At least in the developed world, I don't see $2tn of positive-return investments in any of those categories.
Schools just hire more administrators and build nicer gyms.
chop chop... get to it.
Student to teacher ratios have continuously decreased and are about half of what they were in 1960. Data on the results is mixed: https://www.brookings.edu/articles/class-size-what-research-...
What's your own theory ?
Administrative waste and forced retention of shitty teachers in states where schools are jobs, not education, programmes.
Even excluding military spending, US governments spend $2 trillion every 10 weeks.
And about 10% of this is interest. So over the course of a year, the US is paying about $1.25 trillion in interest at the federal and state level.
Other nations are falling behind and will be at a real disadvantage soon.
Similar to the "why we spend money exploring space when there are hungry people on Earth?" question, I don't think this is a This Or That argument.
People and companies have different interests, some don't/can't care about education etc so they don't invest in those fields. Forcing these people/companies to invest in areas they don't interested in usually results in bad outcomes that is way worse than just let them be.
But some, do invest in education or civil infrastructure projects. It's not as hot, because... well, usually it makes less money from those things.
The core problem is still that, it is hard to figure out how to invest in such way that it could help the disadvantaged people, while at the same time maintaining a 10 or even 100x growth in the next 5 years.
From the company's perspective, there's no dilemma here, it's 100x growth potential ahead of everything else.
Governments are often just as bad at this as private entities are.
What’s scary about the AI boom is people over investing and not being able to recoup their investment which will lead to knock on effects - companies going bankrupt and people losing jobs, savings gone, … etc.
* As ESG has shown, not everyone agrees on what is considered “improving”.
The US government spend a lot on healthcare ($5.3 in 2024)[0]. More than most European countries per capita. But many people still feel that the US hardly has healthcare at all. Pouring more money without a full structural overhaul will likely make things worse.
And the $2T you mentioned is investors' money, which means that your plan is actually to increase tax by $2T and pour it into a system proven inefficient.
[0]: https://www.healthaffairs.org/doi/10.1377/hlthaff.2025.01683
> and we got “Greed is Good” Geckos running things since
This phrase is the opposite of an exaggeration. It sounds like it should not be true, but it really, really is. To be fair though, if you told me in 2015 what the headlines for the 2020s would look like, I would assume you are some kind of satirist or comedian.
and fyi, that 2t is not tax money, it's someone's money.
I don’t know what she’s talking about. I’ve never had a contact group with that title. Out the window my car is doing donuts on an old baseball diamond.
you may think she's just your gal but she may be everyone's pal.
Also, as an aside, the benefits of globalization on the balance far outweigh the drawbacks. Globalization has been the primary force pulling 3rd world countries out of poverty over the last 80 years.
Just kidding.
Banks took the money the American people gave them, and they used it to pay themselves huge bonuses, and lobby the Congress to kill big reform. And then they blamed immigrants and poor people, and this time even teachers. And when all was said and done, only one single banker went to jail."
Edit: I see I'm not the first to quote The Big Short in reply - such a good movie (and book)!
If it’s after the midterms, I’m doubtful. The AI leaders—apart from Dario—have gone particularly partisan. We also have a lot more post-crisis tooling that lets us wipe equity even when bailing out. See, for example, the ‘23 bank failures.
The scapegoats for this plan never change and have never changed in human history.
Multi-million dollar companies will be reduced into multi thousand dollar companies.
The CEOs will be replaced with teenagers in garages with their parent's credit cards.
If it stalls, then China will undercut the whole AI market with cheap electricity and crash the US stock market.
So what exactly is the win scenario here?
Once this snaps, and it will snap suddenly, companies will be climbing over each other to rip out AI as fast as possible. They won't call it that, of course, you're not going to get a CEO on the news talking about how they made a mistake and it was wrong to invest so much in AI tech. But they'll mean it.
The win scenario is that the crash reduces "AI" use to near zero. Spat out into the graveyard of VC hype like blockchain and metaverse before it. Banished to an eternal unlife of scammers running call centre scams, deepfake porn producers, and the occasional "we made AI safe!" startup trying to reignite the bubble again. While companies with their business on the line clamber to announce that they don't use it.
I don't know much about economy and I just did some ctrl + f skimming, but this new 2026 warning is obviously more clear to me.
[1] https://www.bis.org/annualeconomicreports/index.htm?annualec...
Whether overvaluation can deflate gradually or suddently has to do entirely with debt and almost nothing to do with magnitude. AI is, currently, mostly equity financed.
