Even in the unlikely event AI somehow delivers on its valuations and thereby doesn't disappoint, the implied negative externalities on the population (mass worker redundancy, inequality that makes even our current scenario look rosy, skyrocketing electricity costs) means that America's and the world's future looks like a rocky road.
When standard of living increases significantly, inequality often also increases. The economy is not a zero sum game. Having both rising inequality and rising living standards is generally the thing to aim for.
Both parties seem to agree we should build more electric capacity, that does seem like an excellent thing to invest in, why aren't we?
As the cost of material goods decreases, they will become near free. IMO demand for human-produced goods and experiences will increase.
> I was discussing with a friend that my biggest concern with AI right now is not that it isn't capable of doing things... but that we switched from research/academic mode to full value extraction so fast that we are way out over our skis in terms of what is being promised, which, in the realm of exciting new field of academic research is pretty low-stakes all things considered... to being terrifying when we bet policy and economics on it.
That isn't overly prescient or anything... it feels like the alarm bells started a while ago... but wow the absolute "all in" of the bet is really starting to feel like there is no backup. With the cessation of EVs tax credits, the slowdown in infra spending, healthcare subsidies, etc, the portfolio of investment feels much less diverse...
Especially compared to China, which has bets in so many verticals, battery tech, EVs, solar, then of course all the AI/chips/fabs. That isn't to say I don't think there are huge risks for China... but geez does it feel like the setup for a big shift in economic power especially with change in US foreign policy.
>> I was discussing with a friend that my biggest concern with AI right now is not that it isn't capable of doing things... but that we switched from research/academic mode to full value extraction so fast
lol, I read this few hours ago, maybe without enough caffeine but I read it as "my comment from 70 *years* ago" because I thought you somehow where at the The Dartmouth Summer Research Project on Artificial Intelligence 1956 workshop!
I somehow thought "Damn... already back there, at the birth of the field they thought it was too fast". I was entirely wrong and yet in some convoluted way maybe it made sense.
At the end of the day, if you look at almost any government, roughly 2/3 of expenses go towards healthcare and education things which, AI worlkflow are very likely continue offsetting a larger and larger percentage of the costs on.
Can we still have a financial crisis from all this investment going bust because it might take too long for it to make a difference in manufacturing enough automation hardware for everyone? Yes.
But, the fundamentals are still there, parents will still send their kids to some type of school, and people will trade good in exchange for health services. That's not going to change. Neither will the need to use robots in nursing homes, I think that assumption is safe to make.
What's difficult to predict change in is adoption in manufacturing, and repairs ( be that repairing bridges or repairing your espresso machine ) because that is more of a "3D" issue and hard to automate reliably (think about how many gpus today would it actually take to get a robot to reason out and repair a whole in your drywall), given that your RL environments and training data needs grow exponentially. Technically, your phone should have enough gpu performance to do your taxes with a 3B model and a bunch of tools, eventually it'll even be better than you at it. But to tun an actual robot with multiple cameras and stuff doing troubleshooting and decision making.... you're gonna need a whole 8x rack of gpus for that.
And that's what makes it now difficult to predict what's going to happen. The areas under the curve can vary widely. We could get a 1B AGI model in 6 months, or it could take 5 years for agentic workflows to fully automate everyones taxes and actually replace 2/3 of radiology work...
Either way, while theres a significant chance of this transition to the automation age being rough, I am overall quite optimistic given the fundamentals of what governments actually spend majority of their money on.
Anecdotally, our company's next couple quarters are projected to be a bloodbath. Spending is down everywhere, nearly all of our customers are pushing for huge cuts to their contracts, and in turn literally any costs we can jettison to keep jobs is being pushed through. We're hearing the same from our customers.
AI has been the only new investment our company has made (half hearted at that). I definitely get the sense that everyone pretending things are fine to investors, meanwhile they are playing musical chairs.
