I'm not sure the comparison is apples to apples, but this article claims the current AI investment boom pales compared to the railroad investment boom in the 19th century.
> Next, Kedrosky bestows a 2x multiplier to this imputed AI CapEx level, which equates to a $624 billion positive impact on the US GDP. Based on an estimated US GDP figure of $30 trillion, AI CapEx is expected to amount to 2.08 percent of the US GDP!
Do note that peak spending on rail roads eventually amounted to ~20 percent of the US GDP in the 19th century. This means that the ongoing AI CapEx boom has lots of legroom to run before it reaches parity with the rail road boom of that bygone era.
> Do note that peak spending on rail roads eventually amounted to ~20 percent of the US GDP in the 19th century.
Has anyone found the source for that 20%? Here's a paper I found:
> Between 1848 and 1854, railroad investment, in these and in preceding years, contributed to 4.31% of GDP. Overall, the 1850s are the period in which railroad investment had the most substantial contribution to economic conditions, 2.93% of GDP, relative to 2.51% during the 1840s and 2.49% during the 1830s, driven by the much larger investment volumes during the period.
The first sentence isn't clear to me. Is 4.31 > 2.93 because the average was higher from 1848-1854 than from 1850-1859, or because the "preceding years" part means they lumped earlier investment into the former range so it's not actually an average? Regardless, we're nowhere near 20%.
I'm wondering if the claim was actually something like "total investment over x years was 20% of GDP for one year". For example, a paper about the UK says:
> At that time, £170 million was close to 20% of GDP, and most of it was spent in about four years.
By the way it's always nice when somebody actually tries to double check somebody else's research especially when you hear numbers that seemingly just sound crazy. Maybe another factoid, GDP or GNP for all practical purposes wasn't rigorously done by the government until about 1944. I believe a large part of our viewpoints on what happened in the 1800s is primarily based upon census data. But obviously if you're trying to measure a 7 year event Using census that happens every 10 years, there's going to be a lot of gap in the whisker chart.
So we're much closer to the per year spend US saw during the railroad construction era.
At this rate, I hope we get something useful, public, and reasonably priced infrastructure out of these spending in about 5-8 years just like the railroads.
> Do note that peak spending on rail roads eventually amounted to ~20 percent of the US GDP in the 19th century.
When you go so far back in time you run into the problem where GDP only counts the market economy. When you count people farming for their own consumption, making their own clothes, etc, spending on railroads was a much smaller fraction of the US economy than you'd estimate from that statistic (maybe 5-10%?)
Yes, that was a problem back then, and is also a problem today, but in different ways.
First, GDP still doesn't count you making your own meals. Second, when eg free Wikipedia replaces paid for encyclopedias, this makes society better off, but technically decreases GDP.
However, having said all that, it's remarkably how well GDP correlates with all the goods things we care about, despite its technical limitations.
Am I the only person with vehicles to wrench, a house to work on, chickens in the yard... as well as open source projects? If I'm not getting paid, I still have plenty to do which feeds me to today or prepares me for tomorrow.
> Is it a "good" economy if real GDP is up 4%, the S&P 500 is up 40%, and unemployment is up 10%?
In today's US? Debatable, but on the whole probably not.
In a hypothetical country with sane health care and social safety net policies? Yes that would be hugely beneficial. The tax base would bear the vast majority of the burden of those displaced from their jobs making it a much more straightforward collective optimization problem.
Agree completely. The idea that an increasing GDP or stock market is always good has taken a beating recently. Mostly because it seems that the beneficiaries of that number increase are the same few who already have more than enough, and everyone else continues to decline.
It's more than that even. AI may have plenty of utility. But does the massive capex on GPUs that will all be obsolete in a couple years?
You can still run a train on those old tracks. And it'll be competitive. Sure you could build all new tracks, but that's a lot more expensive and difficult. So they'll need to be a whole lot better to beat the established network.
But GPUs? And with how much tech has changed in the last decade or two and might in the next?
We saw cryptocurrency mining go from CPU to GPU to FPGA to ASICs in just a few years.
We can't yet tell where this fad is going. But there's fair reason to believe that, even if AI has tons of utility, the current economics of it might be problematic.
I'm continually amazed to find takes like this. Can you explain how you don't find clear utility, at the personal level, from LLMs?
I am being 100% genuine here, I struggle to understand how the most useful things I've ever encountered are thought of this way and would like to better understand your perspective.
Computing is fairly general-purpose, so I suspect that the data centers at least will be used for something. Reusing so many GPU's might be harder, but not as bad as ASICs. There are a lot of other calculations they could do.
the goal of the major AI labs is to create AGI. The net utility of AGI is at least on the level of electricity, or the steam engine. It's debatable whether or not they'll achieve that, but if you actually look at what the goal is, the investment makes sense.
> There is obvious utility to railroads, especially in a world with no cars.
> The net utility of AI is far more debatable.
As long as people are willing to pay for access to AI (either directly or indirectly), who are we to argue?
In comparison: what's the utility of watching a Star Wars movie? I say, if people are willing to part with their hard earned cash for something, we must assume that they get something out of it.
Isn't the US economy far more varied than it was in the 19th century? More dense? And therefore wouldn't be more difficult for one industry to dominate the US economy today than it was in the 19th century?
People should keep in mind that there was no such thing as a GDP before the 1980's.
All that has been back-calculated, and the further back you go the more ridiculous it gets.
Excuses sounded plausible at the time but killed two birds with one stone.
Less rapid increase in government benefits which had become based on GNP for survival to cope with inflation, and further obscuring the ongoing poor economic performance of the 1980's going forward compared to how it was before 1970 numerically.
The people who were numerically smart before that and saw what things were like first hand were not fooled so easily.
Even using GDP back in the 1980's when it first came out, you couldn't get a good picture of the 1960's which were not that much earlier.
I wonder about actual effectiveness of spending on railroads vs AI... Even if railroads were somewhat waste, did the investment spread much wider? At least geographically it must have as there were workers that moved around and needed services. That is it was mostly spend in economy. Thus had actual change to trickle down.
