- cross-posted to:
- usa@lemmy.ml
- cross-posted to:
- usa@lemmy.ml
cross-posted from: https://lemmy.ml/post/54396848
If you want to know whether artificial intelligence is a gigantic economic bubble, don’t just take pundits’ word for it. Major investors are now moving their money to try to protect themselves from the AI bubble popping.
For an industry that we’re told is central to our collective future, the artificial intelligence (AI) industry increasingly seems to be built on a combination of artificially inflated hopes and bad accounting.
The industry’s critics have been raising concerns about its finances for a while: the fact that most of its flagship firms are grossly unprofitable, that they’ve had to jack up their prices to try break even (leading their business customers to pump the brakes on using their products), or that many of the eye-popping investment announcements that are meant to show demand for AI is strong have actually been circular financing — meaning different AI firms cycling money to and from each other.
But none of it has seemed to slow the industry’s boom or the relentless hype machine behind it. Until now, anyway. It used to be that you mostly heard concerns about the industry’s underlying economics in newspapers, blogs, social media posts, and podcasts, and that those concerns went completely unreflected in the markets. But these concerns seem now to have finally bled over into investors’ thinking.
You must log in or # to comment.
If the banks desperately want to sell you something, you know it must smell fishy.
They want to get the growing risk out of their portfolios, and when other banks and investors don’t want to take it, they try to find idiots in the masses instead. In Germany, they had the word “Volksaktie” (shares for the common people) for it, and yes, it was about the same, even though back then there still was some substance behind it, and not just greed and unfulfilled contracts like with the AI bubble.
You know, when I paid 2k for a graphics card during the shortage. Maybe that was a good indicator that building giant warehouses using expensive and hard to make components was probably not the best course of action.
I have removed every dollar of my money from anything that is directly involved with AI.
they are keeping the grift going as long as possible,
The grift that keeps on grifting
This is what happens when investment is done on possibility rather than reality.
on ASSUMPTIONS, that dint have a viable product before hand.
Not just wall street, some of the pro-slop people in my work are getting increasingly desperate and unhinged.
They formed an ‘AI native team’ to develop ‘groundbreaking new applications’ more rapidly than our dumb old software development teams are doing even with AI tools available.
The logic: Obviously software development skills just make the developers too opinionated and they stand in the way of AI.
The problem: After 6 months, every single vibed up slop project has failed to get through QA, and the developers can’t get AI to address the issues QA is reporting (similar stuff as people have been reporting with the slop-clones of Office and Photoshop, UI elements that fail to do anything despite looking like they should, the software doing one thing when it was asked to do another).
The proposed solution emailed out: QA obviously is a problem getting in the way of the slop the customers clearly want to pay for, so we should consider skipping QA and working with the customers instead to fix it. I’m hoping this is the line that executives won’t cross, most of them have been chewed out by customers enough over more mundane fuckups that they could see what a shitstorm it would be to skip the only thing protecting us from shit.
That’s unfortunate. But less unfortunate than it could be.
The problem with pure vibecoding is that it can get really flashy results up front, just enough to impress and get green lights. But it’s completely unsustainable outside the simplest projects. At some point, vibecoded stuff gets issues, or one realizes certain features actually aren’t working, and no one can fix them.
In other words, it’s great that QA is already catching the issues. Because they could have quite possibly vibecoded something functional, passed through QA, and ended your separate effort, only for it to collapse later.
Note that I am strictly talking vibecoding, though. I know it’s not a popular opinion in this sub, but more mundane LLM “chore automation” is far more practical.
I was ready to type “just fire QA and have the LLM do it” then I read the last paragraph.
I’m hoping this is the line that executives won’t cross
Hate to be a downer here buuuut…
As a former quality person this is everywhere. Manufacturing has basically relegated QA/QO to be task based (reactive, paper pushing, etc) and removed from the process completely unless deviations occur (which they do all the time, go figure).
The further you are from the product the less value you have.
Wow.
That’s next level FAFO
i know a pro-slop in my immediate family, he would refer to chat gpt as a way to solve whatever question he was having.
QA obviously is a problem
Oh lord…
The more things change the more they stay the same.
If shit rolls downhill QA is at the bottom and I’m saying this as someone who comes from Ops. I deal with the shit when it hits production.
Truth of the matter is in any org it goes like this
Devs - literally walk on water. Give us new and shiny things
Ops - support the half baked shit that devs promote to prod on lies that “it’s production ready we will fix in future sprints”
QA - magical role that is never filled because “we can just get devs to review their own code”
Well, they’re right.
“If we stop testing right now, we’d have very few cases, if any,” Trump asserted, “Without testing, or weak testing, we would be showing almost no cases.”
No. No? You kidding?
In case you weren’t being sarcastic: Yes, that’s a direct quote from the Paedophile traitor, the Fuhrer in Orange, shitlord of Hamberder.
