I’m not sure I understand these references. The banks were too big to fail specifically because they were banks involved with the finances of every major industry and government, not simply because their (arguably specious) valuations, or even market caps, had a ton of zeroes on them. What’s the argument for OpenAI being so inherently critical and interweaved with the rest of the economy that it can’t be allowed to fail? What’s the argument for how such a bailout would result in greater economic outcomes? The banks that got bailed out continued lending and immediately resumed profitable business, how will the AI companies offer value towards such a proposition?
yndoendo 17 hours ago [-]
Too big to fail is an oxymorononic statement. Bailing out bad businesses retains those that poorly managed them. Those organizations should of been sold off to remove the bad actors.
AI is currently a sunk cost to the US stock industry that is repeating the bad actor scenario. Not a single AI company is profitable and none of them produce deterministic nor cost effective solutions
Microsoft's statment of using AI to find the most resource intensive applications being ran highlights this. Task Manager does the same thing and does not need a server farm for training. It also uses MB of RAM vs GB.
If manufacturing had the same error rate in production as AI, those plants would of went out of business.
Both industries heavy use legal bribes, donations. Politicians will gladly bail them out to take ℅ of the cut in bribes.
Too big to fails are false claims to retain the bad actors that fund politicians. Bad actors need to fail so the good ones can properly operate.
Too big to fail is also allowing large corporations to skirt copyright laws. You or I seeding TB of copyright content would be thrown in jail.
Too big to fail is rebranding of legalizing corruption.
andsoitis 17 hours ago [-]
> Both industries heavy use legal bribes, donations. Politicians will gladly bail them out to take ℅ of the cut in bribes.
Are you saying that it is likely that at some point in the not too distant future, OpenAI and Anthropic will need bailout-size cash infusions from the US Government to continue existence and that the US government will do it and not face severe political consequences?
I just don't think that chain of events is likely. The current administration pays very close attention voter sentiment.
dataflow 16 hours ago [-]
> Are you saying that it is likely that at some point in the not too distant future, OpenAI and Anthropic will need bailout-size cash infusions from the US Government to continue existence and that the US government will do it and not face severe political consequences?
> The current administration pays very close attention voter sentiment.
Is that how the Anti-Weaponization Fund came about?
andsoitis 6 hours ago [-]
> Didn't they say this themselves
OpenAI backtracked, according to the article you linked to.
> Is that how the Anti-Weaponization Fund came about?
It hasn’t come about has it? It was blocked. Besides, I don’t see the connection with the topic at hand.
drdexebtjl 17 hours ago [-]
It wouldn’t be the first time the US government made expensive and unpopular moves in the name of national security and walked away largely unscathed.
andsoitis 6 hours ago [-]
That’s not a convincing argument that it is likely to happen in this case. For me to be more convinced, it would be helpful understand what similar specific example you have in mind that points to such likelihood in this case.
watwut 13 hours ago [-]
> The current administration pays very close attention voter sentiment.
In which alternative universe? The amount of bribery and self-enrichment is staggering. The treatment of the war is mind boggling. The actual political moves seem to be designed to punish disloyal republicans rather then win more votes.
jordanb 19 hours ago [-]
Moreover what would a bailout even look like? The banks got loan guarantees from the government essentially.
But like what happens if the government guarantees open ai's loans if the company is structurally unprofitable? Does the government create an operating subsidy?
iambenm 19 hours ago [-]
Modeled on Chrysler, perhaps?
andsoitis 17 hours ago [-]
> Modeled on Chrysler, perhaps?
The government intervened to prevent massive job losses, protect the domestic auto industry, and, in the 1979 case, preserve critical national security manufacturing, as Chrysler produced the M-1 Abrams tank.
Now, I suppose it is possible to imagine that the US government might bail out either or both of OpenAI or Anthropic (whether or not there's an ROI like there was with the Bank Bailout of the 2008 crisis) if the govt. deemed the technology critical to keep a fast pace on (I think we can say without doubt that requirement is satisfied) but, crucially, the government's calculus is that it is better to have these companies compete rather than bring the knowhow in-house.
Is that what you're thinking?
iambenm 1 hours ago [-]
What came to mind to me was a bailout shaped to benefit the public even if the company failed post-bailout, specifically the Chrysler Tech Center and how it was designed as a building that could be repurposed as a shopping mall if it fell through. Odd, interesting place.
etskinner 18 hours ago [-]
Inference is cheap, only the training is expensive. Both Bernie and Trump have suggested doing a partial government takeover of the big AI companies to start a sovereign wealth fund.