Back in my economics classes at college, a professor pointed out that a stock market can go up for two reasons: On one hand, the economy is legitimately growing and shares are becoming more valuable. But on the other hand, people and corporations could be cutting spending en masse so there's extra cash to flood the stock markets and drive up prices regardless of future earnings.
Likewise on all downward business signals at my employer. I was thankfully in school during 09, but this easily feels like the biggest house of cards I have ever experienced as an adult.
> In those intervening years, a bunch of AI companies might be unable to pay back their debts.
Dumb question: isn't a lot of the current investment in the form of equity deals and/or funded by existing tech company profit lines? What do we actually know about the debt levels and schedules of the various actors?
Reminder: If you're going to feel doomer about how tech capex represents like nn% of US GDP growth, you should do some research into what percentage of US GDP growth, especially since 2020, has been the result of government printing. Arguably, our GDP growth right now is more "real" than the historical GDP growth numbers between 2020-2023, but all of it is so warped by policy that its hard to tell what's going on.
We're in extremely unprecedented times. Sometimes maybe good, sometimes maybe shit. The old rules don't apply. Etc.
separate from this article, I don't have a very high opinion of the author. he has an astonishing record of being uninformed and/or just plain wrong in everything I've ever heard him write about.
but as far as this article, the "tech capex as a percentage of GDP growth" is an incredible cherrypicking of statistics to create a narrative... when tech became a boodbath starting in 2022, the rest of the economy continued on strong. all the way until 2025, the rest of the economy was booming while tech layoffs and budget cuts after covid were exploding. so starting that chart in early 2023 when tech had bottomed out (compared to the rest of the economy) is misleading. tech capex as a percentage of the overall GDP has been consistently rising since 2010 - https://gqg.com/highchartal-paper-large-tech-capex-spend-as-...
this is obviously related to the advent of public cloud computing more than anything. why this chart appears to clash with the author's chart is the author's chart specifically calls out just percentage of GDP growth, not overall GDP. so the natural conclusion is that while tech has been in borderline recessionary conditions since 2022, it is now becoming stable (if not recovering) while the rest of the economy that didn't have the post-covid pullback (nor the same boom during covid, of course) is now having issues largely due to geopolitics and global trade.
is there an AI bubble? who cares. it's not as meaningful to the broader economy as these cherrypicking stats imply. if it's a bubble, it represents maybe .3% of the GDP. no one would be screaming from the mountain tops about a shaky economy and a bubble if that same .3% was represented by a bubble in the restaurant industry or manufacturing. in fact, in recent years, those industries DID have inflationary bubbles and it was treated like a positive thing for the most part.
I think a lot of this overanalysis and prodding for flaws in tech is generally an attempt at schadenfreude hoping that tech becomes just another industry like carpentry or plumbing. in particular, hoping for a scenario where tech is not as culturally impactful as it is today. because people are worried and frustrated about the economy, don't understand the value of tech, and hope it stops sucking up so much funding and focus by society in general.
they're not 100% wrong in being untrusting or skeptical of tech. the tech industry hasn't always been the best steward of the wealth and power it possesses. but they are generally wrong about valuations or impact of tech on the economy. like the people spending all this money are clueless. the stock market fell 900 points on friday, wiping out over $1 trillion in value over the course of a couple hours. yet the hundreds of billions invested in datacenters is a sign of impending economic doom.
is the economy good? I don't think it's doing great. but it has little to do with AI one way or another. "AI" is just another trend of making technology more accessible to the masses. no more scarier, complicated, or impactful than microcomputers, DSL, cellular phones, or youtube. and while the economy crashed in 2008, youtube and facebook did well. yet there was none of this dooming about tech specifically at the time simply because the tech industry wasn't as controversial at the time.
He is a partisan hack. During the election last year he consistently posted that gdp growth was real, the economy was booming, and it was all thanks to Biden/Harris. I called him out on it on Twitter, and he was unabashed about being a partisan propagandist. Not surprisingly, now that the politics have changed, the history changes.
