A while ago I was thinking, “Gee, AI is so complicated, how can I keep up with the landscape?”
After reading these articles go by so often, it feels like what I actually can’t keep up with is the bond market. To paraphrase Trotsky, you may not be interested in the bond market, but the bond market is interested in you. I want to be able to read the signals at the bottom of this article, and divine some kind of prediction that can guide me… I don’t know, to choose whether I should buy a house or change the investment strategy in my retirement fund or something. But I’m just seeing all these signals go by, waiting for the story to be written, which only happens when the dust settles.
I guess I’ll go back to not understanding AI, instead of not understanding the bond market.
As a retail investor, you should buy an index fund and then forget about it.
By the time you have read this article, the professionals and their computers will have digested that material a thousand times over and have priced it in.
To be more precise: by the lowest cost most diversified index fund you can buy and then hold it. If you want to spend some smarts to get a better return: look at how to minimise taxes and fees.
Don’t forget there is a constant pressure for everyone to have an opinion on how this is going to end while hoping it ends tomorrow so they can be vindicated. The dotcom bust took a decade to grow and collapse. I think it is too early to make predictions with AI. I mean the sentiment here is either it will dry up the world and kill us all or transcend humanity, there’s no gray area. I don’t want to fall into the emotional sieve that seems to drive everything.
That's the financial stakes here. That's why it's all or nothing. You're spending on a level that is only justified by the bonafide machine god being ushered into existence, not productivity or coding tools (and on relatively short time horizon). So if this doesn't change the near term trajectory of humanity to a parabolic move upward there is going to be a lot of economic pain. It's not just the spending, it's that the expectations for the returns to justify them are in a relatively short period of time.
> if this doesn't change the near term trajectory of humanity to a parabolic move upward there is going to be a lot of economic pain
"trajectory of humanity to a parabolic move upward" is poorly defined here. Whether we are headed to a machine god ruled scenario or "just" incredibly powerful productivity tools, there will be a lot of economic pain for some (most) and a lot of economic gain for a few.
I've yet to a see an LLM/agent-based business plan in where scaling with an order fewer workers than before LLMs is not a central part of the value proposition.
such a business plan has not yet created economic value, being able to roll out features at rocket speed is not a huge determinant of a startup's success.
I think these large numbers are casually thrown about, but the real meaning is mind boggling. 1 trillion dollars is the entire US defense budget - aircraft carriers, nuclear submarines, health care, salaries, stealth fighters ect. The hidden AI debt alone is more than that https://asia.nikkei.com/business/technology/five-us-tech-gia... just for five tech giants (not to mention all the other smaller players like neoclouds)
I mean that's so far, it continues to grow exponentially larger with each quarter. The debt issuance for the first half looks to be crowding out US treasuries in the bond market - https://www.bloomberg.com/news/newsletters/2026-07-23/ai-deb... - that's an extremely large amount of debt. And it's still getting larger and larger each quarter.
1T is big in the absolute sense, but that's simply the scale these big tech companies operate at. Go back to 2024 or 2025 and you'll see as a group they are making a net income of $400B+. The scale at which these companies do anything is just staggering.
What’s weird is how emotional people get on this. I told publicly (because I was asked, not out of an obligation to have an opinion), that the prices we pay for LLMs are likely to go up because that’s what happens when the ratio of operational assets to foreign capital drops due to the capital having been turned into heat rather than operational assets. The grief I got from people, dear Lord…
I think that opinion is as reasonable as any. I feel compelled to argue against it (I even thought out the arguments in my head!) but my compulsion to have an opinion on HN is a disease, and you made a point of saying that you gave the opinion because asked.
I feel obliged to step in here to say there is a grey area where these are useful tools for some applications but not on the path to AGI.
Unfortunately the hype machine has far outstripped their capabilities so far, and the amount of money spent doesn’t look like being recouped, so somebody is going to lose money, as people lost money on the overpriced spacex ipo (overpriced because of AI).
the core issue is that you can't simply will into a existence a thing that is never going to be.