So it would look like the government taking ownership, letting investors lose their stake, and then operating as inference-only, which would turn a profit
oblio 18 hours ago [-]
> Inference is cheap
We have absolutely 0 hard proof of this. We have a lot of wishful thinking but no hard numbers, audited numbers from any public entity.
I'd love to see them if they are available.
fragmede 18 hours ago [-]
Where have you looked? OpenRouter? Your own experiments? From running various models locally on my MacBook, and paying for the laptop and the electricity to power it, but not the training run, as all I did was install some software that downloaded models from Hugging Face, yes it's cheap. Well, the hardware was several thousand dollars, so not cheap on a personal level, but not unaffordable either.
oblio 18 hours ago [-]
> OpenRouter
Do we have the balance sheet for OpenRouter & co?
Especially in this age where if you put AI in your company's mission statement you're drowned in money.
Let's hold off on calling something "cheap" until the external financing money runs out and the actual numbers are revealed AND audited.
> yes it's cheap.
When running toy models that do basically 0 of what regular people expect from state of the art LLMs, sure.
Running Apache is cheap. Running Google search isn't. They both serve web pages.
fragmede 14 hours ago [-]
OpenRouter is the router. We don't care about their financials, the point is that you can buy inference via them for $x/token on a variety of models for a variety of providers. Those are businesses not propped up by SV VC dreams, just hosting plus compute and their costs.
Running a local LLM isn't a mainstream normal thing to do, sure but saying it's "basically 0 of what regular people expect from state of the art LLMs" is lazily dismissing evidence because it contradicts your beliefs. It does work, and it works at a level somewhere above "basically zero" for nerds who are willing and able to set it up for themselves today. The comparison isn't Apache, it's ElasticSearch. It's not Apache cheap and simple, but it's also not Google Spanner expensive.
oblio 11 hours ago [-]
> Those are businesses not propped up by SV VC dreams, just hosting plus compute and their costs.
Again, you have no way of knowing this. During a bubble a myriad small companies nobody hears about get funded for millions and billions.
Also, plenty of startups max out the founder credit cards and then they go bankrupt.
Let's revisit this discussion and see if 10% of all the companies in OpenRouter are around in 2030.
> is lazily dismissing evidence because it contradicts your beliefs
No, it contradicts my experience. The models you can run on 128GB of VRAM/unified RAM (which is realistically the maximum a regular person can buy) are basically bad compared to Anthropic/OpenAI.
More than that hardware prices spike like crazy (and even if consumers could afford them, the hardware itself is basically a huge DYI project).
Let alone the fact that regular users need to run other things on their system so can't dedicate absolutely everything to the LLM.
Again, the financials of these businesses are at best unproven and at worst critically unsound.
treis 17 hours ago [-]
Except for movie pass startups are marginally profitable on whatever they sell.
estetlinus 16 hours ago [-]
Inference is cheap as long as you have 1000 data centers full of GPUs. The only crux is you have neither.
whateveracct 15 hours ago [-]
But you have to keep training
misja111 13 hours ago [-]
> What’s the argument for OpenAI being so inherently critical and interweaved with the rest of the economy that it can’t be allowed to fail?
AI companies are more and more interweaved with the economy because half the world is owning their stocks or has lent them money. Or, they have invested in companies that in turn have invested in AI. It is very similar to the situation before the credit crisis.
disgruntledphd2 11 hours ago [-]
Sortof, much of the financing up to now has been from equity, rather than debt (with the exception of Oracle).
As the funding profile moves more towards debt, there's a bigger chance for problems as leverage tends to amplify the bad outcomes.
If Big AI (basically Mag 7) continue to issue debt, then there may be financial stability risks if it all blows up. The numbers are fine now, but the trend line is concerning (hence the BIS paper).
boccaff 19 hours ago [-]
The value of AI and related companies on retirement funds
aurelius_v 20 hours ago [-]
Who do you think the private credit lenders are exactly?
