and used stronger language to the point of: "You don't get it, THEY ARE GOING TO BE PICKING PEOPLE OFF THE FLOOR when these ARM rates reset" I would guess this was right about 2006 which lines up with the article.
Espressosaurus 1mo ago
Interesting piece, I just wish the author had presented the data and their thesis instead of making Claude vomit out 20 pages of trash around it.
- johnfn 1mo ago
  I really want to get in the mindset of people who are like "AI is totally going to fail! Haha! Now let me just use AI to write a piece about it..."
  - Espressosaurus 1mo ago
    It's not inconsistent if you think of it as the finances falling apart regardless of how useful the tool is.
    - johnfn 1mo ago
      The article claims that the finances fall apart because OpenAI won't hit the growth it wants. It's an interesting thing to say when using their product to write 100% of the article.
      - owebmaster 1mo ago
        Using the free version reinforces the point.
    - throwawayqqq11 1mo ago
      Bubble != AI.
- Sharlin 1mo ago
  Yeah, the signal-to-noise ratio was way too low to keep reading for long.
- nnevatie 1mo ago
  Indeed - obvious AI slop with the annoying language all of the place.
harshaw 1mo ago
Some other commentators said this was AI slop. I don't have enough expertise to say if it really is, but it sure has the "claudish" cadence of AI generated text that makes it hard to take it seriously. The authoritative and strong statements, the use of phrasing with colons and dashes, the use of bold, etc.
- Espressosaurus 1mo ago
  The claims and data are interesting (perhaps overstated in the usual Claude way) but it's about 20x more prose than is actually justified.
- ameliaquining 1mo ago
  Pangram confirms: https://www.pangram.com/history/9ccdf6ed-5016-4325-b1ac-b3b0150a6784 https://www.pangram.com/history/9ccdf6ed-5016-4325-b1ac-b3b0... I find it amusing that even the AI skeptic articles are written with AI these days.
- georgemcbay 1mo ago
  > Some other commentators said this was AI slop. To me it read like a combination of human written and AI slop, as if the author had Claude write it and then rewrote portions of it, or the author wrote an initial version and told Claude to "punch it up, without rewriting the whole thing entirely". Regardless of who or what actually wrote it the piece was much longer than it needed to be (though I do think it highlights a very real problem).
Synaesthesia 1mo ago
IMO there is overinvestment in compute and this will turn out to be a bubble. But all of the money was anyway just lying around doing nothing. An enormous amount of capital has been building since the 80's thanks to corporate profits. A small sector of the population is so rich they don't know what to do with their capital.
tschellenbach 1mo ago
This post is just AI slop. The details of these contracts aren't disclosed as far as I know. You need to understand the contracts, the acceleration of demand, how the various inputs into supply scale (energy, chips, data centers) etc to say something sensible about this.
bradfa 1mo ago
It would be nice if the article cited the actual contracts the labs have signed so that others could also read them and draw their own conclusions (maybe it does and I got tired of the slop-like writing style too early?). Are the contracts actually take-or-pay-style? What are the terms? What are the amounts of compute and money involved for each future time period? What happens if the datacenter costs spiral upwards? What happens to the datacenter investment if the buyer goes bankrupt, goes public, or gets acquired (potentially by the datacenter owner)? I personally think the datacenter build-outs are going to generally be a big swing and a miss. The problem 1-2 years ago was making models good enough to be useful for a variety of tasks. Now we have that. The next problem is making the models efficient enough to run a profitable business. Recent Chinese lab model releases (because they're already constrained on compute resources) and OpenAI price cuts on Luna seem to indicate that this transition to chasing efficiency has already started.
- krona 1mo ago
  > The next problem is making the models efficient enough to run a profitable business. In that world, what does Oracle do with a bunch of data centres which 1. It needs to pay for and 2. nobody needs. This is what the article is about: building supply far in advance of demand.
  - bradfa 1mo ago
    I don't know, but unless that contract is public, not many people know. I get the impression Oracle got a little bit of market pushback on the risk, as theirs seems to be one of the largest.
    - krona 1mo ago
      What contract? It's mostly corporate debt. Seems pretty plain and simple to me. The contracts I guess you're talking about are compute obligations which frontier labs have. I don't need to know what those obligations are to know what happens to Oracle.
Havoc 1mo ago
It’s an interesting comparison. The housing market is linked to the value of the house though which is subject to crashes in value without a corresponding drop in demand. With AI it comes down to whether the large companies orders and building of datacenters aligns with token demand. There is years worth of lag there so they kinda have to front load this by necessity