Anything he says on any topic should be treated as suspect, and probably best ignored.
I think if there's a rational reasoning behind Trump unleashing ICE and the national guard on the domestic population, this must be it: "the economy is doing really bad, and we need a smokescreen so people won't talk about it."
One of my most frustrating things regarding the potential of an AI bubble was some very smart and intelligent researcher being incredibly bullish on AI on Twitter because if you extrapolate graphs measuring AI's ability to complete long-duration tasks (https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...) or other benchmarks then by 2026 or 2027 then you've basically invented AGI.
I'm going to take his statements at face value and assume that he really does have faith in his own predictions and isn't trying to fleece us.
My gripe with this statement is that this prediction is based on proxies for capability that aren't particularly reliable. To elaborate, the latest frontier models score something like 65% on SWE-bench, but I don't think they're as capable as a human that also scored 65%. That isn't to say that they're incapable, but just that they aren't as capable as an equivalent human. I think there's a very real chance that a model absolutely crushes the SWE-bench benchmark but still isn't quite ready to function as an independent software engineering agent.
So a lot of this bullishness basically hinges on the idea that if you extrapolate some line on a graph into the future, then by next year or the year after all white-collar work can be automated. Terrifying as that is, this all hinges on the idea that these graphs, these benchmarks, are good proxies.
US uniquely is suited to maximally benefit startups emerging in a new space, but maximally prevent startups entering a mature space. No smart, young person in the US matriculates into industries paved over by incumbents as they wisely anticipate that they will be in an industry deliberately hamstrung by regulatory capture.
All growth is in AI now because that's where all the smartest people are going. If AI were regulated significantly, they'd go to other industries and they would be growing faster (though not as much likely)
However there is the broader point that AI is poised offer extreme leverage to those who win the AGI race, justifying capex spending on such absurd margins.
I can’t help but think a lot of these comments are actually written by AI — and that, in itself, showcases the value of AI. The fact that all of these comments could realistically have been written by AI with what’s available today is mind-blowing.
I use AI on a day-to-day basis, and by my best estimates, I’m doing the work of three to four people as a result of AI — not because I necessarily write code faster, but because I cover more breadth (front end, back end, DevOps, security) and make better engineering decisions with a smaller team. I think the true value of AI, at least in the immediate future, lies in helping us solve common problems faster. Though it’s not yet independently doing much, the most relevant expression I can think of is: “Those who cannot do, teach.” And AI is definitely good at relaying existing knowledge.
Gotta thank AI — it’s keeping my portfolio from collapsing, at least for now . But yeah, I totally see the point: AI investment might be one of the few things holding up the U.S. economy, and it doesn’t even have to fail spectacularly to cause trouble. Even a “slightly disappointing” AI wave could ripple across markets and policy.
“Election has consequences.” … Managing a country is a big and critical job. Hard to imagine it was handed over to a bunch of people who barely qualified and hardly care about the future of America.
> more than a fifth of the entire S&P 500 market cap is now just three companies — Nvidia, Microsoft, and Apple — two of which are basically big bets on AI.
These 3 companies have been heavyweights since long before AI. Before AI, you couldn't get Nvidia cards due to crypto, or gaming. Apple is barely investing in AI. Microsoft has been the most important enterprise tech company for my entire lifetime.
44 comments
[ 3.4 ms ] story [ 64.4 ms ] threadWell... define "economic crash."
The outputs no longer correlate with the inputs. Is it possible it's "crashed" already? And is now running in a faulty state?
Both parties seem to agree we should build more electric capacity, that does seem like an excellent thing to invest in, why aren't we?
As the cost of material goods decreases, they will become near free. IMO demand for human-produced goods and experiences will increase.
> I was discussing with a friend that my biggest concern with AI right now is not that it isn't capable of doing things... but that we switched from research/academic mode to full value extraction so fast that we are way out over our skis in terms of what is being promised, which, in the realm of exciting new field of academic research is pretty low-stakes all things considered... to being terrifying when we bet policy and economics on it.