BrenBarn 18 hours ago [-]
The argument has already been made. They argued that their business model would collapse if they weren't allowed to train on a bunch of data that wasn't theirs, and nobody stopped them. The argument will be made even more later, as they will argue that too many companies are dependent on their technology, etc.
watwut 13 hours ago [-]
> The banks that got bailed out continued lending and immediately resumed
Pushing against regulation supposed to prevent this happening again. They also resumed taking a lot of risks, just like before. Their managers got rich while doing the same decisions as before, because other people paid the price.
> What’s the argument for OpenAI being so inherently critical and interweaved with the rest of the economy
It does not need to be inherently critical and interweaved with the rest of the economy. It has to pay the bribe to the right president. The "military necessity" excuse will be used then.
datakan 20 hours ago [-]
“National security! We can’t let China win the AI race!” Or some BS
cindyllm 18 hours ago [-]
[dead]
anon373839 19 hours ago [-]
That's obviously how the AI labs are trying to position themselves. But slop generators are not integral to anything. They most definitely should be left to fail, and if the market so dictates, the hundreds of billions invested should go to zero.
nullsanity 19 hours ago [-]
[dead]
surgical_fire 19 hours ago [-]
The thing about bailing OpenAI or Anthropic is that they would need a new bailout every few months.
lbrito 21 hours ago [-]
High growth scenario and medium growth scenario (Graph 2). I feel like an idiot asking - aren't we missing some, or at least one, scenario? Is "medium growth" for the next 4 years really the worst people can think of?
oh_my_goodness 21 hours ago [-]
Financial news tends to be written for people who can fill in a lot of blanks themselves.
mohammedmsgm 21 hours ago [-]
Can't agree more, tech and finance bros have a lot in similar except when it comes to business.
anvuong 21 hours ago [-]
Essentially yes? The stock market operates entirely on the assumption that the lines will keep going up. As soon as they flatten the whole thing collapses onto itself.
willis936 18 hours ago [-]
Flatten would mean there is a profitable business model. It's been years since people have been too tired of repeatedly asking "where will the profit come from?" with no answer. This shit has exactly one direction it will end and it's not flat or up.
redbluered 15 hours ago [-]
Flatten plus debt is bad.
Debt presumes future growth.
Swizec 21 hours ago [-]
> Is "medium growth" for the next 4 years really the worst people can think of?
At this point anything less than "medium growth" will crash the economy. We'll have bigger problems if that happens (think 2000 or 2008)
free_bip 21 hours ago [-]
Right... So since it's a big problem, shouldn't we at least be considering it as a possibility so that we can minimize the impact?
20 hours ago [-]
therobots927 20 hours ago [-]
No no no… that’s unecessary. Because it won’t happen.
19 hours ago [-]
jgalt212 21 hours ago [-]
Hmm. Perhaps too similar to pre-GFC when the ratings agencies' models never accounted for scenarios where home prices went down at the national level.
SpicyLemonZest 18 hours ago [-]
The source article says (in a way that I can understand might be a bit non-obvious) that it's analyzing the AI buildout from the perspective of the people who are participating in it. Someone who believes there'll be less than "medium growth" would probably not be buying hyperscaler bonds right now regardless of their precise estimate. They discuss the tail risks if the whole investment thesis is wrong at the end.
GlacierFox 21 hours ago [-]
Can't you see how much money is being pumped into this lunacy? Of course it's going to succeed. Graphs for failire are such a bummer too and are bad for the economy...
desktopentree 21 hours ago [-]
if growth doesn't materialize, then the infrastructure build out plays out exactly like the dot com bubble. the biggest difference this time around is the earnings. if those fall, the rest crubmles.
oh_my_goodness 20 hours ago [-]
How are the earnings different this time? Can you add any color to that?
edoceo 18 hours ago [-]
In the dot-com situation earnings "didn't matter" as long as there was growth. We[1] all believed profit would come eventually. The lesson learned from that experience was that earning do sort of matter. It turns out there is a limit to selling dollars for dimes. Since then revenue, profit and unit-economics ("fundamentals") have gotten almost as much attention as they deserve.
[1] a broad and poorly defined group of "we" - typically investors and tech-bro types.
redbluered 15 hours ago [-]
That's not quite the lesson.
Earnings did come, and the outcome of the internet include Google, Amazon, and others -- several of the ten biggest companies in the world.
In 2000, there was no sane way to predict who the success stories versus failures would be, timeliness, or otherwise.