hughw 1mo ago
"The hidden mechanics reveals how the AI boom breaks, and when." I stopped there. I just resist reading slop.
deleted 1mo ago
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alwa 1mo ago
This feels like Claude thought to me—assertions and comparisons that look impressive on the surface, but kind of make me scratch my head the more I think about them. I think what made me throw in the towel was “Figure 2 — Two Instruments, One Shape” [0]. That chart comparing when contracts reset. Weirdly consistent norms! [looks at the sourcing] Oh… it’s… not from data at all… it’s just notional… Is there anything here other than “the people financing the factory are betting that it’ll be able to sell what it makes once it’s built”? I mean… isn’t “an instrument that splits time in two” kind of… what capital financing is? And this risk is what earns investors their interest, and the rest of the financial system involves different ways for people to calibrate their bets on the risk materializing? Including derivative instruments that allow investors to smear out the point-in-time “cliffs” this writer is concerned about? If you think the revenue is never going to come, you can bet on that now. Or go into the distressed datacenter acquisition business to prepare! Conversely if Payment Day comes and you think they just need a couple more months, you can adjust the loan or make them a new loan to cover those first few months’ payments, etc., right? Since both parties stand to lose if it blows up completely, unless it’d be worth more to sell to somebody else? These are also not individual homeowners’ “investments.” The risk is coordinated, and it’s big, but we know that already, right? Yes we know the revenue, yes it’s different from the costs of paying down their capital investments, yes both are reported on the financial disclosures. How is the claim here any stronger than “all this depends on them actually being able to sell this crap once they get it built”? [0] https://substackcdn.com/image/fetch/$s_!-2DS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F19f0fdfd-6e2f-4f86-8bf2-6a8c32b58781_2038x1218.png https://substackcdn.com/image/fetch/$s_!-2DS!,f_auto,q_auto:...
- hungryhobbit 1mo ago
  Yeah it's funny: I'm pretty sure (based on what he writes about) that the author didn't use AI to write it. Still ... he's more verbose than Claude itself .. and Claude is very, very verbose!
atleastoptimal 1mo ago
Someone who only knows finance trying to apply that logic to the singularity. There is no comparison. AI does not obey money, money obeys AI, or rather, the operating force of commodified intelligence will not just evaporate when inconvenient obligations for payment come around. Also it seems evident the article is largely AI written, which makes it even funnier.
- deleted 1mo ago
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qoez 1mo ago
I always imagined they're doing that psychological experiment where they randomly give a rat food when they press a button. They get way more addicted than when it's a consistent amount. They can't get away with the optics of facebook-level gamification but this is some sort of loop hole.
yoggies_bro 1mo ago
Became obvious it was AI authored as I read, classic AI overstatement of parallels, lots of jargony words, its not X it is Y.
- mizzao 1mo ago
  If someone takes a bunch of good ideas and turns them into an essay with the help of AI, does that make the ideas inherently untrue?
spwa4 1mo ago
TLDR: what determines if we'll have an AI crash is whether the Anthropic and OpenAI IPOs provide enough money to cover compute for these companies. Without IPOs, these companies cannot survive 2026 and this will have drastic consequences for the hyperscalers, datacenter companies, energy companies, ... ie. the "AI crash". Anthropic: $100B, OpenAI: $150B (that's not market cap, that's what they have to raise with the shares they issue in their IPO). If they make this money, the AI crash is delayed, at least to 2029. To give a point of comparison: SpaceX got about 85B in cash to spend from its IPO. (This is assuming the datacenters ordered actually get built between now and 2030 or so. If not crash is guaranteed)
- arealaccount 26d ago
  There's always the option of a bailout
aaroninsf 1mo ago
Similar looking charts do not make AI companies into subprime loans.
nixonaddiction 26d ago
i think financially, frontier labs are going to crash. this is purely from a financial standpoint. the question is when, this article posits 2027/28. i need to better verify the claim. (its easy to be right, its hard to time being right.) however, when frontier labs become financially insolvent (and they will eventually, the question is when) i think smaller local models will end up taking over. and i think there is a bet to be placed on smaller models here. the demand for ai isnt going away. peoples workflows would be crushed without it. the question actually becomes, who either purchases frontier labs, or what cheaper alternative replaces frontier labs?