Where as AI, who actually gets the investment? Nvidia? TMSC? Are people who are employed some that would have anyway been employed? Do they actually spend much more? Any Nvidia profits likely go just back to the market propping it up even higher.
How much efficiency from use of LLMs have actually increased proctiveness?
Put a comment on this below, but the claim is highly misleading...consumer spending is ~$5 trillion, AI investment is ~$100 billion. The graph is looking at something like contribution to GDP growth (not contribution to GDP), but that is even misleading b/c if you don't adjust for seasonality, H1 consumer spending is almost always lower than H2 consumer spending of the previous year (because Q4 always has a higher level of consumer spending).
Consider other infrastructure such as the US highway system. There may be an expansive bubble, but infrastructure such as the increase in base power production needs to be factored as well.
One way to think about it is what if we’d done it the other way around? If we’d had AI first at 20% GDP investment levels, would the subsequent railroad boom have been an order of magnitude smaller at 2% GDP?
For me, that’s enough of a thought experiment — as implausible as it might be to have AI in 1901 — to be skeptical that the difference is simply that the first tech step-change was a pre-war uplift to build the post-war US success story, and the latter builds on it.
I have started to notice this as well over the past several months, in-fact, I would say it is orders of magnitude larger than the Crypto bubble and when it bursts will be significantly more impactful. Right now, everything is propped up on the premise the hyperscalers will grow EPS proportionately to their investment and that ROA is being priced in as a best case scenario (hope) in their share price. Maybe its not ROA at all, maybe its simply FOMO, we keep citing this 'AI Race' as if there is some end objective to 'win' drawing parallels to the nuclear arms race that only resulted in massive wasted CAPEX in decaying nukes sitting in unused bunkers since the cold war. (Not to mention it isn't even clear this arms race played a direct factor in the war beside depleting resources) Everyone is happy right now. Execs get stock bonuses, investors get returns, vendors get contracts. Once this is questioned, and history demonstrates it undoubtedly will be, it will cause a cascading collapse. History is a mathematical truth.
The usable amount of AI, no matter how optimistic you are about current progression, has to be below the projections the entire AI economy is living on right now.
Looking at the actual job I'm leveraging software to do, we've progressed past the point where I can do everything I want to do in-house on my own hardware. The bottlenecks in my processes are now human, procedural, and there for a reason.
It feels like the AI economy is being propped up by the idea that we're right around the corner from a fabled C-suite promised land where "labor" is unnecessary, but we've already been there for like a year now if you don't need a machine to explain your own business model to you, and it's basically free.
You've got to figure that the mega-capitalists have so much more discretionary accumulated resources relative to government than ever.
Other than government, is there anybody else who can loosen the purse strings a little bit and have it not act as a temporary stimulant as long as it lasts?
Whether they wish it would last or even provide any benefit to the average person, seems like there are plenty who wouldn't wish more prosperity on anyone who doesn't already have it :\
The only real way for long-term growth would be to plant seeds rather than dispense mere artificial stimulants.
Unless AI makes the general public way more than capitalists have spent, it wouldn't be worth any increase in cost whatsoever for things like energy or hardware. Even non-AI software could become unaffordable if their labor costs go up enough too keep top people from being poached by AI companies flush with cash.
I bet even the real estate near the data centers gets more unaffordable, at the same time clocking a win for the local economy due to the increased cash flow and tax revenue. Except all that additional cash is flowing out of peoples' pockets not in :\
I’m sure someone has numbers but I do wonder how many of their users pay and whether that covers the free users. It can still be a bubble even with high demand, if you are burning money to serve those users, because you hope one day you will rule the galaxy.
I don’t really have a strong preference, so I just use any service where I’m currently not rate limited. There are many of them and I don’t see much difference between them for day to day use. My company pays for Cursor but I burned through my monthly quota in a day working on a proof of concept that mirrored their SDK in a different language. Was it nice that I could develop a proof of concept? Yes. Would I pay 500 dollars for it from my own pocket? No, I don’t think so.
It’s like those extremely cheap food and grocery delivery apps, they made their food cheap, no delivery fees for a while… of course everyone was using it. Then, they started to run out of VC money, they had to raise prices, then suddenly nobody used them anymore and they went bankrupt. There was demand, but only because of the suppressed prices fueled by VC money.
Respectfully, starting one's argument with a factually invalid statement is not a good way to argue against a bubble. If by 'every' you are referring to the foundation model providers, this is not 100% of the 'AI service' market and even then, I would argue that a lot of this demand will need to be answered to by companies measuring ROI after the FOMO or unreasonable expectations get settled in and right now, my primary argument is this ROI is driven by speculation rather than empirical measurement.
I have spoken with many companies and nearly all of them, when speaking about AI, have gotten to the point they don't even make any sense. A common theme is 'we need' AI, but nobody can articulate 'why' and in-fact they get defensive when questioned. It is almost perfectly parallel to the 'we need blockchain' argument or 'we need a mobile app'. That isn't to say those are not useful technologies, but the rapid rise, steep decline, then gradual rise is a theme in tech.
User retention is a more important metric. Everyone is silent there. That is directly tied to MRR, long term viability and ROI for investment. If those were positive I'd expect them to be crowing about it, but they aren't.
Capacity just means there is currently more demand than supply and that might be a number of negative factors driving that: users with no ROI (free users), too rapid growth, poor efficiency etc etc.
What percentage of that capacity is being put towards useful things and what is being put towards entertainment? The products main selling point is to make us more efficient at our job and if it’s being primarily used as entertainment which everyone I know who uses an LLM besides programmers falls into that category, then I’d say the expected profit from them is a bubble.
Are those services actually operating with profit to benefit from this demand? Or are they serving that demand while taking losses and showing unrealistically inflated metrics for demand?
I'd love to see the stats though, how much capacity is used for slop vs how much is used for actual productive tasks. If half of the capacity is used by bots on social medias and scammers it doesn't mean much for the economy
Teachers are demanding not to do the work that is teaching. Lawyers are demanding not to do the work of lawyering. Engineers don't want to do coding and leaders don't want to steer the ship anymore unless it's towards AI.
