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- Hacker News
- So, start selling risky assets for bonds and wait for the crash to buy back in to stocks?by NDlurker
- 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?keymo...
by lesuorac - 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.by CBLT
- 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.
by Synaesthesia - 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
by Havoc - 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)
by spwa4 - There's always the option of a bailoutby arealaccount
- 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?
- 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.by qoez
- Became obvious it was AI authored as I read, classic AI overstatement of parallels, lots of jargony words, its not X it is Y.by yoggies_bro
- 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?by mizzao
- 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:...
by alwa - 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!
by hungryhobbit - 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."
by jumanji493 - 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.
- 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.
- Indeed - obvious AI slop with the annoying language all of the place.by nnevatie
- Really? Did you read the article? I did. It read as quirky human to me.by doug_durham
- I strongly recommend summarizing the article with Claude.by olalonde
- What exactly do you/others feel read AI about it? I spend an inordinate amount of time with AI and this did trigger my ai-radar, something I’m otherwise very sensitive too. I’m genuinely curious what phrases/words people reacted to!by lightbulbish
- Yeah, the signal-to-noise ratio was way too low to keep reading for long.by Sharlin
- 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..."by johnfn
- 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.
by awongh - 1. The massive amounts of GPUs being purchased have far shorter valuable lifespans than a house.
2. A model's value seems to be depreciating at an unbelievable rate. The most expensive top SOTA models (GPT-5, Opus 4.1) a year ago are far less capable than GPT-5.6 Luna. Compared to when those models were new, Luna costs 85% less than GPT-5 and 98% less than Opus 4.1. That's good for us consumers, but if a lab stumbles for 6-12 months, a lot of their value goes away. Especially with open models only months behind the SOTA closed models.
by pseudosavant - I mostly agree but at the same time the change in underlying value from opus4.6 to Fable has not been as dramatic, and I'm not really sure if a "better Fable" is something most people even need. To the point where a faster and more cost effective model is preferable
Many would argue that opus5 is a regression in value despite what benchmarks say.
by dimitri-vs - > We don’t know yet what the value of AI is. The underlying product, the model keeps improving and therefore increases its value.
i dont know. i think we already know how far these things go. Buying tons of data on mercor to slightly improve one domain has not really even displaced ppl in that domain. i really cant tell the difference between opus 4.8 and 5
very few domains in the world are closed like math.
by dominotw - 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?
by rootusrootus - > The underlying product, the model keeps improving and therefore increases its value.
I think this is true, but a customer's willingness to spend is based on _perceieved_ value, not actual value. For many companies, the _perceived_ value of AI has been trending down as internal projects fail and cost skyrocket, even as models on paper improve.
by Octoth0rpe - 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.
by vmg12 - "The underlying product, the model keeps improving and therefore increases its value."
That's not exactly true. Yes, the fundamental capabilities of the models do seem to be growing dramatically, but the economic value of any particular model may be steady, or even falling, because of commoditization, or other issues external to the model itself.
Without a moat, improvement in model capability does not necessarily translate into economic value--and the labs need economic value to pay their obligations.
by compiler-guy