95 points by gtzi 1mo ago

wow excellent piece. Gary Marcus had a long post about this article on his substack. scary stuff "And look at what this implies about OpenAI’s valuation as it moves toward an IPO: OpenAI’s equity - valued north of $850 billion - is functionally the junior tranche of a capital structure whose senior claims, the take-or-pay compute obligations, exceed any revenue path management itself has articulated. On those numbers, the equity is effectively underwater, and the market has not priced it that way because it still treats those obligations as service agreements rather than what they are economically: debt. Even if OpenAI can meet those obligations, OpenAI’s unaudited financial statements - as of March 31, 2026 - disclose $665 billion in non-cancellable compute commitments (management’s more recent plan runs to $750 billion). These commitments are take-or-pay in structure - which, as established above, is debt. Carry the net present value of those obligations as senior debt - roughly $450–500 billion, the same methodology rating agencies have used for decades to capitalize take-or-pay contracts as debt - and a company the market prices as debt-free carries a senior claim worth more than half its entire equity value." and the 2008 analog "Millions of subprime borrowers were, at that moment, paying the low introductory rate on a two-year adjustable rate mortgage - the 2/28 ARM. A low fixed-rate for two years, then the rate reset to a payment 30% to 50% higher. During those first two years the loan performed beautifully: the borrower paid, the servicer collected, and the bond paid its coupon. Nothing looked wrong because the whole complex - housing, mortgages, securitization - was sitting inside the teaser period. The AI boom has rebuilt this exact structure, and the market is once again underwriting the teaser. It has a reset wall of its own - a schedule of dated, contractual, non-negotiable payment shocks - hiding inside the trillions of dollars of compute contracts signed by OpenAI and other frontier labs since 2024."

ameliaquining 1mo ago
Marcus believes that the underlying technology doesn't work. If that's true, then of course the whole thing will crash as soon as everyone realizes this. This article is mostly making a different argument (though it contradicts itself in some places), which is that even if the underlying technology does work, and is ultimately going to create quadrillions of dollars of value and transform society, if it takes more than another 1–2 years for that to happen, then there'll still be a crash, because that's when the data center construction bills come due and the labs (especially OpenAI) don't yet have the money to pay them. It argues primarily against a hypothetical optimist who believes that everything is fine because the cash flow numbers currently work out, on the grounds that this hypothetical optimist hasn't realized that the labs' recurring expenses are scheduled to spike in 1–2 years when the data centers come online and the labs have to start paying for them. It also spends a lot of words comparing the situation to the 2008 financial crisis, because that's everyone's favorite morality tale. I am not sure that anyone is actually making this mistake (i.e., trying to predict the future by looking at labs' present cash flows). The better counterargument is what Matt Levine used to call "Netflix Theory": if the large capital investors who own stakes in the labs still believe in their valuations (which they should, if the technology works and the quadrillions are coming, which we're assuming here for the sake of argument), then they will be very highly motivated not to let their investment be seized by the labs' creditors. So the labs will not have too much difficulty raising or borrowing enough money to pay the bills.
- michaelchisari 1mo ago
  There's a third possibility between works and doesn't work: Works but not quite good enough to make the case against commoditization. If open source or on-device AI gets good enough for 80% of consumers, then this stops being a consumer product and the only real market is people who need the high-end models. If those models are slow and expensive, certain tasks like scientific and math research can tolerate slowness, but they run up against the costs. If they're expensive, the tech industry can afford them but runs up against their inefficiencies. We need to talk about how well these improving models work in multiple dimensions: Accuracy, performance and cost. All three have to improve considerably before the debate dies down.
  - ameliaquining 1mo ago
    Yes, if the tech works but in a way that doesn't let the labs command premium prices for inference, then that also means a crash. But that's a fundamentals-based argument like Marcus's (despite being based in economics rather than ML science), so distinct from the one the article's mostly making.
- dumberquestions 1mo ago
  Yes, the labs will be fine as long as investors believe in them, and they overwhelmingly do, trying to draw comparisons based on traditional market wisdom will fail because none of this is precedented.
- w10-1 1mo ago
  > large capital investors [...] will be very highly motivated not to let their investment be seized [...] So the labs will not have too much difficulty raising or borrowing enough money to pay the bills So: sunk costs of large investors mean they'd be willing to pay high interest costs? Thus small investors can rely on this dynamic, shielded by big ones? Remember, the large investors got large in a near-zero interest rate environment (where exact timing doesn't matter as much), but those days are not coming back. Soon margins will matter most, and while NVDA and Apple have the internal discipline for that, OpenAI et al do not.