Alllll the "value" is bullshit. Either AGI arrives and all jobs are over and it's eternal orgy time, or at some point the lazy ai-using losers will get fired and everyone else will go back to doing work like usual
I think it’s more like the “crash” that never happened with Uber/gig and crypto. I can’t tell if it’s just luck with one craze seamlessly enabling another in some cosmic coincidence or smart people being able to absorb the excess capital and capacity to pivot gracefully.
It’s basically similar to biking on rolling hills with each subsequent hill being a lot taller than the previous one. You come down the hill hard, but just before you crash to the ground, another hill comes up, and you let the momentum carry you through, and you also get a gush of wind in your back.
That’s what’s been happening since 2012 - it’s a great 13-year run now. I’ve stopped betting against it.
I worry about correction in chip manufacture after this – will the fab industry get even more concentrated? What if the remaining fabs scale down and set us back a decade or two cutting edge chip research? Will GPUs become extraordinarily expensive?
It is a bubble. It will collapse. The only thing that might cushion the collapse a bit is that most of the capital is from large tech companies that can absorb the fallout and pivot to the next thing. The hardware and infrastructure should be able to be leveraged for other things.
One thing that's different about AI is it's a greater percentage applicable in the real world today than most bubble things that are more hype and speculation mostly by non-technical people who are attention farming.
This statement is unrelated to the funding in the space, which is not going to be mis placed, only a question of how much.
If anything, this might be a realer version of a dot com boom.
Over the last six months, capital expenditures on AI—counting just information processing equipment and software, by the way—added more to the growth of the US economy than all consumer spending combined. You can just pull any of those quotes out—spending on IT for AI is so big it might be making up for economic losses from the tariffs, serving as a private sector stimulus program.
It's not as bad as the alarmist phrasing would suggest. Consider a toy example: suppose consumer spending was $100 and grew by $1, but AI spending was $10 and grew by $1.5, then you can rightly claim that "AI added more to the grow of the US economy than all consumer spending combined"[1]. But it's not as if the economy consists mostly of AI, or that if AI spending stopped the economy will collapse. It just means AI is a major contributor to the economy's growth right now. It's not even certain that the AI bubble popping would lead to all of that growth evaporating. Much of the AI boom involves infrastructure build out for data centers. That can be reallocated to building houses if datacenters are no longer needed.
[1] Things get even spicier if consumer growth was zero. Then what would the comparison? That AI added infinitely more to growth than consumer spending? What if it was negative? All this shows how ridiculous the framing is.
So, non-seasonally adjusted consumer spending is flat. In that sense, yes, anything where spend increased contributed more to GDP growth than consumer spending.
If you look at seasonally-adjusted rates, consumer spending has grown ~$400 billion, which might outstrips total AI CapEx in that time period, let alone growth. (To be fair the WSJ graph only shows the spending from Meta, Google, Microsoft, and Amazon. But it also says that Apple, Nvidia, and Tesla combined "only" spent $6.7 billion in Q2 2025 vs the $96 billion from the other four. So it's hard to believe that spend coming from elsewhere is contributing a ton.)
If you click through the the tweet that is the source for the WSJ article where the original quote comes from (https://x.com/RenMacLLC/status/1950544075989377196) it's very unclear what it's showing...it only shows percentage change, and it doesn't even show anything about consumer spending.
So, at best this quote is very misleadingly worded. It also seems possible that the original source was wrong.
That's bad because you just know at some point the bell is getting rung and then the bubble bursts. It was the same thing with office space in the late 1990s--they overbuilt like crazy predicting huge demand that never appeared and then the dot-com bubble burst and that was that.
Althought we know that there is no empirical evidence for trickle down economy, a worst case scenario was that some of the profit would be allocated to be cost of labor and through great economy expansion and regardless of rising inequality and some reskilling, innovation and its effect on the rise of the economy was at least somewhat positive for everybody.
This will not be the case anymore. There is no labor restructuring to be made, the lists for the future safe jobs are humorous to say the least. There has been a difficulty in finding skilled labor in sustainable wages for the companies and that has been highlighted as a key blocker for growth. Econony will rise by removing this blocker by AI. Rise of the economy due to AI invalidates old models and trickle down spurious correlations. Rise of the economy through AI directly enables the most extreme inequality and no reflexes or economics experience exists to manage it.
There have been many theories for revolutions, social financial ideological and others. I will not comnent on those but I will make a practical observation: It boils down to the ratio of controlers vs controlled. AI also enables an extremely minimal number of controllers through the AI managment of the flow information and later a large number of drones can keep everyone at bay. Cheaply, so good for the economy.
> there is no empirical evidence for trickle down economy
I usually avoid responding to remarks like this because they risk forays into politics, which I avoid, but the temptation to ask was too great here. What do you consider computers, cellphones, air conditioners, flat screen TVs and refrigerators to be? The first ones had outrageous prices that only the exorbitantly wealthy could afford. Now almost everyone in the US has them. They seem to have trickled down to me.
> What do you consider computers, cellphones, air conditioners, flat screen TVs and refrigerators to be?
Products people buy with the money they earn. Not things that fall down from the tables of the ultra rich.
Their affordability comes from the economies of scale. If I can sell 100000 units of something as opposed to 100 units, the cost-per-unit goes down. Again, nothing to do with anything "trickling down".
My understanding of trickle down economy, could be incorrect, has been that it is a policy that advocates govt. giving money to the rich. Through tax breaks and other means. The idea being that the rich would then spend that money in ways that would allow the benefits to trickle down to the poor.
I'd say prices of products come down due to competition, not due to the companies getting more money outside of the regular supply/demand relationship.
Let's assume you have a monopoly on something with a guarantee that no one else can sell the same product in your market. Then there is no direct incentive to make the product cheaper, even if you can produce it for cheaper.
Adding more money on top of it that is supposed to trickle down in some way will not make that product cheaper, unless there is an incentive for that company to do so.
The real world is of course more complicated, let's say you have two companies that get the incentives and one of them is using it to make the product cheaper, then that will "trickle down" as a price decrease because the other company need to follow suit to stay competitive. But this again is driven by the market and not the incentives and would have happened without them just as well.