He claimed that the only reason america had COVID cases to report was because we were testing for them, stating directly that testing was bad for publicity.
Not sarcastic: aghast. It’s so hard to know reality from the Onion.
Covid kind of exposed how he operates.
His problem was that the virus did not pay attention to the media or care about politics.
Moron downplayed it because he thought it would hurt his reelection chances. If he had leaned into COVID and mad a huge public commitment to fight it he would have sailed right back into office.
And if you know how few of the real problems QA normally detects before a product is being shipped to the customer you know the shit show that those products will cause.
Hand me the popcorn, that show has a lot of potential.
One early example I heard about slop code being bad was that if you have a process that is repeated, an LLM will not write a function that is broadly scoped so it can handle a significant number of related use cases, it will write different code for each instance, so when that process fails you have no idea which version is responsible. Seems like the kind of thing QA would flag.
I’ve never known QA evaluations to be design-based, only results-based. They would test each of the cases and reject the code if it failed any of them, but they wouldn’t check for or reject the code just because it was handling them in stupid, non-generalized ways.
Checking for bad design is more of a team lead code reviewer thing (if it happens at all).
Way back in the oughties I worked on a consumer electronics project where our QA guy actually used the product, would come to design reviews, and filed bugs about the UI design confusing the user.
It was awesome, so of course that job got eliminated as soon as possible.
I would still call the user-facing look and feel of the UI more of a “result” in the sense I’m using it, though. When I said “design” I was really talking about the internal implementation that someone not looking at the source code would never experience.
It doesn’t necessarily hurt for QA people to have access to the source code, but they shouldn’t need it to do their job.
Some of the devs in my team do this occasionally and it ALWAYS eventually causes issues
If QA hadn’t been replaced with a chatbot, that is.
QA obviously is a problem getting in the way
Tbf, QA being seen as a problem slowing things down is nothing new in development. AI just gives it a new impulse.
The same thing is happening in my work. Just as we got the higher ups convinced that yes, having QA is very valuable, we get called the bottleneck again because dev is supposedly speeding up due to AI (according to dubious metrics).
The proposed solution emailed out: QA obviously is a problem getting in the way of the slop the customers clearly want to pay for, so we should consider skipping QA and working with the customers instead to fix it.
Narrator: the people who agreed to this never interacted with a single customer.
Well, so far, it’s the “I’ve bet my entire career on AI” leader who has not yet gotten traction. He had a large benefit of the doubt but I feel like leadership is getting more and more skeptical about him and his band of merry sloppers.
The problem: After 6 months, every single vibed up slop project has failed to get through QA, and the developers can’t get AI to address the issues QA is reporting (similar stuff as people have been reporting with the slop-clones of Office and Photoshop, UI elements that fail to do anything despite looking like they should, the software doing one thing when it was asked to do another).
- Is AI imploding within itself through poisoning and no new content?
- Are they putting in their own guardrails to take away the really good innovations because of greed?
- AI was never as good as they claimed, even the super advanced models?
- All of the above?
I’m more curious than anything. It seems to be getting worse for the free models.
Is AI imploding within itself through poisoning and no new content?
Model collapse doesn’t retroactively affect models that have already been trained, so this option seems like a pretty nonrigorous belief
Are they putting in their own guardrails to take away the really good innovations because of greed?
This would be difficult and likely counterproductive, but they are known to adjust the amount of compute they allow models to use, so they could be throttling that
AI was never as good as they claimed, even the super advanced models?
Ding ding ding, we have a winner! AI has improved, but those who are selling it will always and forever oversell it, like they would with any product.
I’d say it’s never been as good as Musk and Altman especially make it sound.
If you drill into the nuance of their proof points that their companies bother to share, it’s generally a bit more clear that things aren’t exactly ‘asterisk free’ even then. Most recently I read how one of them proudly proclaimed they were 100% manual code free, but for the task described they still had 200 developers, which is significantly more developers than I have traditionally seen. To get things vaguely working, you need to be relentless in providing a super comprehensive set of requirements and criteria that are impeccable at fully capturing what is needed and could reasonably go wrong. Also a fanatical amount of detail to audit how the solution was reached and correct missteps, like when it decides to delete a failing test case instead of fixing the correlated problem. The ‘purist’ approach is, in my opinion, worse for the sake of just signaling how ‘AI-friendly’ you are.
I can at least buy that from a pragmatic perspective, the codegen can accelerate things if used under a more balanced approach, being able to be in the code and grasp in detail where it might have gone wrong and correct it before it gets lost in a mess of garbage. It will do things that a human might skip that they shouldn’t, like hooking various unlikely errors and providing a nicer treatment. It is often useful to get a general idea of a good choice of library to do something and how it fits in your code, though you still have to beware that it may invent details that would be nice and convenient, but are wrong.