Im very convinced there's a cult-like level of psychosis in silicon valley (except in Apple) where LLM's must begin displacing labour. It simply is not happening. And the longer this continues, the crazier and unhinged they will get.
I was able to create a custom index based on the top 500 that I stripped the big AI stocks from (shovels too). Then I added decent chunks of international, small cap, and treasury ETFs to it.
I have no illusions that I can time a bubble, but I'm hopeful I'm at least partially shielded, and most importantly I feel better about ignoring wall street again.
Instead of starting with the top 500 American stocks, and then adding international and small caps, you can start with a global all-market stock index--and then remove AI from that.
How can people in Hacker News still doubt AI's benefit when they are seeing in front of their eyes every technical profession getting disrupted to oblivion in the last year. Just ask basically any software engineer how much their profession has changed over the last 12 months
Obviously there is risk, but can't we really extrapolate the AI gains forward and just see how big it's ahead to become?
> How can people in Hacker News still doubt AI's benefit
Because what many of us are seeing is meaningless “productivity” improvements.
If at the end of the day you don’t have more users paying for your product or the same users and paying more, then what’s the point of being more productive?
How can people not trust in anecdotes and vibes while avoiding studies, do you mean?
Isn't that the point here? That everyone thinks massive disruption is happening and everyone is 100xing their productivity, but it's not actually showing up in the numbers anywhere?
Lenders are doubting their return. People's benefits have nothing to do with it. The benefits would go in a minute, if doing so yielded a better return.
Revolutionary technology + massive adoption ≠ good investment
Investors have poured money into a bottomless pit, attracted by the growth and glamour of the industry. The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
Commodity Product, no switching costs. Infinite competition
The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
The industrialisation essentially socializes the cost across a lot more people though, so even though it doesn't make a profit it does mean people can have air travel without it costing millions per flight for the few people who can afford it. Essentially the economies of scale from having lots of flights isn't enough to make it profitable but they are enough to make it affordable.
There's no spare money to extract from the airline industry but it's still very useful. The same could be true for AI in the long term.
Sometimes the goal of an industry is to exist rather than to make a profit, because the benefit to society is more important than profit. People don't like that though so they do a bit of creative accounting or head-in-the-sand denial around it.
> There's no spare money to extract from the airline industry but it's still very useful. The same could be true for AI in the long term.
Of course it could, let’s start with making the models open weight and entirely open source. Fully publicly owned and not shaped to maximise profits for the shareholders.
Oh wait, Scam Altman entered the chat and turned a non-profit lab into the next biggest IPO vehicle the world has ever seen.
OpenAI launched as a nonprofit research institution. Its announcement explicitly said it wanted to pursue AI “unconstrained by a need to generate financial return,” produce value for everyone rather than shareholders, publish research and share patents broadly.
in the case of airplanes the only thing thats the private market is the planes and the ticket, the entire system of airports, safety, navigation is state subsidized and when the market fails it gets bailed out. the oil is subsidized by constant warfare. it's just an illusion for reganomics so a few rich ppl can make a buck off of a public utility.
How does constant warfare subsidise oil? In case you haven't noticed: both the latest US-vs-Iran war and Russia-vs-Ukraine war have made oil and gas a lot more expensive than the peaceful counterfactual.
It isn't a commodity product in my opinion. Far from it. I think it will ultimately be a monopoly or duopoly for SOTA. The mid to low end is commodity, yes. But SOTA models are not commodities.
The number of competitors for SOTA drops by a few every year. The winners make more money, get more revenue, buy more compute, train better model with compute, buy best talent, and the cycle goes.
I think it's easier to fall behind and never catch back up than people think. One disastrous training run can leave a lab months to a year behind. For example, Meta's disastrous LLAMA 4 models. Meta is lucky to have their ads business as a funding source. However, Anthropic's revenue is growing so fast, that ability to use ads as a funding source to stay in the race may not last much longer for Meta.