That isn't overly prescient or anything... it feels like the alarm bells started a while ago... but wow the absolute "all in" of the bet is really starting to feel like there is no backup. With the cessation of EVs tax credits, the slowdown in infra spending, healthcare subsidies, etc, the portfolio of investment feels much less diverse...
Especially compared to China, which has bets in so many verticals, battery tech, EVs, solar, then of course all the AI/chips/fabs. That isn't to say I don't think there are huge risks for China... but geez does it feel like the setup for a big shift in economic power especially with change in US foreign policy.
>> I was discussing with a friend that my biggest concern with AI right now is not that it isn't capable of doing things... but that we switched from research/academic mode to full value extraction so fast
lol, I read this few hours ago, maybe without enough caffeine but I read it as "my comment from 70 *years* ago" because I thought you somehow where at the The Dartmouth Summer Research Project on Artificial Intelligence 1956 workshop!
I somehow thought "Damn... already back there, at the birth of the field they thought it was too fast". I was entirely wrong and yet in some convoluted way maybe it made sense.
How the AI Bubble Will Pop
https://news.ycombinator.com/item?id=45448199
America is now one big bet on AI
https://news.ycombinator.com/item?id=45502706
Jeff Bezos says AI is in a bubble but society will get 'gigantic' benefits
https://news.ycombinator.com/item?id=45464429
etc
etc
Can we still have a financial crisis from all this investment going bust because it might take too long for it to make a difference in manufacturing enough automation hardware for everyone? Yes.
But, the fundamentals are still there, parents will still send their kids to some type of school, and people will trade good in exchange for health services. That's not going to change. Neither will the need to use robots in nursing homes, I think that assumption is safe to make.
What's difficult to predict change in is adoption in manufacturing, and repairs ( be that repairing bridges or repairing your espresso machine ) because that is more of a "3D" issue and hard to automate reliably (think about how many gpus today would it actually take to get a robot to reason out and repair a whole in your drywall), given that your RL environments and training data needs grow exponentially. Technically, your phone should have enough gpu performance to do your taxes with a 3B model and a bunch of tools, eventually it'll even be better than you at it. But to tun an actual robot with multiple cameras and stuff doing troubleshooting and decision making.... you're gonna need a whole 8x rack of gpus for that.
And that's what makes it now difficult to predict what's going to happen. The areas under the curve can vary widely. We could get a 1B AGI model in 6 months, or it could take 5 years for agentic workflows to fully automate everyones taxes and actually replace 2/3 of radiology work...
Either way, while theres a significant chance of this transition to the automation age being rough, I am overall quite optimistic given the fundamentals of what governments actually spend majority of their money on.
AI has been the only new investment our company has made (half hearted at that). I definitely get the sense that everyone pretending things are fine to investors, meanwhile they are playing musical chairs.
Back in my economics classes at college, a professor pointed out that a stock market can go up for two reasons: On one hand, the economy is legitimately growing and shares are becoming more valuable. But on the other hand, people and corporations could be cutting spending en masse so there's extra cash to flood the stock markets and drive up prices regardless of future earnings.
Dumb question: isn't a lot of the current investment in the form of equity deals and/or funded by existing tech company profit lines? What do we actually know about the debt levels and schedules of the various actors?
