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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 e

by awongh 21d 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 21d 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 21d 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 21d ago
  Yes and much like the technological leaps of the past, everyone’s standard of living goes up.
rootusrootus 21d 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?
- chermi 20d ago
  Individuals and families buy houses(ideally). Entities like corporations buy work, often intelligent work. If they can crank up outputs and profits via more intelligent work done by models, I think the ceiling is global demand for the entity's product. Which is still a bound, and ultimately set by individual consumers. The question is whether the consumers will have the income to spend. So I kind of agree in the end I guess.
- rkangel 20d ago
  The performance of the recent open weight models is making it harder for the bug players to justify their pricing.
compiler-guy 21d ago
"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.
- PaulHoule 21d ago
  The economic value may be real but the profits may not be. One thing that's clear is that there is no leading vendor in this space and there may never be one. To some extent premium models can charge a premium price but it's going to be a competitive market and the likes of Anthropic and OpenAI will not be able to sustain monopoly pricing.
  - slg 21d ago
    The AI debate has often been flattened into "Do you believe in the long term viability of the tech?" when there is also another question that needs to be asked in "Do you believe in the long term viability of these companies' business models?" It's a lot easier to believe the former than the latter. It's entirely possible for this tech to be humanity altering in the long term while we are also in a huge bubble that could pop at any moment. In that way the housing analogy is apt. The utility of the houses themselves didn't change, the problem was purely with financial markets until eventually those markets made it everyone's problem.
    - user43928 21d ago
      As of now the compute is fully utilized, progress is rapid, and both OpenAI's and Anthropic's revenue is growing fast. This could change, but there is no sign of it yet. No one knows whether other companies are going to catch up, with what compute, or if OpenAI or Anthropic will be able to conquer robotics or medicine.
    - 20d ago
Octoth0rpe 21d ago
> 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.
- jonwinstanley 21d ago
  And the Open Weight models keep improving. For many tasks, you don’t need a frontier model.
krona 21d ago
GPUs depreciate at a far, far faster rate than houses do. And then they need to be replaced. Who's paying for that? OpenAI and Anthropic don't even have positive free cash flow.
pseudosavant 21d ago
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.
- XenophileJKO 20d ago
  I feel like the idea that GPUs wear out in 3 years is as far as I can tell, generally unfounded. The GPU build out will keep pumping tokens until the cost to replace is less that the cost to maintain. It is effectively sunk cost.
  - pseudosavant 20d ago
    Even if it is 5 or 7 years, houses last decades. Even cars last longer than GPUs. GPUs are a highly depreciating asset. They'll last longer than 3 years, but might not be very cost effective (tokens per Wh) compared to the latest AI accelerators that are available. I wonder if it will be that the U.S. (and allied countries) will be using the latest 1-2 generations of AI accelerators, and if the 3-5+ year old stuff will be sold to Chinese datacenters since that will still be the most powerful tech we'll be allowed to export to them?
whack 20d ago
Funny how you're echoing exactly what the author said in the article > This is not precisely 2008. GPUs are not houses; take-or-pay contracts are not mortgage-backed securities; OpenAI is not a subprime borrower in Stockton, and artificial intelligence may well be the most consequential technology of the century, which is more than anyone could ever say for a McMansion in the Inland Empire. > The bear case in this piece is not that artificial intelligence will fail, or that the demand is fake, or that the technology disappoints. It is narrower: that the financing structure can break before the demand arrives, because the obligations are fixed and front-loaded in commencement while the revenue is variable and back-loaded in adoption - and a fixed obligation meeting a lagging revenue stream is a solvency problem regardless of how transformative the underlying technology turns out to be. > The industry will spend the next eighteen months debating whether artificial intelligence is a bubble, which is the wrong question, asked at the wrong layer. The technology is real; so were the houses. The question is narrower: what happens when instruments underwritten at the teaser meet their reset schedule, and who is holding the paper when the obligations cannot be met as written Ie, if you spent $10M buying a house, it doesn't matter if it will be worth $100M in the future. If you're unable to make your mortgage payments in the interim, you're going to lose everything
- jumanji493 20d ago
  thanks this is a helpful way of summarizing it
doug_durham 20d ago
I'm still paying OpenAI $20/month for a product that has gotten massively more valuable. That's the problem. They aren't getting any more money from me for a product which is much more valuable.
dominotw 20d ago
> 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.
analognoise 20d ago
You pointed out correctly that house prices are bounded by incomes, then immediately made the same mistake with AI - someone has to want to pay for this stuff. It also has to compete against free models, which are not only almost as good, but they pull ahead sometimes. Saying “the product increased in value” is only true if someone buys it!
dimitri-vs 20d ago
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 awongh 21d ago

tyromaniac 21d 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 21d 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 21d ago
Yes and much like the technological leaps of the past, everyone’s standard of living goes up.

rootusrootus 21d 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?

chermi 20d ago
Individuals and families buy houses(ideally). Entities like corporations buy work, often intelligent work. If they can crank up outputs and profits via more intelligent work done by models, I think the ceiling is global demand for the entity's product. Which is still a bound, and ultimately set by individual consumers. The question is whether the consumers will have the income to spend. So I kind of agree in the end I guess.
rkangel 20d ago
The performance of the recent open weight models is making it harder for the bug players to justify their pricing.

compiler-guy 21d ago

"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.