To me, SOTA LLM training is very much like new chip fab nodes. One disastrous node can put you behind for many years or forever. The cost to build the next chip node doubles every every 4 years (Rock's law). The cost to train the next SOTA model likely has some similar power law which means over time, it's too costly for losers to keep up. The only reason TSMC isn't a defacto monopoly for advanced chip nodes is strictly due to geopolitics.
Mate the vast majority of firms dont care about this SOTA crap.
They can barely get any efficiency gains beyond the productivity of software engineers. And even that is not really translating into financial performance.
All things equal, let's say your SaaS startup uses GPT 5.0 (release 10 months ago) and my business uses Fable 5. We have the same business goals, same talent level, same strategies. I think the chance of my business winning against yours is higher.
It's easy to agree to that, but you're disregarding that the resources you spend on the stronger model could be allocated elsewhere. Conversely, you're assuming that spending more on AI will always yield better results and be worth it, compared to spending the money on other things.
This might actually still hold true now, or or at least many actors in the market behave that way. But I'm not so sure there isn't a cliff to that effect. At some point, if SOTA models remain expensive, it'll turn into a market advantage to figure out how to get things done without depending on the most expensive tooling available.
Similar scenario, different phrasing: if your company relies on overqualified workers to deliver 100% quality, the market may still decide that it's fine to go with 90% quality for 50% the price.
@orwin has claimed that SOTA LLMs have already hit that diminishing return where spending more money on a SOTA LLM today does not add more value than a non-SOTA LLM (assuming high value tasks).
I never said there will never be a diminishing return. I'm challenging the statement that we've already hit.
Note: We're still scaling chip nodes. It's still worth it for TSMC and chip design companies to invest hundreds of billions into every new chip node every 2-3 years. This is after decades of scaling already.
I'd guess it depends on the type of business. If it's some genuinely deep technical space, the model would give an edge but even then I think luck would be a significant factor. In a monte carlo of such scenarios, the business with the stronger model might win 6 out of 10 times, but it's no sure thing between the two of us. If we were comparing two businesses building Yet Another Generic CRUD, I would guess it's closer... perhaps even a net-negative to spend money on Fable versus marketing.
> Grey Swans: risks that were in the data but overlooked or dismissed because few had synthesized the signals into a coherent picture.
Directly conflicts with
> Alert and Critical signals represent readings that have historically been associated with meaningful financial stress.
These are all pretty standard things to track and are regularly (and publicly!)
Not saying we’re not in a bubble or near/far from it popping, but these metrics aren’t going to precisely tell you _when_, which is pretty much the only thing that matters.
That wasn't what it seemed like at the time. Amazon didn't post profits, sure, but they sure as hell weren't a giant money suck either, they didn't need billions in financing to run their business. There were a lot of Amazon bears, but they were concerned about the high valuation, not about them going broke (since even the most pessimistic bear can read a cashflow statement).
Amazon had a close call around the .com crash as capital markets froze, but they were not going broke every year. They were purposely (and rather famously in business circles) investing every dollar made in order to grow the business. It was clear early on the original business worked.
Amazon also added/pivoted to AWS, which is where a huge part of its value comes from today.
you won't get debt if you don't have assets that can be repossessed, so having debt means these AI companies have assets: that's a strong thing, not a weak thing. interest rates are what they are, and they go up and down for reasons exogenous to your industry; debt regardless of interest is always "cheaper" than equity, and the shareholders expect to make their money from equity, paying interest on debt as a type of impedance matching and cost of keeping more equity.
so everything is going according to plan, and nobody knows the future, and predicting collpses has never been a profitable business.
I didn't have to read past the first few confusing contorted and convoluted paragraps of this article to decide to come over here and explain it, this is all straightforward corporate finance 102 and the article is fluff
I agree with the general sentiment, but I feel like it is also a bit reductive. Assets in this space are near impossible to evaluate and can fluctuate in value greatly based on other actors. In a hypothetical scenario where, say, google releases a new frontier model that somehow leapfrogs the competition by 5 months all of a sudden the value of the Asset of Fable 5 and GPT 5.6 might completely crater.
