AI boom risks global financial crash, warn central bankers(telegraph.co.uk) |
AI boom risks global financial crash, warn central bankers(telegraph.co.uk) |
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?
Be it software, artwork, essays, graphic design or movie clips. There is a market for shipping cheap junk.
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...
"Historical episodes of investment booms offer instructive parallels (Graph 11.C). The canal mania of the 1830s, the British railway mania in the 1840s, the electrification exuberance of the late 1920s (roaring 20s) and the dotcom boom of the late 90s all shared one common trait: a genuine technological breakthrough that attracted capital in excess of what commercial returns could ultimately justify. These episodes ended with an eventual reversal in investment, inducing economy-wide recessions. The scale and pace of the current AI investment boom accompanied by expectations of large productivity payoffs bear resemblance to these precedents, highlighting potential downside risks in the near term."
The US gov should dissolve Anthropic and OpenAI tomorrow. Failing that they should block them from going public.
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.
Maybe I miss out on some gains and buy back in December or January. Maybe I'll increase my Berkshire position. I don't know. But companies tend to push the bad news till the end of the year, and boy, howdy there could be some bad news this year.
"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."
I’m not worried about it…
1) Could've added nifty features to roads (rf beacons?) and make it super easy to build autonomous vehicles. This would've solved so many problems, but most importantly 45,000 lives every year and millions of accidents.
2) Could've given the money to farmers who are getting ethanol subsidies today to add panels, supply tons of power to the grid, creating permanent income to the farmers instead of handouts every year.
3) Could've built many Universities permanently free which is feasible with an endowment that large.
4) Could've built walking/biking infrastructure in most cities, which would help reduce healthcare expenses. Most of the expenses today are lifestyle/metabolic diseases.
5) Could've switched the entire country to clean energy, exporting ALL of the oil and create a sovereign wealth fund.
6) Could've built a city for homeless people with homes, excess energy production (solar) providing the function of a UBI, a massive hospital with health and mental health facilities, de-addiction centers. New city in the middle of nowhere where land is dirt cheap. Army corps of engineers could execute this.
7) Rehabilitate prison (not like George Carlins suggestion of Kansas: https://www.youtube.com/watch?v=PkMrFIv_QHk), but more like nordic countries.
8) Build solar over all the interstates.
All this money is being deployed to try and turn a dime into a dollar.
The biggest area I can see where money could be deployed into building something useful -- while generating a positive return -- is real estate development in cities with massive housing shortages. That's basically not allowed in the same cities. In large part, because people who yearn for an more altruistic world care very much about their own quality of life and property values than they do about the well-being of their community in the long run.
Not sure about all of your choices in particular but "100 Manhattan projects" caps it all nicely.
Schools just hire more administrators and build nicer gyms.
And, school administrators are the opposite of what's needed in schools: the US needs better teacher pay and more teachers -- the ones who actually teach students.
Short of that however, yes, we get philanthropic failures such as Zuckerberg's attempt in silicon valley, and basically any attempt throughout Africa as examples. Throwing laptops at the problem doesn't work, neither does external donations that get funneled to the wrong places.
Maybe use it to increase outcomes.
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.
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.
If "$2T is not as much as you think", and yet we could fund literally tens of thousands of more interesting projects with this money, then we are severely misusing capital in general. My point still stands that we're pouring more money into a technology than ever before, and yet it's a technology that's been a net NEGATIVE socially so far.
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”.
Governments are often just as bad at this as private entities are.
You can then give all of the $2 trillion demurrage dollars directly to the most corrupt individual on the planet and it won't matter.
There are two scenarios:
1. The recipient keeps the money: It will automatically be returned. 2. The recipient spends the money: It has flown from the most corrupt individual on the planet to a less corrupt individual.
If we assume that each transaction allows the next recipient to make a decision on how to best spend the money, it would automatically spread out, since it cannot stagnate and pool up at any given individual.
Short term corruption doesn't pay, because accumulating excess money that you don't need via corruption just means your demurrage fee is higher.
Investing or lending money means giving it to someone that needs it more than you do and since the demurrage defeats the zero lower bound, it is rational to do so even at 0% interest since it allows you to avoid the demurrage.
And here is something that isn't intuitive for people whose mental model assumes permanent capital scarcity. If supply and demand on the money capital markets are balanced out, the expected interest rate is 0%.
Lower capital costs mean that products can be cheaper now. It is also much easier to invest into long term projects, e.g. against climate change, since the investment only needs to break even rather than growing the economy even further.
Oh yeah, also you now get full employment, like classical economic theory predicts. No more automation scare and feeling like the economy is trying to get rid of you or justify removing working class humans or being hostile to them.
The absence of unemployment makes welfare unattractive, which in turn means that governments will simultaneously have more tax payments and less welfare expenses simultaneously. All welfare should be paid out as demurrage currency in all countries. It's completely logical.
Since capital markets are now fair, it is possible to reduce total debt by paying off loans, whereas with permanent money the holder of money can always decide "I'll spend it later" thereby delaying the possibility of paying off a debt using that money, which is implicitly an extension of the duration of the debt. Given an infinite holding duration, the expected duration of the corresponding debt is obviously infinite too (eternal growing debt woooo).