Tickle down is a bit of a nonsensical term, it's called supply side economics and it's a well studied, proven way to strengthen the economy. It's how Reagan ended stagflation, and is generally one of the first things governments turn to when the economy is struggling
Computers of course were invented by a state controlled war economy, pretty much the opposite of trickle down.
Permeation of technology due to early adopters paying high costs leading to lower costs is not what trickle down generally means. Being an early adopter of cellphones, AC, flat screen TVs or computers required the wealth level of your average accountant of that era - it didn't require being a millionaire.
"Over the last six months, capital expenditures on AI—counting just information processing equipment and software, by the way—added more to the growth of the US economy than all consumer spending combined."
If this isn't the Singularity, there's going to be a big crash. What we have now is semi-useful, but too limited. It has to get a lot better to justify multiple companies with US $4 trillion valuations. Total US consumer spending is about $16 trillion / yr.
Remember the Metaverse/VR/AR boom? Facebook/Meta did somehow lose upwards of US$20 billion on that. That was tiny compared to the AI boom.
Look at the induced demand due to Claude code. I mean, they wildly underestimated average token usage by users. There's high willingness to pay. There's literally not enough inference infra available.
I was working on crypto during the NFT mania, and THAT felt like a bubble at the time. I'd spend my days writing smart contracts and related infra, but I was doing a genuine wallet transaction at most once a week, and that was on speculation, not work.
My adoption rate of AI has been rapid, not for toy tasks, but for meaningful complex work. Easily send 50 prompts per day to various AI tools, use LLM-driven auto-complete continuously, etc.
That's where AI is different from the dot com bubble (not enough folks materially transaction on the web at the time), or the crypto mania (speculation and not utility).
Could I use a smarter model today? Yes, I would love that and use the hell out of it.
Could I use a model with 10x the tokens/second today? Yes, I would use it immediately and get substantial gains from a faster iteration cycle.
A bubble isn't related to whether something is useful or not, it's about speculation and detachment from reality. AI being extremely useful and being a bubble aren't mutually exclusive. It can be the case that everyone finds it useful but at the same time the valuations and investments aren't realized.
Claude Code was the tipping point for me from "that's neat" to "wow, that's really useful". Suddenly, paying $200/month for an AI service made sense. Before that, I didn't want to pay $20/month for access to Claude, as I already had my $20/month subscription to ChatGPT.
I have to imagine that other professions are going to see similar inflection points at some point. When they do, as seen with Claude Code, demand can increase very rapidly.
* Even with all this infra buildout all the hyperscalers are constantly capacity constrained, especially for GPUs.
* Surveys are showing that most people are only using AI for a fraction of the time at work, and still reporting significant productivity benefits, even with current models.
The AGI/ASI hype is a distraction, potentially only relevant to the frontier model labs. Even if all model development froze today, there is tremendous untapped demand to be met.
The Metaverse/VR/AR boom was never a boom, with only 2 big companies (Meta, Apple) plowing any "real" money into it. Similarly with crypto, another thing that AI is unjustifiably compared to. I think because people were trying to make it happen.
With the AI boom, however, the largest companies, major governments and VCs are all investing feverishly because it is already happening and they want in on it.
> Even with all this infra buildout all the hyperscalers are constantly capacity constrained, especially for GPUs.
Are they constrained on resources for training, or resources for serving users using pre-trained LLMs? The first use case is R&D, the second is revenue. The ratio of hardware costs for those areas would be good to know.
Everything I have worked on as a fullstack developer for multiple large companies over the past 25 years tells me that AI isn't just going to replace a bunch of workers. The complexity of those places is crazy and it takes teamwork to keep them running. Just look what happens internally over a long holiday weekend at most big companies, they are often just barely meeting their uptime guarantees.
I was recently at a big, three-letter pharmacy company and I can't be specific, but just let me say this: They're always on the edge of having the main websites going down for this or that reason. It's a constant battle.
How is adding more AI complexity going to help any of that when they don't even have a competent enough workforce to manage the complexity as it is today?
You mention VR--that's another huge flop. I got my son a VR headset for Christmas in like 2022. It was cool, but he couldn't use it long or he got nauseaus. I was like "okay, this is problematic." I really liked it in some ways, but sitting around with that goofy thing on your head wasn't a strong selling point at all. It just wasn't.
If AI can't start doing things with accuracy and cleverness, then it's not useful.
So, to give a tactile example that helped me recently: We have a frontend web application that was having some issues with a specific feature. This feature makes a complex chain of a maybe dozen API requests when a resource is created, conditionally based on certain things, and there's a similar process that happens when editing this resource. But, there was a difference in behavior between the creating and editing routes, when a user expected that the behavior would be the same.
This is crusty, horrible, old, complex code. Nothing is in one place. The entire editing experience was copy-pasted from the create resource experience (not even reusable components; literally copy-pasted). As the principal on the team, with the best understanding of anyone about it, even my understanding was basically just "yeah I think these ten or so things should happen in both cases because that's how the last guy explained it to me and it vibes with how I've seen it behave when I use it".
I asked Cursor (Opus Max) something along the lines of: Compare and contrast the differences in how the application behaves when creating this resource versus updating it. Focus on the API calls its making. It responded in short order with a great summary, and without really being specifically prompted to generate this insight it ended the message by saying: It looks like editing this resource doesn't make the API call to send a notification to affected users, even though the text on the page suggests that it should and it does when creating the resource.
I suspect I could have just said "fix it" and it could have handled it. But, as with anything, as you say: Its more complicated than that. Because while we imply we want the app to do this, its a human's job (not the AI's) to read into what's happening here: The user was confused because they expected the app to do this, but do they actually want the app to do this? Or were they just confused because text on the page (which was probably just copy-pasted from the create resource flow) implied that it would?
So instead I say: Summarize this finding into a couple sentences I can send to the affected customer to get his take on it. Well, that's bread and butter for even AIs three years ago right there, so off it goes. The current behavior is correct; we just need to update the language to manage expectations better. AI could also do that, but its faster for me to just click the hyperlink in Claude's output, jumps right to the file, and I make the update.