I would imagine Anthropic et al. are largely leasing land/buildings, so as the other commenter said… must be the server racks that are acting as collateral (if anything). Generally enterprise hardware depreciates very harshly. I’m used to paying $10 for Intel Xeons that once retailed for over $5,000. I expect to pick up some NVIDIA Blackwell 6000s for $100 each someday.
Yep, a friend recently told me that he remembers working somewhere that gave away old empty server racks - they were unnecessary, and expensive to store, so why keep them?
GPUs have a five year lifespan before they become obsolete and start experiencing reliability issues. We're already 1-2 years into that five year lifespan.
A while ago I was thinking, “Gee, AI is so complicated, how can I keep up with the landscape?”
After reading these articles go by so often, it feels like what I actually can’t keep up with is the bond market. To paraphrase Trotsky, you may not be interested in the bond market, but the bond market is interested in you. I want to be able to read the signals at the bottom of this article, and divine some kind of prediction that can guide me… I don’t know, to choose whether I should buy a house or change the investment strategy in my retirement fund or something. But I’m just seeing all these signals go by, waiting for the story to be written, which only happens when the dust settles.
I guess I’ll go back to not understanding AI, instead of not understanding the bond market.
As a retail investor, you should buy an index fund and then forget about it.
By the time you have read this article, the professionals and their computers will have digested that material a thousand times over and have priced it in.
To be more precise: by the lowest cost most diversified index fund you can buy and then hold it. If you want to spend some smarts to get a better return: look at how to minimise taxes and fees.
Don’t forget there is a constant pressure for everyone to have an opinion on how this is going to end while hoping it ends tomorrow so they can be vindicated. The dotcom bust took a decade to grow and collapse. I think it is too early to make predictions with AI. I mean the sentiment here is either it will dry up the world and kill us all or transcend humanity, there’s no gray area. I don’t want to fall into the emotional sieve that seems to drive everything.
That's the financial stakes here. That's why it's all or nothing. You're spending on a level that is only justified by the bonafide machine god being ushered into existence, not productivity or coding tools (and on relatively short time horizon). So if this doesn't change the near term trajectory of humanity to a parabolic move upward there is going to be a lot of economic pain. It's not just the spending, it's that the expectations for the returns to justify them are in a relatively short period of time.
> if this doesn't change the near term trajectory of humanity to a parabolic move upward there is going to be a lot of economic pain
"trajectory of humanity to a parabolic move upward" is poorly defined here. Whether we are headed to a machine god ruled scenario or "just" incredibly powerful productivity tools, there will be a lot of economic pain for some (most) and a lot of economic gain for a few.
I've yet to a see an LLM/agent-based business plan in where scaling with an order fewer workers than before LLMs is not a central part of the value proposition.
such a business plan has not yet created economic value, being able to roll out features at rocket speed is not a huge determinant of a startup's success.
What’s your reasoning for saying that the spending level requires that level of justification?
I think these large numbers are casually thrown about, but the real meaning is mind boggling. 1 trillion dollars is the entire US defense budget - aircraft carriers, nuclear submarines, health care, salaries, stealth fighters ect. The hidden AI debt alone is more than that https://asia.nikkei.com/business/technology/five-us-tech-gia... just for five tech giants (not to mention all the other smaller players like neoclouds)
By that measure it doesn’t sound like that much.
You’re talking about about an amount that is a 13% of the total US government spending, of which is 20% of the entire US GDP.
I’m not saying it’s insignificant but it’s only a few percent of the US GDP and it represents spending over several years.
I mean that's so far, it continues to grow exponentially larger with each quarter. The debt issuance for the first half looks to be crowding out US treasuries in the bond market - https://www.bloomberg.com/news/newsletters/2026-07-23/ai-deb... - that's an extremely large amount of debt. And it's still getting larger and larger each quarter.
1T is big in the absolute sense, but that's simply the scale these big tech companies operate at. Go back to 2024 or 2025 and you'll see as a group they are making a net income of $400B+. The scale at which these companies do anything is just staggering.