AI will be a big change. We don't know how big, when, or who the losers and winners will be yet. Everything could be grossly overvalued or undervalued. We'll only know in hindsight.
bigstrat2003 6 hours ago [-]
There is no shot that current AI tech comes even close to being as influential as the Internet. What we have right now is useless for getting anything productive done because it's so unreliable.
oh_my_goodness 6 hours ago [-]
Does anybody know how much AI is earning?
amazingamazing 20 hours ago [-]
Usefulness aside, I see little evidence AI is making money (profit, not revenue) for any firm whose profit doesn't come from the AI itself or the infrastructure, including supply chain. I'd love to hear a counterexample. One such example would be of a hypothetical company that does translations for payment, and with AI they now are making more profit because they use AI to do the translation rather than pay a translator.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
---
AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
rainprincess 19 hours ago [-]
I think this is a great point.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
ironSkillet 18 hours ago [-]
I'm not an MBA over here, but this math seems wrong. If they are spending $240 in increased costs, then they only have to make about $247 in additional revenue from that spend to preserve a 3% margin. That seems much more reasonable if it increases the probability that customers find the product they are looking for and have a good experience.
amazingamazing 10 hours ago [-]
No, because costco has a 3% margin. A cart of stuff at costco costing 247 will yield 240 to various operating costs, and roughly $7 actually to costco.
If you have a lemonade stand you might sell a cup for $1, but overall after paying yourself and for the cups, lemons, etc you might only get 3 cents each cup.
For costco revenue equals sales and membership.
ironSkillet 9 hours ago [-]
I understand that. The AI software is meant to be a productivity enhancer for the employees using it. Other than the licenses, some training etc, there are no operating costs associated with it. Just by using the software, I don't suddenly have to pay more for salaries, retirement plans, etc, which are things that in aggregate produce the 3% margin. Maybe I have to pay more in logistics because I'm moving more product now, but I think the point stands.
amazingamazing 8 hours ago [-]
The point is if you are paying for software but not increasing your revenue by your margin you are lowering it even if you are increasing profit in absolute terms.
What you are mentioning with salaries is not relevant.
ironSkillet 4 hours ago [-]
I think we can agree to disagree here. I don't see how a company needs to have an $8000 increase in revenue to justify a $240 software purchase. You are assuming that the current operating cost for every dollar of revenue is also applied to every incremental dollar in revenue gained from software efficiency, and that is just not true.
amazingamazing 1 hours ago [-]
There is nothing to disagree on, i am talking about net operating profit margins. It is math.
What you are saying is again irrelevant. It is not about justification. Is about net margins…
ambicapter 17 hours ago [-]
I agree here. OP is taking a retail company's entire profit margin, which includes a lot of operating costs, and estimating that the AI subscription will have the same margin. The AI subscription is software though, it probably has the operating costs and profit margins of software.
keeda 17 hours ago [-]
This study finds increased sales and value per customer from GenAI integration at a large Chinese online retailer (all the way back in 2023-24!) The customer Q&A scenario is one of those covered, except the customer talks directly to the LLM rather than an employee with a subscription:
> We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over 2023-2024, the platform integrated GenAI into seven business workflows spanning customer service, consumer-product matching, advertising, and seller services. We find that GenAI adoption increases sales in most workflows, with effects ranging from no detectable impact to 16.3%, depending on GenAI's marginal contribution relative to baseline firm practices. Across the four GenAI applications with positive sales effects, the implied annual incremental value is roughly $5 per consumer−an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The gains operate primarily through higher conversion rates rather than larger cart values, consistent with GenAI improving the shopping experience by reducing search, information, communication, and personalization frictions. Importantly, these effects are not associated with worse post-purchase outcomes, as product return rates and customer ratings do not deteriorate. Finally, we document substantial demand-side heterogeneity, with larger gains for less experienced consumers. Our findings provide novel, large-scale causal evidence on how GenAI shapes sales productivity in online retail, highlighting both its immediate value and broader potential.
Impact on profitability itself is hard to determine due to caveats listed in the paper (which are important to read!) but offhand I would guess that incemental $5 margin per customer is much more than what their prompts cost.
rubyfan 20 hours ago [-]
Translator services usually get paid because they offer an accreditation or certification that the humans doing the translation are trained and are not randos / computers. I could imagine these services becoming marginally more efficient but no dramatically improving profits.
ifwinterco 14 hours ago [-]
The issue is Duolingo is rubbish, what the app does isn’t that hard to replicate and there are already competitors that have a better product.