Oh and it could have saved pension systems if it had been adopted ahead of time. Pension systems collapse because shrinking populations yield less output in the future but permanent money tells you that you can build a time machine to take labor from today and just teleport it straight into the future. Who needs young people working for you, if you can let the money work for you instead! Everyone knows the value of a dollar bill is backed by a humanoid robot inside the dollar bill that can perform exactly one dollar of work.
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
FWIW, we have a similar problem in Canada where the federal government makes large investments and plans that backfire terribly.
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.
Why not parts of the world even? There are more countries than "the country". Some of us here aren't even from "the country".
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.
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)!
The scapegoats for this plan never change and have never changed in human history.
Dying with dignity is never in the cards.
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 took the antithesis of the “great man” theory and ended up believing in a nonsensical version of it - every great thing in the world was done by normal people working 9-5. This is a kind of crude Labour Theory Of Value.
So you see these kind of comments signalling hatred in an attempt to show solidarity. But ultimately it is simply a signalling thing, a way to LARP as an activist because what else might one do as a simple rank and file employee. One wants to have a greater purpose to life and being an activist is a path for 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
When did that happen?
If you can fully automate software you are fully missing the point of everything you can do with that and how valuable it is
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.
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.
Pretty soon we're going to have to reckon with the fact that AI writes better code than us.
Also seems suspiciosly similar to LLM maxxing guys saying things like "this is just like the internet, bro"
Also like someone else wrote in a comment, another aspect is that there is a very large sentiment that this is will crash this time so not sure if it could even crash like before, assuming people werent so aware of the risks in past cryses.
This bet includes you.
It’s actual less than $2T IIRC, which makes my point even more.
Plural implies they count more than the federal government.
you may think she's just your gal but she may be everyone's pal.
In a similar vein with CAFE standards: why were those loop holes introduced? Lobbying by the auto industry.
> 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.
What I am saying is that the paper pushers are allocated elsewhere, they are more miserable and shallow minded now, and they have a corrosive long-term effect on society and culture, even though they contribute positively to economic growth. In way, it is trans-generational debt with extra steps.
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.
1) the single thing you cannot beat is capable teachers. And NOT capable as in able to teach, subject-matter-experts. And that is what everybody wants to avoid at all costs.
Put it like this: an unwashed, abrasive, offensive smelly asshole with a master in math can teach kids math. A super-friendly, nice, beautiful, polite social science major (or not even that) who doesn't know math well cannot. The level of teachers needs to be an order of magnitude above the level expected of kids at the end of the class. Knowledge of the subject needs to take absolute precedence in teacher hiring decisions, to the point that good teachers get rejected if lacking expertise in the subject.
This is not how things work. They only worked that way for a short while due to the crash of 89. I've had a French teacher that couldn't speak more than "some" French. Certainly nowhere near fluent.
2) Money needs to support that. Which means for Math, the money for math teachers needs to be competitive with research departments of banks, and very different for different subjects, which seems offensive to schools and government in general. If teaching positions aren't competing with other professional careers in the subject matter, it will never work. This will, of course, mean that many science teachers make more than a school principal and even a district administrator. Deal with it.
For Math, they are literally not even 25% of that, but even for French it's insufficient.
I believe this to be a heavily US-centric view, Estonia and Finland do not pay more for math teachers than they could get in banks' research departments but still manage to get competent teaching across most school subjects.
Things work outside of the US, the issue is the US does not want to look outside and adapt itself to incorporate what's been learnt from other systems. It's a "do the US way or no way" attitude, and it's slowly eroding to become more a "no way" than any kind of "US way" of doing things.
And I do mean easily beat.
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.
The Nasdaq took 14 years to recover, 17 once you factor in inflation.
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-...
A parallel is when I looked into home births versus hospital births when my wife was pregnant. The statistics of home births crushes hospital births in terms of outcomes. But that's because only healthy women who don't have complications are in the home birth category. Hospitals must admit anyone that shows up in labor, and must handle any negative situations.
Schools now handle so many more kids than they used to, and try to meet the challenge. They are failing because the challenge is too great given the funding, not to mention the corruption of the bureaucracy that inflates administrations.
We aren't incentivizing meaningful work, we are incentivizing diplomas.
What's your own theory ?
I don't think American society has the appetite nor patience for the actions needed for this kind of change.
> 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
We can debate the just access to land (commons) and point to Henry George, John Locke, Thomas Payne and others, but still agree that the value produced by the farm comes from the labour put in to refine the common resource into something more useful.
There can be rent seeking and value produced at the same time.
Edit: One can provably extend the rent seeking parts of the analogy in terms of John Deere and Monsanto
In point of fact a loaf of bread is not significantly cheaper now than it was 40 years ago. What has changed significantly is the total number of participants in the industry is greatly reduced, and the bulk of profits from agriculture accrue to AG services companies. There is no evidence that AI will buck this trend.