PaulHoule 21d ago
The economic value may be real but the profits may not be. One thing that's clear is that there is no leading vendor in this space and there may never be one. To some extent premium models can charge a premium price but it's going to be a competitive market and the likes of Anthropic and OpenAI will not be able to sustain monopoly pricing.
- slg 21d ago
  The AI debate has often been flattened into "Do you believe in the long term viability of the tech?" when there is also another question that needs to be asked in "Do you believe in the long term viability of these companies' business models?" It's a lot easier to believe the former than the latter. It's entirely possible for this tech to be humanity altering in the long term while we are also in a huge bubble that could pop at any moment. In that way the housing analogy is apt. The utility of the houses themselves didn't change, the problem was purely with financial markets until eventually those markets made it everyone's problem.
  - user43928 21d ago
    As of now the compute is fully utilized, progress is rapid, and both OpenAI's and Anthropic's revenue is growing fast. This could change, but there is no sign of it yet. No one knows whether other companies are going to catch up, with what compute, or if OpenAI or Anthropic will be able to conquer robotics or medicine.
  - 20d ago

Octoth0rpe 21d ago

> 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.

jonwinstanley 21d ago
And the Open Weight models keep improving. For many tasks, you don’t need a frontier model.

krona 21d ago

GPUs depreciate at a far, far faster rate than houses do. And then they need to be replaced. Who's paying for that? OpenAI and Anthropic don't even have positive free cash flow.

pseudosavant 21d ago

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.

XenophileJKO 20d ago
I feel like the idea that GPUs wear out in 3 years is as far as I can tell, generally unfounded. The GPU build out will keep pumping tokens until the cost to replace is less that the cost to maintain. It is effectively sunk cost.
- pseudosavant 20d ago
  Even if it is 5 or 7 years, houses last decades. Even cars last longer than GPUs. GPUs are a highly depreciating asset. They'll last longer than 3 years, but might not be very cost effective (tokens per Wh) compared to the latest AI accelerators that are available. I wonder if it will be that the U.S. (and allied countries) will be using the latest 1-2 generations of AI accelerators, and if the 3-5+ year old stuff will be sold to Chinese datacenters since that will still be the most powerful tech we'll be allowed to export to them?

whack 20d ago

Funny how you're echoing exactly what the author said in the article > This is not precisely 2008. GPUs are not houses; take-or-pay contracts are not mortgage-backed securities; OpenAI is not a subprime borrower in Stockton, and artificial intelligence may well be the most consequential technology of the century, which is more than anyone could ever say for a McMansion in the Inland Empire. > The bear case in this piece is not that artificial intelligence will fail, or that the demand is fake, or that the technology disappoints. It is narrower: that the financing structure can break before the demand arrives, because the obligations are fixed and front-loaded in commencement while the revenue is variable and back-loaded in adoption - and a fixed obligation meeting a lagging revenue stream is a solvency problem regardless of how transformative the underlying technology turns out to be. > The industry will spend the next eighteen months debating whether artificial intelligence is a bubble, which is the wrong question, asked at the wrong layer. The technology is real; so were the houses. The question is narrower: what happens when instruments underwritten at the teaser meet their reset schedule, and who is holding the paper when the obligations cannot be met as written Ie, if you spent $10M buying a house, it doesn't matter if it will be worth $100M in the future. If you're unable to make your mortgage payments in the interim, you're going to lose everything

jumanji493 20d ago
thanks this is a helpful way of summarizing it

doug_durham 20d ago

I'm still paying OpenAI $20/month for a product that has gotten massively more valuable. That's the problem. They aren't getting any more money from me for a product which is much more valuable.

dominotw 20d ago

> 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.

analognoise 20d ago

You pointed out correctly that house prices are bounded by incomes, then immediately made the same mistake with AI - someone has to want to pay for this stuff. It also has to compete against free models, which are not only almost as good, but they pull ahead sometimes. Saying “the product increased in value” is only true if someone buys it!

dimitri-vs 20d ago

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.