So if AI is real then that‘s the cherry on top: people can now make an alternative to your ineffective messy app even easier.
For those kind of SaaS products with no moat LLMs could actually be a problem and definitely aren’t a good thing
lumost 19 hours ago [-]
The risk here is that either AI commoditizes the software "why ask duolingo to ask chatgpt when I can do so directly?" or simply adds cost to an existing service "why does every costco employee now cost 10% more?"
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
rsalus 18 hours ago [-]
I agree with your main observations, but the Costco example is a bit contrived. I expect companies to eventually figure out suitable applications for AI, and I doubt a flat subscription per seat will be one of them. Personally, I feel the main issue is that the tooling + systems needed to deploy AI successfully have only recently started to mature.
jmalicki 19 hours ago [-]
AI has been making a ton for advertisers for decades. Think Facebook ads, Google search ads, etc.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
grey-area 15 hours ago [-]
You’re talking about machine learning, that’s not what all this money has been ploughed into, and not what people mean when they say ‘AI’ today but you’re right that it’s much more clearly effective and profitable than LLMs.
amazingamazing 18 hours ago [-]
> but it's not fundamentally different
It is. We are talking about LLMs here.
watwut 13 hours ago [-]
I don't know why you would expect Duolingo profits be helped a lot by AI. Their profits going up and down are more about how much then enshittify for free users - basically tradeoff between long term success and temporary profits. AI does not change that balance. You can enshittify and profit quickly or not enshittify and keep long term engagement.
AI announcement annoyed some people, the slop translate courses were, well, slop. That is the extend of the change.
MichaelMoser123 18 hours ago [-]
Speaking of financing: how is the Anthropic IPO going, what is the timeline? They filed over a month ago, no news since. (I would have expected some spectacular news headlines that would be designed to fuel public interest in the impending IPO, but can't detect anything of substance)
MichaelMoser123 16 hours ago [-]
just recalled: some significant open source projects are being rewritten in Rust, with the help of Claude. I don't know if these efforts will be successful in the long run, but in some way these news headlines may be creating a media dynamic as part of the IPO preparations?
I doubt anyone in the media is paying attention to projects being rewritten in Rust...
eric_khun 17 hours ago [-]
they're probably waiting to see how market reacts to fable5 and gpt 5.6
SpicyLemonZest 17 hours ago [-]
AFAICT, the last we heard of any AI company IPO was that OpenAI got spooked by the market response to SpaceX and is considering punting to 2027 (https://www.the-independent.com/tech/openai-ipo-date-valuati...). My money is on Anthropic similarly punting, especially if SpaceX manages to cross the very very short distance remaining to drop below the IPO price.
grey-area 14 hours ago [-]
They think things will be better for them in 2027?
This is the pattern I’d expect for their IPOs too, give their current fantasy valuations.
ChrisArchitect 22 hours ago [-]
(January 2026)
blobbers 20 hours ago [-]
At least if the datacenters usage crashes, we'll have cheap power from all the infra that got built.
HWR_14 16 hours ago [-]
Public utilities tend to pass on all their costs to their customers. If the data centers crumble, that just means the remaining customers (business and residential) each will have to pick up a larger share of the debt payments for the buildout.
rogerrogerr 20 hours ago [-]
No, we won't - there's significant capex on all that infra that will have to be paid down, and we won't have datacenters to help pay for it.
dd8601fn 20 hours ago [-]
Call me overly cynical, but I’m willing to bet we’re already footing the bill in more than a few ways.
19 hours ago [-]
lelanthran 14 hours ago [-]
> No, we won't - there's significant capex on all that infra that will have to be paid down, and we won't have datacenters to help pay for it.
AIUI, OP is saying that, with all these DCs with no load, we'll have excess electricity generation capacity that was built to support these DCs. That's the "cheap power" he is talking about, not necessarily "cheap computational power".
rogerrogerr 7 hours ago [-]
And I’m saying the electricity companies will have excess power, but will also have excess debt to service on infrastructure they now don’t need. They’ll get rate hikes approved to force the remaining ratepayers to pay down the capex.