Opus Max is expensive. According to Cursor's dashboard, this back-and-forth cost ~$1.50. But let's say it would have taken me just an hour to arrive at the same insight it did (in a fifth the time): that's easily over $100. That's a net win for the business, and its a net win for me because I now understand the code better than I did before, and I was able to focus my time on the components of the problem that humans are good at.
Honestly, VR/AR is a small gaming peripheral business, like joysticks and third party controllers. And their are companies that make that their thing and make money from it, but it was never going to be profitable enough to be the thing that a company the size of Facebook pivots to, which I could see being a consumer in the space before Facebook got in and after too.
Don't get me wrong, VRChat and Beat Saber are neat, and all the money thrown at the space got the tech advanced at a much faster rate than it would have organically have done I'm the same time (or potentially ever). But you can see Horizon's attempt to be "VRChat but a larger more profitable business" to see how the things you would need to do to monetise it to that level will lose you the audience that you want to monetise.
I honestly disagree (mostly). Sure, we might see some adjustments to valuations to better account for the expected profit margins; those might have been overblown. But if you had access to any dashboard inside these companies ([1]) all you'd see is numbers going up and to the right. Every day is a mad struggle to find capacity to serve people who want what they're selling.
The average response to that is "its just fake demand from other businesses also trying to make AI work". Then why are the same trends all but certainly happening at Cursor, for Claude Code, Midjourney, entities that generally serve customers outside of the fake money bubble? Talk to anyone under the age of 21 and ask them when they used Chat last. McDonalds wants to deploy Gemini in 43,000 US locations to help "enhance" employees (and you know they won't stop there) [2]. Students use it to cheat at school, while their professors use it to grade their generated papers. Developers on /r/ClaudeAI are funding triple $200/mo claude max subscriptions and swapping between them because the limits aren't high enough.
You can not like the world that this technology is hurtling us toward, but you need to separate that from the recognition that this is real, everyone wants this, today its the worst it'll ever be, and people still really want it. This isn't like the metaverse.
> There could be a crash that exceeds the dot com bust, at a time when the political situation through which such a crash would be navigated would be nightmarish.
If the general theme of this article is right (that it's a bubble soon to burst), I'm less concerned about the political environment and more concerned about the insane levels of debt.
If AI is indeed the thing propping up the economy, when that busts, unless there are some seriously unpopular moves made (Volcker level interest rates, another bailout leading to higher taxes, etc), then we're heading towards another depression. Likely one that makes the first look like a sideshow.
The only thing preventing that from coming true IMO is dollar hegemony (and keeping the world convinced that the world's super power having $37T of debt and growing is totally normal if you'd just accept MMT).
Some of the variables that made the Great Depression what it was included very high tariff rates and lack of quality federal oversight.
Today, we have the highest tariffs since right before the Great Depression, with the added bonus of economic uncertainty because our current tariff rates change on a near daily basis.
Add in meme stocks, AI bubble, crypto, attacks on the Federal Reserve’s independence, and a decreasing trust in federal economic data, and you can make the case that things could get pretty ugly.
Ai bubble, economy in the trash already, inflation from tariffs. Dollar might get real cheap when big holders start selling stocks and exchanging it, nobody wants to be left holding their bag, and they have a lot of dollars.
Which is their (Thiel, project2025, etc) plan, federal land will be sold for cheap.
It’s because most companies already have a lot of confidence with Microsoft contracts, and are generally very comfortable storing and processing highly sensitive data on Microsoft’s SaaS platforms. It’s a significant advantage.
Also Microsoft Azure hosts its own OpenAI models. It isn’t a proxy for OpenAI.
MS salespeople presumably already have weekly or monthly meetings with all the people with check-cutting authority, and OpenAI doesn't. They're already an approved vendor, and what's more the Azure bill is already really really big, so a few more AI charges barely register.
It's the same reason you would use RDS at an AWS shop, even if you really like CloudSQL better.
This is the main reason the big cloud vendors are so well-positioned to suck up basically any surplus from any industry even vaguely shaped like a b2b SaaS.
Lots of AI things are features masquerading as products. Microsoft already has the products, so they just have to add the AI features. Customers can either start using a new and incomplete product just for one new feature, or they can stick with the mature Microsoft suite of products they're already using and get that same feature.
As others have kind of pointed out, using "outside our DC" processing for corporate data is a non-starter for many companies.
These companies are left to choose between self-hosting models, or a vendor like MS who will rent them "their own AI running in their own Azure subscription", cut off from the outside world.
Correction ... Nvidia is propping up the economy. its like 24% of the tech sector and is the only source of gpus for most companies. This is really , really bad. Talk about all eggs in one basket. If that company was to take a shit, the domino effect would cripple the whole sector and have unimaginable ramifications to the US economy.
Readit News
https://wccftech.com/ai-capex-might-equal-2-percent-of-us-gd...
> Next, Kedrosky bestows a 2x multiplier to this imputed AI CapEx level, which equates to a $624 billion positive impact on the US GDP. Based on an estimated US GDP figure of $30 trillion, AI CapEx is expected to amount to 2.08 percent of the US GDP!
Do note that peak spending on rail roads eventually amounted to ~20 percent of the US GDP in the 19th century. This means that the ongoing AI CapEx boom has lots of legroom to run before it reaches parity with the rail road boom of that bygone era.
Has anyone found the source for that 20%? Here's a paper I found:
> Between 1848 and 1854, railroad investment, in these and in preceding years, contributed to 4.31% of GDP. Overall, the 1850s are the period in which railroad investment had the most substantial contribution to economic conditions, 2.93% of GDP, relative to 2.51% during the 1840s and 2.49% during the 1830s, driven by the much larger investment volumes during the period.
https://economics.wm.edu/wp/cwm_wp153.pdf
The first sentence isn't clear to me. Is 4.31 > 2.93 because the average was higher from 1848-1854 than from 1850-1859, or because the "preceding years" part means they lumped earlier investment into the former range so it's not actually an average? Regardless, we're nowhere near 20%.
I'm wondering if the claim was actually something like "total investment over x years was 20% of GDP for one year". For example, a paper about the UK says:
> At that time, £170 million was close to 20% of GDP, and most of it was spent in about four years.
https://www-users.cse.umn.edu/~odlyzko/doc/mania18.pdf
That would be more believable, but the comparison with AI spending in a single year would not be meaningful.