NDlurker 1mo ago

So, start selling risky assets for bonds and wait for the crash to buy back in to stocks?

CBLT 1mo ago
If you can actually time the market, sure. I cannot, so I don't pull money out of my stock indexes; I just send a larger fraction of my new investments into bonds.
- NDlurker 1mo ago
  That's a smarter idea. I've tried timing the market in the past and have been very wrong.
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lesuorac 1mo ago
Who are you going to sell the bonds to? People only want cash during the crash so the value of everything goes down. It doesn't matter if you bond has a known 8% yield when held to maturity; the market can't hold it to maturity so its current value drops. Like go find 2008 in the graph of BND (Vanguard Bond ETF) vs SPY (SNP500) [1]. Let me know how you'd know when to sell your bonds for stocks. [1]: https://www.google.com/finance/beta/quote/SPY:NYSEARCA?keymoments=false&comparison=BND%3ANASDAQ&type=line&window=MAX https://www.google.com/finance/beta/quote/SPY:NYSEARCA?keymo...

firmretention 1mo ago

Sloppity slop.

NDlurker 1mo ago
That was the impression I got too, so I just skimmed it

awongh 1mo ago

I get the structural comparison they are trying to make. But mortgages are not a frontier AI lab. They try to draw a comparison to the valuation of the real estate and the valuation of the hyper scalers in the markets. I would argue that the demand and valuation of a house is less elastic than AI. While a house’s value may continue to appreciate in the market there is an upper bound for the price of a house set by people’s income. We don’t know yet what the value of AI is. The underlying product, the model keeps improving and therefore increases its value. A house is still fundamentally a house a year later and doesn’t intrinsically appreciate in value. From gpt-3 to gpt-5.5 there’s been a massive change in the underlying value of the product and company in a way that simply doesn’t happen with a house. That’s where the analogy breaks down.

tyromaniac 1mo ago
I think its well corrected by the increase in competition that meets or exceeds the quality. The house may have gotten nicer but now you are selling a single room
vmg12 1mo ago
The dynamics are interesting. If all businesses get productivity increases from AI, the margins they could have claimed are competed away. The model companies also have their margins competed away because of open models. The only companies that have a moat are the ones with capital as a barrier to entry and even then there is cut throat competition. We might end up with massive consumer surplus from AI because no business will be able to raise prices due to competition. This is why it's so important that we don't allow for regulatory capture in this space.
- plasticchris 1mo ago
  Yes and much like the technological leaps of the past, everyone’s standard of living goes up.
rootusrootus 1mo ago
The value is going up, but the pricing is going down, right? At least at the token level. So the usage would have to go up dramatically to compensate for that. > there is an upper bound for the price of a house set by people’s income Isn't that essentially true here too? The money to pay these expected future AI prices is coming from someone's income. Sure, the pie will be growing at the same time, but enough?

alexpotato 1mo ago

> Every ARM reset was known, dated, and contractually inevitable from the moment of origination. Aggregate those reset schedules and you get the most damning exhibit of the era: the reset wall. One of my distinct memories from this era is watching CNBC where a guest said exactly the same thing. As the interview went on, he became more animated and used stronger language to the point of: "You don't get it, THEY ARE GOING TO BE PICKING PEOPLE OFF THE FLOOR when these ARM rates reset" I would guess this was right about 2006 which lines up with the article.