Also, a bunch of that money they spent will be on transmission infrastructure that is 100% useless if you aren’t moving that amount of power along exactly that route.
steveBK123 20 hours ago [-]
+GPUs have significantly shorter useful life spans than say, all the dark fiber laid in the 90s
mattas 20 hours ago [-]
Thinking out loud, is productivity the ultimate macro benefit of AI? Should we expect macro AI investment to be a leading indicator of macro productivity gains?
For example, did macro investment in factory automation predict future productivity gains?
physix 18 hours ago [-]
I'm not sure the current administration is fully driven by macroeconomic arguments.
redwood 21 hours ago [-]
I've seen other reports that suggest the level of investment for eclipses the internet buid out in 2000 and the railroad boom more than a century earlier. I wonder if they use different ways of landing on these wildly different assessments
cperciva 21 hours ago [-]
Yes. In inflation adjusted dollars spending on AI dwarfs previous "megaprojects". But as a fraction of GDP it's fairly modest -- comparable to the Apollo Project.
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
tripletao 19 hours ago [-]
You seem to be implying that railway spending was "over 10% of GDP for a few decades" in the late 1800s. If yes then can you trace that back to a methodology? I tried and found much lower numbers, around 3% average over the peak decade.
Your estimate of current AI spending is also low. Hyperscaler capex alone is around 2% of US GDP, not including other costs (neoclouds, employee comp, etc.).
cperciva 18 hours ago [-]
You're right, I was remembering the peak and duration of the railway boom but of course it wasn't at the peak for the entire duration.
webnrrd2k 16 hours ago [-]
Manhattan Project: $36B, 5 years
▫ Apollo Program: $257B, 14 years
▫ Interstate Highway System: $620B, 37 years
▫ AI data centers: $930B, 6 years and still accelerating
That AI number is a gross underestimate. It’s nearly that for this year alone. Wildly off.
redwood 9 hours ago [-]
Amazing if inflation adjusted as the chart claims and if the other article is true... it suggests that GDP growth has eclipsed inflation. EDIT that GDP Road is reported was inflation baked in other words 0% GDP growth would include inflation so as long as the GDP is growing this phenomenon exists
kingleopold 15 hours ago [-]
this time its free printed fiat debt tho, not fully comparable. If market crashes, they will print even few times more again
mrcwinn 20 hours ago [-]
[flagged]
ambicapter 17 hours ago [-]
Is it being "invested" or is it being set on fire? Would you rather see capital be set on fire or hoarded?
doctorwho42 20 hours ago [-]
We don't have to spend it on hardware with such short use-life to spend down those dragon hoards...
The amount of money we are talking about could have given the entire US high speed commuter rail.
edoceo 18 hours ago [-]
Or every teacher gets classroom supplies for five years.
Or treatment programs for addicts. There are a lot of economic benefits to helping folks on the lower side of the income spectrum.
arjie 18 hours ago [-]
Yeah but taxing 50% of all earnings below $100k could also do that. What money can be spent on is fine but I think we’ve got a good system where people can have reward for economic output and they can use that to allocate money where they want. There are places with central planning and I don’t like them.
Personally, I’d rather the money be spent on datacenters. And as it goes, the guys with the money also would prefer that.
sapphicsnail 16 hours ago [-]
We have central planning just not by a government
paulhebert 17 hours ago [-]
You would rather build data centers than buy school supplies or implement a nationwide high speed commuter rail network?
arjie 16 hours ago [-]
Yes.
To do the latter things as a substitute would require appropriation of other people's money to spend on highly captured industries. I'd rather that not happen.
blackqueeriroh 16 hours ago [-]
But it wouldn’t have been so who cares? It’s a counterfactual.
SpicyLemonZest 17 hours ago [-]
Could it, though? California estimates the cost of SF to LA at $126 billion (and >20 years of construction time!); at that rate you'd have to spend $1T just to get a single cross-coast track. It is not obvious to me that the US's lack of high speed rail can be solved by money.
Rendered at 20:45:32 GMT+0000 (Coordinated Universal Time) with Vercel.
https://www.bis.org/publ/arpdf/ar2026e.htm
AI is currently a sunk cost to the US stock industry that is repeating the bad actor scenario. Not a single AI company is profitable and none of them produce deterministic nor cost effective solutions
Microsoft's statment of using AI to find the most resource intensive applications being ran highlights this. Task Manager does the same thing and does not need a server farm for training. It also uses MB of RAM vs GB.
If manufacturing had the same error rate in production as AI, those plants would of went out of business.