What’s weird is how emotional people get on this. I told publicly (because I was asked, not out of an obligation to have an opinion), that the prices we pay for LLMs are likely to go up because that’s what happens when the ratio of operational assets to foreign capital drops due to the capital having been turned into heat rather than operational assets. The grief I got from people, dear Lord…
I think that opinion is as reasonable as any. I feel compelled to argue against it (I even thought out the arguments in my head!) but my compulsion to have an opinion on HN is a disease, and you made a point of saying that you gave the opinion because asked.
I feel obliged to step in here to say there is a grey area where these are useful tools for some applications but not on the path to AGI.
Unfortunately the hype machine has far outstripped their capabilities so far, and the amount of money spent doesn’t look like being recouped, so somebody is going to lose money, as people lost money on the overpriced spacex ipo (overpriced because of AI).
> there is a constant pressure for everyone to have an opinion on how this is going to end while hoping it ends tomorrow so they can be vindicated
In what bubble does this pressure exist?
How do you stay out of it all, if at all?
the core issue is that you can't simply will into a existence a thing that is never going to be.
Im very convinced there's a cult-like level of psychosis in silicon valley (except in Apple) where LLM's must begin displacing labour. It simply is not happening. And the longer this continues, the crazier and unhinged they will get.
I was able to create a custom index based on the top 500 that I stripped the big AI stocks from (shovels too). Then I added decent chunks of international, small cap, and treasury ETFs to it.
I have no illusions that I can time a bubble, but I'm hopeful I'm at least partially shielded, and most importantly I feel better about ignoring wall street again.
Instead of starting with the top 500 American stocks, and then adding international and small caps, you can start with a global all-market stock index--and then remove AI from that.
>I can time a bubble
What do you mean? Selling everything before this bubble pops?
Oh, if you could time a bubble, you wouldn't just sell everything: you'd sell more than everything. Ie you'd sell short.
Talk about taking a quote out of context...
Key reports to understand the root problem (no ROI):
- Gen AI: Too Much Spend, Too Little Benefit?: https://www.goldmansachs.com/insights/top-of-mind/gen-ai-too... (Goldman Sachs)
- AI’s $600 Billion Question: https://sequoiacap.com/article/ais-600b-question/ (Sequoia Capital)
- The Simple Macroeconomics of AI: https://www.nber.org/system/files/working_papers/w32487/w324... (MIT / Daron Acemoglu)
How can people in Hacker News still doubt AI's benefit when they are seeing in front of their eyes every technical profession getting disrupted to oblivion in the last year. Just ask basically any software engineer how much their profession has changed over the last 12 months
Obviously there is risk, but can't we really extrapolate the AI gains forward and just see how big it's ahead to become?
> every technical profession getting disrupted to oblivion
Where is this disruption? The longer we go, the more people report that the supposed net-gain of easily 100s of percents is not visible.
I do strongly believe "It's just a tool" - A powerful one, but not one like the invention of the steam machine.
> How can people in Hacker News still doubt AI's benefit
Because what many of us are seeing is meaningless “productivity” improvements.
If at the end of the day you don’t have more users paying for your product or the same users and paying more, then what’s the point of being more productive?
disruption != benefit.
I was called quite disruptive in class when I was young. I'm sure my teachers never meant it as a compliment.
How can people not trust in anecdotes and vibes while avoiding studies, do you mean?
Isn't that the point here? That everyone thinks massive disruption is happening and everyone is 100xing their productivity, but it's not actually showing up in the numbers anywhere?
People aren't doubting the benefit.
Lenders are doubting their return. People's benefits have nothing to do with it. The benefits would go in a minute, if doing so yielded a better return.
Warren Buffet way
Revolutionary technology + massive adoption ≠ good investment
Investors have poured money into a bottomless pit, attracted by the growth and glamour of the industry. The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
Commodity Product, no switching costs. Infinite competition
The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
The industrialisation essentially socializes the cost across a lot more people though, so even though it doesn't make a profit it does mean people can have air travel without it costing millions per flight for the few people who can afford it. Essentially the economies of scale from having lots of flights isn't enough to make it profitable but they are enough to make it affordable.