"The five largest hyperscalers are set to spend over a trillion US dollars on AI-related capital expenditure from 2025 through 2026. These commitments are outpacing earnings and the free cash flow of these firms, leading some to issue debt to raise additional financing (Graph 11.A). This investment race may be partly driven by the perception that only a small number of players with superior technology will ultimately dominate the market shares. The intense competition raises the risk of firms over-committing resources to investment projects with still uncertain returns, leaving all firms vulnerable to disappointments in AI payoffs. Model analysis based on such contest motives highlights the downside risk of current AI exuberance. As competitive pressure drives capex higher, the net economic surplus – the total payoff less investment costs – declines for the sector as a whole and could turn negative in adverse scenarios (Graph 11.B). Disappointment in returns could trigger a sudden pullback in financing and turn the capex boom into a protracted investment bust, with potential knock-on effects on financial conditions (see below).
Another risk is that the AI boom runs into a supply side roadblock. The AI build- out has recently been facing growing bottlenecks in electricity, advanced semiconductors and grid equipment. Fast-growing demand for computing power is already pressuring electricity prices and input costs, with potential spillovers to inflation. Looking ahead, these temporary shortages may also amplify over-investment, as firms attempt to lock in future capacity through long-dated contracts that further expose them to any disappointments in demand.
...
Should inflation rise significantly or AI-led investment turn to a bust, the macroeconomic consequences could be amplified by existing financial vulnerabilities. A tightening of policy rates needed to contain inflation could precipitate a sharp pullback in asset prices after a prolonged period of exuberant risk-taking, triggering disruptive macro-financial feedback loops. A reversal of AI optimism could likewise have major financial consequences, given AI firms’ rising leverage and growing footprint in credit markets. Vulnerabilities extend to their supplier ecosystem, including engineering, procurement and construction (EPC) contractors whose balance sheets are comparatively weak, leaving them exposed to any capex pullback by hyperscalers.
...
A sharp repricing of equity risk could prompt a reassessment of corporate credit risk and lead to tighter credit conditions more broadly.1 Indeed, broad indices of credit spreads tend to correlate negatively with stock market returns (Graph 14.A), more so for the high-yield than the investment grade segment. While large, synchronised corrections in both markets are rare, there are notable precedents such as the Great Financial Crisis and the March 2020 dash for cash episode. A repricing of risk this time, whether triggered by higher interest rates or an AI bust, has the potential to be similarly disruptive by triggering a corporate credit freeze with wider implications for aggregate investment."
Producing a product that delivers value and people are willing to pay for makes you a "parasite"? Sure, it might cause massive disruptions to the labor market, but that's mostly orthogonal to whether it's a "parasite" or not. Mechanized farming has almost wiped out agricultural employment (compared to pre-industrial levels), but that doesn't make tractor manufacturers or fertilizer companies "parasites"
Maybe in the eyes of seething artists/programmers seeing their jobs getting automated, but courts have so far ruled that AI training falls under fair use.
Moreover it's not hard to think of vaguely similar objections to fertilizers. They're often produced at some harm to society, as well as their use. They're also in some sense, a "heavily discounted" versions of that they replaced, bird guano or whatever.
> Moreover it's not hard to think of vaguely similar objections to fertilizers.
It's completely different. If LLM companies pulled this out of thin air it would be also different, but no; they've effectively plundered the commons and locked up all the profit for themselves. If intellectual labor goes the way of agricultural labor, I think humanity will have lost something valuable.
And don't come back with the "farmers would have said the same thing about the industrial revolution!" thing again if you're just going to terminate your thought there. Automating agricultural labor brings vast material benefits for all since it lowers the cost of tangible goods needed for life. I'd challenge you take this one step further and explain why automating intellectual labor will provide similar fruits and is therefore something to cheer for.
That’s the steel man argument.
FWIW I mostly don’t believe that LLMs are the answer, I don’t think they’re going to reach a high enough level of capability to do this, and I think the current AI companies are problematic in a lot of ways.
I also think LLM use is bad for us and probably harms our thinking abilities. And using it takes away a lot of what it means to be human.
Personally I like both physical and mental difficulty. I like gardening even if I could just buy mass produced flowers. I like riding a bike even though cars are “easier”. I like playing ukulele with my family even though I can barely make a chord, much better than listening to some other real musician, or Suno ai generated songs. I like eating my wife’s sourdough bagels even if they take several hours more than just buying some.
And I think having those regular challenges and achievements make life worth living! And I worry that the AI future that some envision will make much of what we get value from feel meaningless in the same way that writing code by hand is starting to.