Both industries heavy use legal bribes, donations. Politicians will gladly bail them out to take ℅ of the cut in bribes.
Too big to fails are false claims to retain the bad actors that fund politicians. Bad actors need to fail so the good ones can properly operate.
Too big to fail is also allowing large corporations to skirt copyright laws. You or I seeding TB of copyright content would be thrown in jail.
Too big to fail is rebranding of legalizing corruption.
Are you saying that it is likely that at some point in the not too distant future, OpenAI and Anthropic will need bailout-size cash infusions from the US Government to continue existence and that the US government will do it and not face severe political consequences?
I just don't think that chain of events is likely. The current administration pays very close attention voter sentiment.
Didn't they say this themselves? https://edition.cnn.com/2025/11/06/tech/openai-backtracks-go...
> The current administration pays very close attention voter sentiment.
Is that how the Anti-Weaponization Fund came about?
OpenAI backtracked, according to the article you linked to.
> Is that how the Anti-Weaponization Fund came about?
It hasn’t come about has it? It was blocked. Besides, I don’t see the connection with the topic at hand.
In which alternative universe? The amount of bribery and self-enrichment is staggering. The treatment of the war is mind boggling. The actual political moves seem to be designed to punish disloyal republicans rather then win more votes.
But like what happens if the government guarantees open ai's loans if the company is structurally unprofitable? Does the government create an operating subsidy?
The government intervened to prevent massive job losses, protect the domestic auto industry, and, in the 1979 case, preserve critical national security manufacturing, as Chrysler produced the M-1 Abrams tank.
Now, I suppose it is possible to imagine that the US government might bail out either or both of OpenAI or Anthropic (whether or not there's an ROI like there was with the Bank Bailout of the 2008 crisis) if the govt. deemed the technology critical to keep a fast pace on (I think we can say without doubt that requirement is satisfied) but, crucially, the government's calculus is that it is better to have these companies compete rather than bring the knowhow in-house.
Is that what you're thinking?
So it would look like the government taking ownership, letting investors lose their stake, and then operating as inference-only, which would turn a profit
We have absolutely 0 hard proof of this. We have a lot of wishful thinking but no hard numbers, audited numbers from any public entity.
I'd love to see them if they are available.
Do we have the balance sheet for OpenRouter & co?
Especially in this age where if you put AI in your company's mission statement you're drowned in money.
Let's hold off on calling something "cheap" until the external financing money runs out and the actual numbers are revealed AND audited.
> yes it's cheap.
When running toy models that do basically 0 of what regular people expect from state of the art LLMs, sure.
Running Apache is cheap. Running Google search isn't. They both serve web pages.
Running a local LLM isn't a mainstream normal thing to do, sure but saying it's "basically 0 of what regular people expect from state of the art LLMs" is lazily dismissing evidence because it contradicts your beliefs. It does work, and it works at a level somewhere above "basically zero" for nerds who are willing and able to set it up for themselves today. The comparison isn't Apache, it's ElasticSearch. It's not Apache cheap and simple, but it's also not Google Spanner expensive.
Again, you have no way of knowing this. During a bubble a myriad small companies nobody hears about get funded for millions and billions.
Also, plenty of startups max out the founder credit cards and then they go bankrupt.
Let's revisit this discussion and see if 10% of all the companies in OpenRouter are around in 2030.
> is lazily dismissing evidence because it contradicts your beliefs
No, it contradicts my experience. The models you can run on 128GB of VRAM/unified RAM (which is realistically the maximum a regular person can buy) are basically bad compared to Anthropic/OpenAI.
More than that hardware prices spike like crazy (and even if consumers could afford them, the hardware itself is basically a huge DYI project).
Let alone the fact that regular users need to run other things on their system so can't dedicate absolutely everything to the LLM.
Again, the financials of these businesses are at best unproven and at worst critically unsound.
AI companies are more and more interweaved with the economy because half the world is owning their stocks or has lent them money. Or, they have invested in companies that in turn have invested in AI. It is very similar to the situation before the credit crisis.
As the funding profile moves more towards debt, there's a bigger chance for problems as leverage tends to amplify the bad outcomes.
If Big AI (basically Mag 7) continue to issue debt, then there may be financial stability risks if it all blows up. The numbers are fine now, but the trend line is concerning (hence the BIS paper).