We're in extremely unprecedented times. Sometimes maybe good, sometimes maybe shit. The old rules don't apply. Etc.
but as far as this article, the "tech capex as a percentage of GDP growth" is an incredible cherrypicking of statistics to create a narrative... when tech became a boodbath starting in 2022, the rest of the economy continued on strong. all the way until 2025, the rest of the economy was booming while tech layoffs and budget cuts after covid were exploding. so starting that chart in early 2023 when tech had bottomed out (compared to the rest of the economy) is misleading. tech capex as a percentage of the overall GDP has been consistently rising since 2010 - https://gqg.com/highchartal-paper-large-tech-capex-spend-as-... this is obviously related to the advent of public cloud computing more than anything. why this chart appears to clash with the author's chart is the author's chart specifically calls out just percentage of GDP growth, not overall GDP. so the natural conclusion is that while tech has been in borderline recessionary conditions since 2022, it is now becoming stable (if not recovering) while the rest of the economy that didn't have the post-covid pullback (nor the same boom during covid, of course) is now having issues largely due to geopolitics and global trade.
is there an AI bubble? who cares. it's not as meaningful to the broader economy as these cherrypicking stats imply. if it's a bubble, it represents maybe .3% of the GDP. no one would be screaming from the mountain tops about a shaky economy and a bubble if that same .3% was represented by a bubble in the restaurant industry or manufacturing. in fact, in recent years, those industries DID have inflationary bubbles and it was treated like a positive thing for the most part.
I think a lot of this overanalysis and prodding for flaws in tech is generally an attempt at schadenfreude hoping that tech becomes just another industry like carpentry or plumbing. in particular, hoping for a scenario where tech is not as culturally impactful as it is today. because people are worried and frustrated about the economy, don't understand the value of tech, and hope it stops sucking up so much funding and focus by society in general.
they're not 100% wrong in being untrusting or skeptical of tech. the tech industry hasn't always been the best steward of the wealth and power it possesses. but they are generally wrong about valuations or impact of tech on the economy. like the people spending all this money are clueless. the stock market fell 900 points on friday, wiping out over $1 trillion in value over the course of a couple hours. yet the hundreds of billions invested in datacenters is a sign of impending economic doom.
is the economy good? I don't think it's doing great. but it has little to do with AI one way or another. "AI" is just another trend of making technology more accessible to the masses. no more scarier, complicated, or impactful than microcomputers, DSL, cellular phones, or youtube. and while the economy crashed in 2008, youtube and facebook did well. yet there was none of this dooming about tech specifically at the time simply because the tech industry wasn't as controversial at the time.
Anything he says on any topic should be treated as suspect, and probably best ignored.
I'm going to take his statements at face value and assume that he really does have faith in his own predictions and isn't trying to fleece us.
My gripe with this statement is that this prediction is based on proxies for capability that aren't particularly reliable. To elaborate, the latest frontier models score something like 65% on SWE-bench, but I don't think they're as capable as a human that also scored 65%. That isn't to say that they're incapable, but just that they aren't as capable as an equivalent human. I think there's a very real chance that a model absolutely crushes the SWE-bench benchmark but still isn't quite ready to function as an independent software engineering agent.
So a lot of this bullishness basically hinges on the idea that if you extrapolate some line on a graph into the future, then by next year or the year after all white-collar work can be automated. Terrifying as that is, this all hinges on the idea that these graphs, these benchmarks, are good proxies.
And if they aren't, oh wow.
All growth is in AI now because that's where all the smartest people are going. If AI were regulated significantly, they'd go to other industries and they would be growing faster (though not as much likely)
However there is the broader point that AI is poised offer extreme leverage to those who win the AGI race, justifying capex spending on such absurd margins.
I use AI on a day-to-day basis, and by my best estimates, I’m doing the work of three to four people as a result of AI — not because I necessarily write code faster, but because I cover more breadth (front end, back end, DevOps, security) and make better engineering decisions with a smaller team. I think the true value of AI, at least in the immediate future, lies in helping us solve common problems faster. Though it’s not yet independently doing much, the most relevant expression I can think of is: “Those who cannot do, teach.” And AI is definitely good at relaying existing knowledge.
These 3 companies have been heavyweights since long before AI. Before AI, you couldn't get Nvidia cards due to crypto, or gaming. Apple is barely investing in AI. Microsoft has been the most important enterprise tech company for my entire lifetime.