Maybe we’ll still be fine in the same way I find meaning in all of those things that I listed above. But damn what a gamble
It's about capital, human or otherwise, having positive economic value. It's literally in the name. Marx tried his hand at labour-based econmics. As an economic theory, it doesn't work.
I’m not worried about it…
As to whether that will happen, I think that risk is real. Because claude code isnt made by the generalozed capabilities of the tech but by good old non-generalozable hueristics and rule based engines. I dont think that will scale to other feilds at the factor these investments assume. Its the bitter lesson again. It scales with deliberate and specific design, not data, so it wont scale
We learnt this with ibm watson. Deepblue achieved chess supremacy but the last mile wasnt data driven, it was heiristic driven, and so watson, its successor, couldnt scale/generalize.
My prediction is that this speculation on LLMs with harnesses will collapse since they wont scale. We'll have another winter where the reasearchers will be leaft alone long wnough to come up with the next breakthrough (probably game theory based data driven agency) which might then create what this hypecycle is speculating
It is cliche at this point that HN is the place you go to hear software developers reduce all of the world's problems into simple algorithmic arguments which for some reason never actually solve anything. Not shocked that we are similarly incapable of understanding that algorithmically replacing a software developer isn't easy just because we think we know what the job is.
What you've just told me is that psychologists, just like SWEs, are prone to thinking they know how business works but in fact know fuck all.
Meaning claude code wont be able to make a "claude video editing" or "claude accounting" with the current tech. Human experts will need to encode their knowledge into it for the last mile and that wont scale the way these speculations expect
This is speculation as well. Its well founded but speculation nonetheless. Youre speculating things will stay the way they have till now.
I do see your point but what makes me consoder the other side is that ive been building an app that reaches ~10k LOC, purely with opus, no code review at all, and it hasnt hit any tech debt issues that i havent easily been able to address. Setting up good context management meant that claude could just figure things out itself.
And for reference this is an app that manages an ethernet camera, runs vehicle detection on the stream, and surfaces the detections on an ipad for operators to inspect and annotate for cellphone usage, so not trivial. Needed good architechtong and design from my end, but it was honestly scarily easy. So idk what the threshold for tech debt crash is but it wasnt there
Here’s how that plays out in the economy:
- My company spent $50 on my tokens to build this internal tool
- Anthropic spent $XXX to deliver those tokens to me.
- The company I was going to buy the tool from lost $XX,XXX per year that I would have paid them.
I dunno, kind of sounds like the economy just got smaller.
I could usually accept the idea that software getting cheaper generally increases demand for software and expands the economy surrounding it, but I’m not sure if we have precedent for what happens when software becomes positively worthless.
The company could just be happy to have better margins and be happy the stock finally went up. It might literally do nothing with them or do something economically unproductive like buy back stock.
What I can tell you with certainty is that we aren’t going to hire anyone else or launch any other product as a result. Our business just isn’t at that level of growth potential.
Perhaps we can surmise that money going to shareholders can grow the economy. They’ve got more money to reinvest in other stuff.
But then again, if everyone can shart out a SaaS app with $50 in tokens, what software companies will they want to invest in?
AI gives me that feeling of “what happens to bakers and butchers when the supermarket gets invented and they decide to sell bread and meat at or below cost?”
Every company has a list of >WACC IRR projects that it can spend saved money on. If not, it’s a cash cow company that wasn’t growing in the first place and will allow shareholders to use the saved cash for other economically expanding projects.
The only path that isn’t disastrous is threading the needle of “just right” productivity gains. The people in charge aren’t smart enough to give me warm fuzzy feelings on that.
Otherwise it would probably be the software companies that are the most focused on last-mile details (where AI in my experience has the most trouble). I expect that as consumers are faced with more and more AI slop SaaS they will be increasingly willing and able to pay for quality.
Pretty soon we're going to have to reckon with the fact that AI writes better code than us.
There isn't a direct correlation between AI improvement or stagnation and whether or not the amount being spent by AI labs and the associated ecosystem will result in a financial crash.
Look into the history of railroads and the internet itself to see how massive levels of investment can result in economic crashes even when the thing being invested in produces real, widespread societal value.
One could argue that one of the nightmare economic scenarios for AI is actually that it gets too good too fast and results in a wipeout of the white collar worker that we are currently nowhere near ready to deal with given how propped up our economy is on consumer spending.
The Nasdaq took 14 years to recover, 17 once you factor in inflation.