Pushing against regulation supposed to prevent this happening again. They also resumed taking a lot of risks, just like before. Their managers got rich while doing the same decisions as before, because other people paid the price.
> What’s the argument for OpenAI being so inherently critical and interweaved with the rest of the economy
It does not need to be inherently critical and interweaved with the rest of the economy. It has to pay the bribe to the right president. The "military necessity" excuse will be used then.
Debt presumes future growth.
At this point anything less than "medium growth" will crash the economy. We'll have bigger problems if that happens (think 2000 or 2008)
[1] a broad and poorly defined group of "we" - typically investors and tech-bro types.
Earnings did come, and the outcome of the internet include Google, Amazon, and others -- several of the ten biggest companies in the world.
In 2000, there was no sane way to predict who the success stories versus failures would be, timeliness, or otherwise.
AI will be a big change. We don't know how big, when, or who the losers and winners will be yet. Everything could be grossly overvalued or undervalued. We'll only know in hindsight.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
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AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
If you have a lemonade stand you might sell a cup for $1, but overall after paying yourself and for the cups, lemons, etc you might only get 3 cents each cup.
For costco revenue equals sales and membership.
What you are mentioning with salaries is not relevant.
What you are saying is again irrelevant. It is not about justification. Is about net margins…
https://arxiv.org/abs/2510.12049
> We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over 2023-2024, the platform integrated GenAI into seven business workflows spanning customer service, consumer-product matching, advertising, and seller services. We find that GenAI adoption increases sales in most workflows, with effects ranging from no detectable impact to 16.3%, depending on GenAI's marginal contribution relative to baseline firm practices. Across the four GenAI applications with positive sales effects, the implied annual incremental value is roughly $5 per consumer−an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The gains operate primarily through higher conversion rates rather than larger cart values, consistent with GenAI improving the shopping experience by reducing search, information, communication, and personalization frictions. Importantly, these effects are not associated with worse post-purchase outcomes, as product return rates and customer ratings do not deteriorate. Finally, we document substantial demand-side heterogeneity, with larger gains for less experienced consumers. Our findings provide novel, large-scale causal evidence on how GenAI shapes sales productivity in online retail, highlighting both its immediate value and broader potential.
Impact on profitability itself is hard to determine due to caveats listed in the paper (which are important to read!) but offhand I would guess that incemental $5 margin per customer is much more than what their prompts cost.
So if AI is real then that‘s the cherry on top: people can now make an alternative to your ineffective messy app even easier.
For those kind of SaaS products with no moat LLMs could actually be a problem and definitely aren’t a good thing
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
It is. We are talking about LLMs here.
AI announcement annoyed some people, the slop translate courses were, well, slop. That is the extend of the change.
[1] https://news.ycombinator.com/item?id=48870966 pgrust passes 100% of the Postgres regression tests
[2] https://news.ycombinator.com/item?id=48837877 Rewriting Bun in Rust
[3] https://news.ycombinator.com/item?id=48789325 My AI-built PHP engine in Rust passes 17% of PHP-src tests, renders WordPress (ekinertac.com)
This is the pattern I’d expect for their IPOs too, give their current fantasy valuations.
AIUI, OP is saying that, with all these DCs with no load, we'll have excess electricity generation capacity that was built to support these DCs. That's the "cheap power" he is talking about, not necessarily "cheap computational power".
Also, a bunch of that money they spent will be on transmission infrastructure that is 100% useless if you aren’t moving that amount of power along exactly that route.
For example, did macro investment in factory automation predict future productivity gains?
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
https://news.ycombinator.com/item?id=44805979
Your estimate of current AI spending is also low. Hyperscaler capex alone is around 2% of US GDP, not including other costs (neoclouds, employee comp, etc.).
▫ Apollo Program: $257B, 14 years
▫ Interstate Highway System: $620B, 37 years
▫ AI data centers: $930B, 6 years and still accelerating
From: https://substack.com/@rubendominguez/note/c-244929068
The amount of money we are talking about could have given the entire US high speed commuter rail.
Or treatment programs for addicts. There are a lot of economic benefits to helping folks on the lower side of the income spectrum.
Personally, I’d rather the money be spent on datacenters. And as it goes, the guys with the money also would prefer that.
To do the latter things as a substitute would require appropriation of other people's money to spend on highly captured industries. I'd rather that not happen.