There's no spare money to extract from the airline industry but it's still very useful. The same could be true for AI in the long term.
Sometimes the goal of an industry is to exist rather than to make a profit, because the benefit to society is more important than profit. People don't like that though so they do a bit of creative accounting or head-in-the-sand denial around it.
> There's no spare money to extract from the airline industry but it's still very useful. The same could be true for AI in the long term.
Of course it could, let’s start with making the models open weight and entirely open source. Fully publicly owned and not shaped to maximise profits for the shareholders.
Oh wait, Scam Altman entered the chat and turned a non-profit lab into the next biggest IPO vehicle the world has ever seen.
OpenAI launched as a nonprofit research institution. Its announcement explicitly said it wanted to pursue AI “unconstrained by a need to generate financial return,” produce value for everyone rather than shareholders, publish research and share patents broadly.
in the case of airplanes the only thing thats the private market is the planes and the ticket, the entire system of airports, safety, navigation is state subsidized and when the market fails it gets bailed out. the oil is subsidized by constant warfare. it's just an illusion for reganomics so a few rich ppl can make a buck off of a public utility.
How does constant warfare subsidise oil? In case you haven't noticed: both the latest US-vs-Iran war and Russia-vs-Ukraine war have made oil and gas a lot more expensive than the peaceful counterfactual.
It isn't a commodity product in my opinion. Far from it. I think it will ultimately be a monopoly or duopoly for SOTA. The mid to low end is commodity, yes. But SOTA models are not commodities.
The number of competitors for SOTA drops by a few every year. The winners make more money, get more revenue, buy more compute, train better model with compute, buy best talent, and the cycle goes.
I think it's easier to fall behind and never catch back up than people think. One disastrous training run can leave a lab months to a year behind. For example, Meta's disastrous LLAMA 4 models. Meta is lucky to have their ads business as a funding source. However, Anthropic's revenue is growing so fast, that ability to use ads as a funding source to stay in the race may not last much longer for Meta.
To me, SOTA LLM training is very much like new chip fab nodes. One disastrous node can put you behind for many years or forever. The cost to build the next chip node doubles every every 4 years (Rock's law). The cost to train the next SOTA model likely has some similar power law which means over time, it's too costly for losers to keep up. The only reason TSMC isn't a defacto monopoly for advanced chip nodes is strictly due to geopolitics.
Mate the vast majority of firms dont care about this SOTA crap.
They can barely get any efficiency gains beyond the productivity of software engineers. And even that is not really translating into financial performance.
But who needs SOTA models, really? It was necessary 10 months ago, but now?
All things equal, let's say your SaaS startup uses GPT 5.0 (release 10 months ago) and my business uses Fable 5. We have the same business goals, same talent level, same strategies. I think the chance of my business winning against yours is higher.
I can't prove it. It's just my opinion.
It's easy to agree to that, but you're disregarding that the resources you spend on the stronger model could be allocated elsewhere. Conversely, you're assuming that spending more on AI will always yield better results and be worth it, compared to spending the money on other things.
This might actually still hold true now, or or at least many actors in the market behave that way. But I'm not so sure there isn't a cliff to that effect. At some point, if SOTA models remain expensive, it'll turn into a market advantage to figure out how to get things done without depending on the most expensive tooling available.
Similar scenario, different phrasing: if your company relies on overqualified workers to deliver 100% quality, the market may still decide that it's fine to go with 90% quality for 50% the price.
@orwin has claimed that SOTA LLMs have already hit that diminishing return where spending more money on a SOTA LLM today does not add more value than a non-SOTA LLM (assuming high value tasks).
I never said there will never be a diminishing return. I'm challenging the statement that we've already hit.