Espressosaurus 1mo ago

Interesting piece, I just wish the author had presented the data and their thesis instead of making Claude vomit out 20 pages of trash around it.

johnfn 1mo ago
I really want to get in the mindset of people who are like "AI is totally going to fail! Haha! Now let me just use AI to write a piece about it..."
- Espressosaurus 1mo ago
  It's not inconsistent if you think of it as the finances falling apart regardless of how useful the tool is.
  - johnfn 1mo ago
    The article claims that the finances fall apart because OpenAI won't hit the growth it wants. It's an interesting thing to say when using their product to write 100% of the article.
    - owebmaster 1mo ago
      Using the free version reinforces the point.
  - throwawayqqq11 1mo ago
    Bubble != AI.
Sharlin 1mo ago
Yeah, the signal-to-noise ratio was way too low to keep reading for long.
nnevatie 1mo ago
Indeed - obvious AI slop with the annoying language all of the place.

harshaw 1mo ago

Some other commentators said this was AI slop. I don't have enough expertise to say if it really is, but it sure has the "claudish" cadence of AI generated text that makes it hard to take it seriously. The authoritative and strong statements, the use of phrasing with colons and dashes, the use of bold, etc.

Espressosaurus 1mo ago
The claims and data are interesting (perhaps overstated in the usual Claude way) but it's about 20x more prose than is actually justified.
ameliaquining 1mo ago
Pangram confirms: https://www.pangram.com/history/9ccdf6ed-5016-4325-b1ac-b3b0150a6784 https://www.pangram.com/history/9ccdf6ed-5016-4325-b1ac-b3b0... I find it amusing that even the AI skeptic articles are written with AI these days.
georgemcbay 1mo ago
> Some other commentators said this was AI slop. To me it read like a combination of human written and AI slop, as if the author had Claude write it and then rewrote portions of it, or the author wrote an initial version and told Claude to "punch it up, without rewriting the whole thing entirely". Regardless of who or what actually wrote it the piece was much longer than it needed to be (though I do think it highlights a very real problem).

Synaesthesia 1mo ago

IMO there is overinvestment in compute and this will turn out to be a bubble. But all of the money was anyway just lying around doing nothing. An enormous amount of capital has been building since the 80's thanks to corporate profits. A small sector of the population is so rich they don't know what to do with their capital.

tschellenbach 1mo ago

This post is just AI slop. The details of these contracts aren't disclosed as far as I know. You need to understand the contracts, the acceleration of demand, how the various inputs into supply scale (energy, chips, data centers) etc to say something sensible about this.

bradfa 1mo ago

It would be nice if the article cited the actual contracts the labs have signed so that others could also read them and draw their own conclusions (maybe it does and I got tired of the slop-like writing style too early?). Are the contracts actually take-or-pay-style? What are the terms? What are the amounts of compute and money involved for each future time period? What happens if the datacenter costs spiral upwards? What happens to the datacenter investment if the buyer goes bankrupt, goes public, or gets acquired (potentially by the datacenter owner)? I personally think the datacenter build-outs are going to generally be a big swing and a miss. The problem 1-2 years ago was making models good enough to be useful for a variety of tasks. Now we have that. The next problem is making the models efficient enough to run a profitable business. Recent Chinese lab model releases (because they're already constrained on compute resources) and OpenAI price cuts on Luna seem to indicate that this transition to chasing efficiency has already started.

krona 1mo ago
> The next problem is making the models efficient enough to run a profitable business. In that world, what does Oracle do with a bunch of data centres which 1. It needs to pay for and 2. nobody needs. This is what the article is about: building supply far in advance of demand.
- bradfa 1mo ago
  I don't know, but unless that contract is public, not many people know. I get the impression Oracle got a little bit of market pushback on the risk, as theirs seems to be one of the largest.
  - krona 1mo ago
    What contract? It's mostly corporate debt. Seems pretty plain and simple to me. The contracts I guess you're talking about are compute obligations which frontier labs have. I don't need to know what those obligations are to know what happens to Oracle.

Havoc 1mo ago

It’s an interesting comparison. The housing market is linked to the value of the house though which is subject to crashes in value without a corresponding drop in demand. With AI it comes down to whether the large companies orders and building of datacenters aligns with token demand. There is years worth of lag there so they kinda have to front load this by necessity

hughw 1mo ago

"The hidden mechanics reveals how the AI boom breaks, and when." I stopped there. I just resist reading slop.