At this rate, I hope we get something useful, public, and reasonably priced infrastructure out of these spending in about 5-8 years just like the railroads.
When you go so far back in time you run into the problem where GDP only counts the market economy. When you count people farming for their own consumption, making their own clothes, etc, spending on railroads was a much smaller fraction of the US economy than you'd estimate from that statistic (maybe 5-10%?)
First, GDP still doesn't count you making your own meals. Second, when eg free Wikipedia replaces paid for encyclopedias, this makes society better off, but technically decreases GDP.
However, having said all that, it's remarkably how well GDP correlates with all the goods things we care about, despite its technical limitations.
Cache la poudre.
What's good for one class is often bad for another.
Is it a "good" economy if real GDP is up 4%, the S&P 500 is up 40%, and unemployment is up 10%?
For some people that's great. For others, not so great.
Maybe some economies are great for everyone, but this is definitely not one of those.
This economy is great for some people and bad for others.
In today's US? Debatable, but on the whole probably not.
In a hypothetical country with sane health care and social safety net policies? Yes that would be hugely beneficial. The tax base would bear the vast majority of the burden of those displaced from their jobs making it a much more straightforward collective optimization problem.
We need new metrics.
The net utility of AI is far more debatable.
You can still run a train on those old tracks. And it'll be competitive. Sure you could build all new tracks, but that's a lot more expensive and difficult. So they'll need to be a whole lot better to beat the established network.
But GPUs? And with how much tech has changed in the last decade or two and might in the next?
We saw cryptocurrency mining go from CPU to GPU to FPGA to ASICs in just a few years.
We can't yet tell where this fad is going. But there's fair reason to believe that, even if AI has tons of utility, the current economics of it might be problematic.
I am being 100% genuine here, I struggle to understand how the most useful things I've ever encountered are thought of this way and would like to better understand your perspective.
I'm sure if you asked the luddites the utility of mechanized textile production you'd get a negative response as well.
> The net utility of AI is far more debatable.
As long as people are willing to pay for access to AI (either directly or indirectly), who are we to argue?
In comparison: what's the utility of watching a Star Wars movie? I say, if people are willing to part with their hard earned cash for something, we must assume that they get something out of it.
More like apples to octopus.
People should keep in mind that there was no such thing as a GDP before the 1980's.
All that has been back-calculated, and the further back you go the more ridiculous it gets.
Excuses sounded plausible at the time but killed two birds with one stone.
Less rapid increase in government benefits which had become based on GNP for survival to cope with inflation, and further obscuring the ongoing poor economic performance of the 1980's going forward compared to how it was before 1970 numerically.
The people who were numerically smart before that and saw what things were like first hand were not fooled so easily.
Even using GDP back in the 1980's when it first came out, you couldn't get a good picture of the 1960's which were not that much earlier.
Don't make me laugh trying for the 1860's :)
Where as AI, who actually gets the investment? Nvidia? TMSC? Are people who are employed some that would have anyway been employed? Do they actually spend much more? Any Nvidia profits likely go just back to the market propping it up even higher.
How much efficiency from use of LLMs have actually increased proctiveness?
https://sherwood.news/markets/the-ai-spending-boom-is-eating...
(comment below: https://news.ycombinator.com/item?id=44804528 )
For me, that’s enough of a thought experiment — as implausible as it might be to have AI in 1901 — to be skeptical that the difference is simply that the first tech step-change was a pre-war uplift to build the post-war US success story, and the latter builds on it.
It feels like the AI economy is being propped up by the idea that we're right around the corner from a fabled C-suite promised land where "labor" is unnecessary, but we've already been there for like a year now if you don't need a machine to explain your own business model to you, and it's basically free.
Other than government, is there anybody else who can loosen the purse strings a little bit and have it not act as a temporary stimulant as long as it lasts?
Whether they wish it would last or even provide any benefit to the average person, seems like there are plenty who wouldn't wish more prosperity on anyone who doesn't already have it :\
The only real way for long-term growth would be to plant seeds rather than dispense mere artificial stimulants.
Unless AI makes the general public way more than capitalists have spent, it wouldn't be worth any increase in cost whatsoever for things like energy or hardware. Even non-AI software could become unaffordable if their labor costs go up enough too keep top people from being poached by AI companies flush with cash.
I bet even the real estate near the data centers gets more unaffordable, at the same time clocking a win for the local economy due to the increased cash flow and tax revenue. Except all that additional cash is flowing out of peoples' pockets not in :\
As long as that remains true, don't see how this bubble will be popped
I don’t really have a strong preference, so I just use any service where I’m currently not rate limited. There are many of them and I don’t see much difference between them for day to day use. My company pays for Cursor but I burned through my monthly quota in a day working on a proof of concept that mirrored their SDK in a different language. Was it nice that I could develop a proof of concept? Yes. Would I pay 500 dollars for it from my own pocket? No, I don’t think so.
It’s like those extremely cheap food and grocery delivery apps, they made their food cheap, no delivery fees for a while… of course everyone was using it. Then, they started to run out of VC money, they had to raise prices, then suddenly nobody used them anymore and they went bankrupt. There was demand, but only because of the suppressed prices fueled by VC money.
I have spoken with many companies and nearly all of them, when speaking about AI, have gotten to the point they don't even make any sense. A common theme is 'we need' AI, but nobody can articulate 'why' and in-fact they get defensive when questioned. It is almost perfectly parallel to the 'we need blockchain' argument or 'we need a mobile app'. That isn't to say those are not useful technologies, but the rapid rise, steep decline, then gradual rise is a theme in tech.
That's what everybody was saying in February 2000.
Capacity just means there is currently more demand than supply and that might be a number of negative factors driving that: users with no ROI (free users), too rapid growth, poor efficiency etc etc.
Teachers are demanding not to do the work that is teaching. Lawyers are demanding not to do the work of lawyering. Engineers don't want to do coding and leaders don't want to steer the ship anymore unless it's towards AI.