Note: We're still scaling chip nodes. It's still worth it for TSMC and chip design companies to invest hundreds of billions into every new chip node every 2-3 years. This is after decades of scaling already.
he clearly has never ran a firm
the constraint long-term is vision
and vision is really hard - no LLM will help with this.
I'd guess it depends on the type of business. If it's some genuinely deep technical space, the model would give an edge but even then I think luck would be a significant factor. In a monte carlo of such scenarios, the business with the stronger model might win 6 out of 10 times, but it's no sure thing between the two of us. If we were comparing two businesses building Yet Another Generic CRUD, I would guess it's closer... perhaps even a net-negative to spend money on Fable versus marketing.
Ceteris paribus, all other things are never equal.
haha what a load of crap
that worked as tactic a year ago. not anymore fella.
> Grey Swans: risks that were in the data but overlooked or dismissed because few had synthesized the signals into a coherent picture.
Directly conflicts with
> Alert and Critical signals represent readings that have historically been associated with meaningful financial stress.
These are all pretty standard things to track and are regularly (and publicly!)
Not saying we’re not in a bubble or near/far from it popping, but these metrics aren’t going to precisely tell you _when_, which is pretty much the only thing that matters.
I remember when Amazon was going to go broke every year for over a decade.
Until they didn't.
That wasn't what it seemed like at the time. Amazon didn't post profits, sure, but they sure as hell weren't a giant money suck either, they didn't need billions in financing to run their business. There were a lot of Amazon bears, but they were concerned about the high valuation, not about them going broke (since even the most pessimistic bear can read a cashflow statement).
That’s because they were reinvesting the profits. I think they had given a profitable quarter just to show that they could do it.
And I'm sure Anthropic would be immensely profitable if they stopped investing their inference profits into training newer models.
Amazon had a close call around the .com crash as capital markets froze, but they were not going broke every year. They were purposely (and rather famously in business circles) investing every dollar made in order to grow the business. It was clear early on the original business worked.
Amazon also added/pivoted to AWS, which is where a huge part of its value comes from today.
I remember when hundreds of dotcom companies were going to go broke, and they all did.
Not sure what your point is.
As a side note. All money is borrowed. That's how money gets created! Short explainer video by the great late David Graeber
https://youtu.be/LxJW7hl8oqM?is=IjdyHwZchaiMHk4C
you won't get debt if you don't have assets that can be repossessed, so having debt means these AI companies have assets: that's a strong thing, not a weak thing. interest rates are what they are, and they go up and down for reasons exogenous to your industry; debt regardless of interest is always "cheaper" than equity, and the shareholders expect to make their money from equity, paying interest on debt as a type of impedance matching and cost of keeping more equity.
so everything is going according to plan, and nobody knows the future, and predicting collpses has never been a profitable business.
I didn't have to read past the first few confusing contorted and convoluted paragraps of this article to decide to come over here and explain it, this is all straightforward corporate finance 102 and the article is fluff
I agree with the general sentiment, but I feel like it is also a bit reductive. Assets in this space are near impossible to evaluate and can fluctuate in value greatly based on other actors. In a hypothetical scenario where, say, google releases a new frontier model that somehow leapfrogs the competition by 5 months all of a sudden the value of the Asset of Fable 5 and GPT 5.6 might completely crater.
Yes, they have assets: GPUs sitting in datacenters, and data.
Question is: is that worth enough to cover the debt after the market crashed?
Don’t they all have mostly the same data, with a small / negligible delta between each other?
I would imagine Anthropic et al. are largely leasing land/buildings, so as the other commenter said… must be the server racks that are acting as collateral (if anything). Generally enterprise hardware depreciates very harshly. I’m used to paying $10 for Intel Xeons that once retailed for over $5,000. I expect to pick up some NVIDIA Blackwell 6000s for $100 each someday.
Yep, a friend recently told me that he remembers working somewhere that gave away old empty server racks - they were unnecessary, and expensive to store, so why keep them?
GPUs have a five year lifespan before they become obsolete and start experiencing reliability issues. We're already 1-2 years into that five year lifespan.