Also, some might say that upending the de facto copyright regime in favour of AI companies was an altruistic gift.
Your unstated assumption that investments in AI were private and therefore beyond question simply isn't true.
The AI industry's profits depend to a large degree vast textual corpuses that they acquired and trained on in either straight up illegal or at the least in legally murky contexts; public and private knowledge form the backbone of these enterprises. Said industry then serves AI models to customers via data centers that again off load the cost of inference to the public.
Of course, AI companies could step up pay up their fair share and people will happily treat the prerogatives of private enterprise as private. But until then I think certain quarters of society will continue to believe, rightfully so in my opinion, that AI companies are on the hook for unacknowledged debt.
Of course morality doesn't inform law so the current situation isn't illegal despite how egregious it is. But the law can only attempt to deliver justice, it can't guarantee it. Which is why open, honest, collaborative discussions are important to have exactly now.
Let’s pull on this thread though. This money is investment, in the hope that it grows into more than a trillion.
Right now, this looks like it’s mostly going to displace workers. Some of it will address demand that cannot be addressed directly; you couldn’t afford an editor to look over your emails, now you can.
Much of it will wipe out intern level work across the entire economy, reducing the opportunities for people to learn and develop.
This tech is already devastating education across the globe, and has been built on outright theft of creative work by people who can expect nothing in return.
There was an article on HN how authors of self-help books are seeing a reduction in revenue from book sales, so this is wiping out multiple sources of revenue via automated harvesting of content.
What, precisely, is there to be happy about here? The convenience of writing more code, at the cost of everyone else’s happiness?
There is a LOT better, that could be done with $1 tn.
Not sure you realize how divorced from reality this statement appears (at least to me). These things make fantastic personal tutors for material up though the bachelor's level that are available around the clock and never tire of your inane questions. Currently google offers this for free on their home page without even needing to log in (at least from a residential ISP in the US).
LLMs are found to erode skill
> https://arxiv.org/abs/2506.08872
LLMs have largely been a net negative on human education systems.
If we take peoples' retirement investments, and spend it on puppy dogs and ice cream for veterans and children, we're going to be in a worse place than we started a few years down the road.
Maybe the market will crash. Maybe it will grow. It's hard to say, but that's the point if investing.
None of this is based on anything that stands up to scrutiny. This isn't investing, this is buying the story being sold for AI.
Lest we forget, A story whose bull case, automates the jobs of many people who are currently employed, creating a gig economy for white collar work.
Anyone who is buying this, is buying this for the potential future payoff. The firms themselves bleed money at scales that makes the destruction in outright war look like a responsible use of resources.
From https://www.cyclinguk.org/briefing/case-cycling-economy:
> For every £1 invested, walking and cycling return an average of around £5-6. A ‘benefit to cost ratio’ (BCR) greater than or equal to 4 is considered to be ‘very high’ value for money. Putting this in some context, the predicted BCR for the HS2 (high speed railway) wasn’t nearly so impressive at about £2.30 for every £1 invested.
Probably not. Its better explained here: https://www.mcsweeneys.net/articles/ai-economics-for-dummies
One of the examples from the article: Xavier owns an apartment that he rents out at a loss of $1 billion/month. Seeing this success, he decides to make financial commitments to construct $850 billion in new apartments in places nobody wants them. He convinces Ted to leverage everything he owns to help him build the apartments, telling him that once they are built, every human being on Earth will live in them. Ted contributes $100 billion, part of which immediately goes toward paying off Xavier’s $1 billion/month loss. Forbes gives Xavier and Ted a cover feature, likening their building project to God creating the Heavens and the Earth. Many Fortune 500 CEOs take this comparison literally and establish a new religion around Ted and Xavier, with themselves as high priests. Soon, they start a Holy War with the pope, declaring “Ted and Xavier the One True Gods on Earth” and promising to “purge the nonbelievers” in an official press release. They annex, then subsequently demolish, Vatican City, committing another $900 billion dollars to build new apartments in its place. Forbes hails this as “disruptive,” though it’s not clear how Ted and Xavier plan to finance the project.
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.
chop chop... get to it.
My point is that investment here -- "the outlay of money usually for income or profit" -- isn't just giving people stuff altruistically. Investors, here investing in AI, are trying to get a return on their investment.
They aren't just spending money to spend it.
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
LLMs will revolutionize education for those that care to learn. They will have at least as large an impact on access to knowledge as wikipedia had ~25 years ago.
Also - which kid (or adult) wants to study instead of just play?
Furthermore, Wikipedia (and calculators) were largely free, nor did they come with a side of white collar work automation.
Personally I think we are at the top of the S-curve for this technology. And I suspect a lot of what we see as major recent advances are attributable to improved harnesses as much as any improvement in the abilities of the models. My guess is we will see only minor improvements going forward in the frontier models (barring a major new discovery) and major improvements in smaller models. IMO that is where the real impact will be felt day-to-day, when we can run fairly powerful LLMs in all sorts of places without having to make API calls to huge GPU clusters in the cloud.