Alllll the "value" is bullshit. Either AGI arrives and all jobs are over and it's eternal orgy time, or at some point the lazy ai-using losers will get fired and everyone else will go back to doing work like usual
It’s basically similar to biking on rolling hills with each subsequent hill being a lot taller than the previous one. You come down the hill hard, but just before you crash to the ground, another hill comes up, and you let the momentum carry you through, and you also get a gush of wind in your back.
That’s what’s been happening since 2012 - it’s a great 13-year run now. I’ve stopped betting against it.
No, history is a web of lies written by the winners, just like your daily news.
This statement is unrelated to the funding in the space, which is not going to be mis placed, only a question of how much.
If anything, this might be a realer version of a dot com boom.
[1] Things get even spicier if consumer growth was zero. Then what would the comparison? That AI added infinitely more to growth than consumer spending? What if it was negative? All this shows how ridiculous the framing is.
Is the keyword here. US consumers have been spending so much so of course that sector doesn't have that much room to grow.
Using non-seasonally adjusted St. Louis FRED data (https://fred.stlouisfed.org/series/NA000349Q), and the AI CapEx spending for Meta, Alphabet, Microsoft, and Amazon from the WSJ article (https://www.wsj.com/tech/ai/silicon-valley-ai-infrastructure...):
-------------------------------------------------
Q4 2025 consumer spending: ~$5.2 trillion
Q4 2025 AI CapEx spending: ~$75 billion
-------------------------------------------------
Q1 2025 consumer spending: ~$5 trillion
Q1 2025 AI CapEx spending: ~$75 billion
-------------------------------------------------
Q2 2025 consumer spending: ~$5.2 trillion
Q2 2025 AI CapEx spending: ~$100 billion
-------------------------------------------------
So, non-seasonally adjusted consumer spending is flat. In that sense, yes, anything where spend increased contributed more to GDP growth than consumer spending.
If you look at seasonally-adjusted rates, consumer spending has grown ~$400 billion, which might outstrips total AI CapEx in that time period, let alone growth. (To be fair the WSJ graph only shows the spending from Meta, Google, Microsoft, and Amazon. But it also says that Apple, Nvidia, and Tesla combined "only" spent $6.7 billion in Q2 2025 vs the $96 billion from the other four. So it's hard to believe that spend coming from elsewhere is contributing a ton.)
If you click through the the tweet that is the source for the WSJ article where the original quote comes from (https://x.com/RenMacLLC/status/1950544075989377196) it's very unclear what it's showing...it only shows percentage change, and it doesn't even show anything about consumer spending.
So, at best this quote is very misleadingly worded. It also seems possible that the original source was wrong.
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This will not be the case anymore. There is no labor restructuring to be made, the lists for the future safe jobs are humorous to say the least. There has been a difficulty in finding skilled labor in sustainable wages for the companies and that has been highlighted as a key blocker for growth. Econony will rise by removing this blocker by AI. Rise of the economy due to AI invalidates old models and trickle down spurious correlations. Rise of the economy through AI directly enables the most extreme inequality and no reflexes or economics experience exists to manage it.
There have been many theories for revolutions, social financial ideological and others. I will not comnent on those but I will make a practical observation: It boils down to the ratio of controlers vs controlled. AI also enables an extremely minimal number of controllers through the AI managment of the flow information and later a large number of drones can keep everyone at bay. Cheaply, so good for the economy.
I usually avoid responding to remarks like this because they risk forays into politics, which I avoid, but the temptation to ask was too great here. What do you consider computers, cellphones, air conditioners, flat screen TVs and refrigerators to be? The first ones had outrageous prices that only the exorbitantly wealthy could afford. Now almost everyone in the US has them. They seem to have trickled down to me.
Products people buy with the money they earn. Not things that fall down from the tables of the ultra rich.
Their affordability comes from the economies of scale. If I can sell 100000 units of something as opposed to 100 units, the cost-per-unit goes down. Again, nothing to do with anything "trickling down".
You're talking about this: https://ideas.repec.org/p/wrk/warwec/270.html
:)
Let's assume you have a monopoly on something with a guarantee that no one else can sell the same product in your market. Then there is no direct incentive to make the product cheaper, even if you can produce it for cheaper. Adding more money on top of it that is supposed to trickle down in some way will not make that product cheaper, unless there is an incentive for that company to do so.
The real world is of course more complicated, let's say you have two companies that get the incentives and one of them is using it to make the product cheaper, then that will "trickle down" as a price decrease because the other company need to follow suit to stay competitive. But this again is driven by the market and not the incentives and would have happened without them just as well.
Permeation of technology due to early adopters paying high costs leading to lower costs is not what trickle down generally means. Being an early adopter of cellphones, AC, flat screen TVs or computers required the wealth level of your average accountant of that era - it didn't require being a millionaire.
I ask hyperbolically: are they economic enablers or financial traps?
(My hunch is that fridges are net-enablers, but TVs are net-traps. I say this as someone with a TV habit I would like to kick.)
If this isn't the Singularity, there's going to be a big crash. What we have now is semi-useful, but too limited. It has to get a lot better to justify multiple companies with US $4 trillion valuations. Total US consumer spending is about $16 trillion / yr.
Remember the Metaverse/VR/AR boom? Facebook/Meta did somehow lose upwards of US$20 billion on that. That was tiny compared to the AI boom.
I was working on crypto during the NFT mania, and THAT felt like a bubble at the time. I'd spend my days writing smart contracts and related infra, but I was doing a genuine wallet transaction at most once a week, and that was on speculation, not work.
My adoption rate of AI has been rapid, not for toy tasks, but for meaningful complex work. Easily send 50 prompts per day to various AI tools, use LLM-driven auto-complete continuously, etc.
That's where AI is different from the dot com bubble (not enough folks materially transaction on the web at the time), or the crypto mania (speculation and not utility).
Could I use a smarter model today? Yes, I would love that and use the hell out of it. Could I use a model with 10x the tokens/second today? Yes, I would use it immediately and get substantial gains from a faster iteration cycle.
I have to imagine that other professions are going to see similar inflection points at some point. When they do, as seen with Claude Code, demand can increase very rapidly.
* Even with all this infra buildout all the hyperscalers are constantly capacity constrained, especially for GPUs.