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alwa 1mo ago

This feels like Claude thought to me—assertions and comparisons that look impressive on the surface, but kind of make me scratch my head the more I think about them. I think what made me throw in the towel was “Figure 2 — Two Instruments, One Shape” [0]. That chart comparing when contracts reset. Weirdly consistent norms! [looks at the sourcing] Oh… it’s… not from data at all… it’s just notional… Is there anything here other than “the people financing the factory are betting that it’ll be able to sell what it makes once it’s built”? I mean… isn’t “an instrument that splits time in two” kind of… what capital financing is? And this risk is what earns investors their interest, and the rest of the financial system involves different ways for people to calibrate their bets on the risk materializing? Including derivative instruments that allow investors to smear out the point-in-time “cliffs” this writer is concerned about? If you think the revenue is never going to come, you can bet on that now. Or go into the distressed datacenter acquisition business to prepare! Conversely if Payment Day comes and you think they just need a couple more months, you can adjust the loan or make them a new loan to cover those first few months’ payments, etc., right? Since both parties stand to lose if it blows up completely, unless it’d be worth more to sell to somebody else? These are also not individual homeowners’ “investments.” The risk is coordinated, and it’s big, but we know that already, right? Yes we know the revenue, yes it’s different from the costs of paying down their capital investments, yes both are reported on the financial disclosures. How is the claim here any stronger than “all this depends on them actually being able to sell this crap once they get it built”? [0] https://substackcdn.com/image/fetch/$s_!-2DS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F19f0fdfd-6e2f-4f86-8bf2-6a8c32b58781_2038x1218.png https://substackcdn.com/image/fetch/$s_!-2DS!,f_auto,q_auto:...

hungryhobbit 1mo ago
Yeah it's funny: I'm pretty sure (based on what he writes about) that the author didn't use AI to write it. Still ... he's more verbose than Claude itself .. and Claude is very, very verbose!

atleastoptimal 1mo ago

Someone who only knows finance trying to apply that logic to the singularity. There is no comparison. AI does not obey money, money obeys AI, or rather, the operating force of commodified intelligence will not just evaporate when inconvenient obligations for payment come around. Also it seems evident the article is largely AI written, which makes it even funnier.

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qoez 1mo ago

I always imagined they're doing that psychological experiment where they randomly give a rat food when they press a button. They get way more addicted than when it's a consistent amount. They can't get away with the optics of facebook-level gamification but this is some sort of loop hole.

yoggies_bro 1mo ago

Became obvious it was AI authored as I read, classic AI overstatement of parallels, lots of jargony words, its not X it is Y.

mizzao 1mo ago
If someone takes a bunch of good ideas and turns them into an essay with the help of AI, does that make the ideas inherently untrue?

spwa4 1mo ago

TLDR: what determines if we'll have an AI crash is whether the Anthropic and OpenAI IPOs provide enough money to cover compute for these companies. Without IPOs, these companies cannot survive 2026 and this will have drastic consequences for the hyperscalers, datacenter companies, energy companies, ... ie. the "AI crash". Anthropic: $100B, OpenAI: $150B (that's not market cap, that's what they have to raise with the shares they issue in their IPO). If they make this money, the AI crash is delayed, at least to 2029. To give a point of comparison: SpaceX got about 85B in cash to spend from its IPO. (This is assuming the datacenters ordered actually get built between now and 2030 or so. If not crash is guaranteed)

arealaccount 26d ago
There's always the option of a bailout

aaroninsf 1mo ago

Similar looking charts do not make AI companies into subprime loans.

nixonaddiction 26d ago

i think financially, frontier labs are going to crash. this is purely from a financial standpoint. the question is when, this article posits 2027/28. i need to better verify the claim. (its easy to be right, its hard to time being right.) however, when frontier labs become financially insolvent (and they will eventually, the question is when) i think smaller local models will end up taking over. and i think there is a bet to be placed on smaller models here. the demand for ai isnt going away. peoples workflows would be crushed without it. the question actually becomes, who either purchases frontier labs, or what cheaper alternative replaces frontier labs?