* Surveys are showing that most people are only using AI for a fraction of the time at work, and still reporting significant productivity benefits, even with current models.
The AGI/ASI hype is a distraction, potentially only relevant to the frontier model labs. Even if all model development froze today, there is tremendous untapped demand to be met.
The Metaverse/VR/AR boom was never a boom, with only 2 big companies (Meta, Apple) plowing any "real" money into it. Similarly with crypto, another thing that AI is unjustifiably compared to. I think because people were trying to make it happen.
With the AI boom, however, the largest companies, major governments and VCs are all investing feverishly because it is already happening and they want in on it.
Are they constrained on resources for training, or resources for serving users using pre-trained LLMs? The first use case is R&D, the second is revenue. The ratio of hardware costs for those areas would be good to know.
I was recently at a big, three-letter pharmacy company and I can't be specific, but just let me say this: They're always on the edge of having the main websites going down for this or that reason. It's a constant battle.
How is adding more AI complexity going to help any of that when they don't even have a competent enough workforce to manage the complexity as it is today?
You mention VR--that's another huge flop. I got my son a VR headset for Christmas in like 2022. It was cool, but he couldn't use it long or he got nauseaus. I was like "okay, this is problematic." I really liked it in some ways, but sitting around with that goofy thing on your head wasn't a strong selling point at all. It just wasn't.
If AI can't start doing things with accuracy and cleverness, then it's not useful.
Humans are not always accurate or clever. But we still consider them useful and employ them.
This is crusty, horrible, old, complex code. Nothing is in one place. The entire editing experience was copy-pasted from the create resource experience (not even reusable components; literally copy-pasted). As the principal on the team, with the best understanding of anyone about it, even my understanding was basically just "yeah I think these ten or so things should happen in both cases because that's how the last guy explained it to me and it vibes with how I've seen it behave when I use it".
I asked Cursor (Opus Max) something along the lines of: Compare and contrast the differences in how the application behaves when creating this resource versus updating it. Focus on the API calls its making. It responded in short order with a great summary, and without really being specifically prompted to generate this insight it ended the message by saying: It looks like editing this resource doesn't make the API call to send a notification to affected users, even though the text on the page suggests that it should and it does when creating the resource.
I suspect I could have just said "fix it" and it could have handled it. But, as with anything, as you say: Its more complicated than that. Because while we imply we want the app to do this, its a human's job (not the AI's) to read into what's happening here: The user was confused because they expected the app to do this, but do they actually want the app to do this? Or were they just confused because text on the page (which was probably just copy-pasted from the create resource flow) implied that it would?
So instead I say: Summarize this finding into a couple sentences I can send to the affected customer to get his take on it. Well, that's bread and butter for even AIs three years ago right there, so off it goes. The current behavior is correct; we just need to update the language to manage expectations better. AI could also do that, but its faster for me to just click the hyperlink in Claude's output, jumps right to the file, and I make the update.
Opus Max is expensive. According to Cursor's dashboard, this back-and-forth cost ~$1.50. But let's say it would have taken me just an hour to arrive at the same insight it did (in a fifth the time): that's easily over $100. That's a net win for the business, and its a net win for me because I now understand the code better than I did before, and I was able to focus my time on the components of the problem that humans are good at.
Edit: agree on the metaverse as implemented/demoed not being much, but that's literally one application
Don't get me wrong, VRChat and Beat Saber are neat, and all the money thrown at the space got the tech advanced at a much faster rate than it would have organically have done I'm the same time (or potentially ever). But you can see Horizon's attempt to be "VRChat but a larger more profitable business" to see how the things you would need to do to monetise it to that level will lose you the audience that you want to monetise.
The average response to that is "its just fake demand from other businesses also trying to make AI work". Then why are the same trends all but certainly happening at Cursor, for Claude Code, Midjourney, entities that generally serve customers outside of the fake money bubble? Talk to anyone under the age of 21 and ask them when they used Chat last. McDonalds wants to deploy Gemini in 43,000 US locations to help "enhance" employees (and you know they won't stop there) [2]. Students use it to cheat at school, while their professors use it to grade their generated papers. Developers on /r/ClaudeAI are funding triple $200/mo claude max subscriptions and swapping between them because the limits aren't high enough.
You can not like the world that this technology is hurtling us toward, but you need to separate that from the recognition that this is real, everyone wants this, today its the worst it'll ever be, and people still really want it. This isn't like the metaverse.
[1] https://openrouter.ai/rankings
[2] https://nypost.com/2025/03/06/lifestyle/mcdonalds-to-employ-...
If the general theme of this article is right (that it's a bubble soon to burst), I'm less concerned about the political environment and more concerned about the insane levels of debt.
If AI is indeed the thing propping up the economy, when that busts, unless there are some seriously unpopular moves made (Volcker level interest rates, another bailout leading to higher taxes, etc), then we're heading towards another depression. Likely one that makes the first look like a sideshow.
The only thing preventing that from coming true IMO is dollar hegemony (and keeping the world convinced that the world's super power having $37T of debt and growing is totally normal if you'd just accept MMT).
The first Great Depression was pretty darn bad, I'm not at all convinced that this hypothetical one would be worse.
Today, we have the highest tariffs since right before the Great Depression, with the added bonus of economic uncertainty because our current tariff rates change on a near daily basis.
Add in meme stocks, AI bubble, crypto, attacks on the Federal Reserve’s independence, and a decreasing trust in federal economic data, and you can make the case that things could get pretty ugly.
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[0]: https://en.wikipedia.org/wiki/The_Mandibles
Which is their (Thiel, project2025, etc) plan, federal land will be sold for cheap.
As someone in an AI company right now - Almost every company we work with is using Azure wrapped OpenAI. We're not sure why, but that is the case.
Also Microsoft Azure hosts its own OpenAI models. It isn’t a proxy for OpenAI.
It's the same reason you would use RDS at an AWS shop, even if you really like CloudSQL better.
This is the main reason the big cloud vendors are so well-positioned to suck up basically any surplus from any industry even vaguely shaped like a b2b SaaS.
These companies are left to choose between self-hosting models, or a vendor like MS who will rent them "their own AI running in their own Azure subscription", cut off from the outside world.