The problem is that narrative is totally not what they need to justify the spend. They needed to take randos and prompt up things without full understanding. They needed AI codegen to be really valued on the same level as a full headcount. This trickles down to little folk like the team lead in my situation, where he thinks this is his only ticket to the ‘big leagues’ if he manages to drive a success story for ‘AI native’. He doesn’t understand any of it and his team doesn’t understand any of it and so of course the AI can’t bring what actually understanding the scenario would.
Even more rough for that guy: he imagines a world of slopping up code and then selling the result, without ever having unique skill or insight. Assuming that can work, then why would any company buy your slop instead of just slopping it up themselves?
Remarkably well said. I don’t have much of substance to add, but it is funny to me that:
To get things vaguely working, you need to be relentless in providing a super comprehensive set of requirements and criteria that are impeccable at fully capturing what is needed and could reasonably go wrong.
is basically describing what programming already was.
AI is the new COBOL.
I have found AI to be great as an extra pair of eyes, organizing, and finding obscure sources. So it’s a great assistant, not creator. You have to know what you’re doing.
It’s like sending a fresh set of very smart, right out of school, employees to do the job. They have been trained to do everything you want them to do and more, but guiding them takes expertise. These recruits can’t do it on their own, they need a leader.
Are the companies understanding this, or is greed blinding them?
Heya colleague!
working with the customers instead to fix it
Ow, my sides!
Moving QA to the customer base is straight Microsoft.
Might be an idea to start looking at vacancies in other companies. Just in case yours goes nuclear on the stupid.
As someone who went through the dot.com bust at a very unfortunate time in my career, I’m always looking for the escape hatch.
But I feel like the prevaling opinion in the leadership guy is increasingly dubious of this guy, so I’m hopeful sanity prevails.
Damn, I wish I could see the results of this inevitable shit storm.
CEOs and Boards will constantly fail on the model that demand, money and technology will scale indefinitely.
One of the “leaders” of the industry posted an $80 billion loss this year. Wall Street is not nervous enough about AI.
An $80 billion loss so far. That was only for the first half of the year!
I agree with the general story but that example is not a great one, 90% of it is an accounting adjustment as a result of their share price going up. This would actually happen in a case where a company was being successful. What happens is the startup gets say $100m in cash in return for 1000 shares, valued at $100 each. Then later when the startup is doing well their share price is now worth $500 each, they still owe the same number of shares, but the value of the shares they owe is now $500m, so on paper that is a $400m loss. They don’t actually pay or owe that in cash, they just owe x number of shares to the creditors, which they have to hand over at some point. So that is not actually a direct problem with the business model.
But otherwise in general yes it’s a house of cards
That’s not how shares work at all!
You can’t turn them into the company at market value, you have to sell it to other people to cash out. The only time a company buys its shares is when they do a buyback, but that wouldn’t be a debt on the balance sheet.
The shareholders are just the company owners.
Well the description is literally what is behind the $72 billion reported loss
That’s not the case with anthropic, though. They are simply burning money while not making a profit.
Number of AI companies making a profit: 0
(No, NVIDIA doesn’t count)
The specific example you used, of Anthropic’s $80 billion loss, does match the explanation, though. It should be closer to $8 billion before the accounting adjustment, which is still a loss, but the other $72 billion is just numbers changing in a spreadsheet, not actual cash going one way or another.
The financial inbreeding didn’t trigger any alarms?
The red flags have been waving, alarms have been going off, everyone with two braincells to rub together can see this is a ponzi-like scheme of circular financing paired with extreme market concentration.
Wallstreet doesn’t care. This level of incompetence considering almost everyone with retirement is tied to this is just too much to believe. Firing everyone in charge and preventing them from ever working in finance or even a leadership position for the rest of their lives should be the absolute minimum of their punishment for this complicity. If they spoke out early and took action, we can exempt them. Otherwise it is time to clean house.
more like financial cannibalization in favor of the AI hype, sacrifice all your other business ventures, or employees for AI.
Imagine when that bubble pops and AI goes back down to “tool” level, and everyone goes back to work with a brand new dislike for work.
Even its tool status only exists because these companies subsidize the cost. In the event any survive the pop, realistic costs would price it out of being a frequent tool for typical workers.
A lot of people are getting addicted, though. I have the sinking feeling they’re trying to keep this going for as long as they can so there’s enough addicts who will then sink their savings to get their fix once the bubble pops.
That addiction made me wonder. Is it possible that AI was secretly used for disinformation on social media? I see some similarities.
i know a person that is addicted to it, use it to do every job searching, resume, his other personal problems.
I think technology will catch up and AI models will improve to the point where we have whatever ChatGPT is using at the time of this comment running locally on regular hardware.
That’s not saying the industry will die out of course, just that homegrown will be a real option.
But that’s not solving any real problems.
That isn’t really compatible with this timeline because these companies are spending trillions of dollars building data centers, which serendipitously is extinguishing any hope of buying local AI hardware by cornering the market for GPUs, RAM, CPUs and both solid state and platter hard drives.
The implication of this all is that we will rent compute and run nothing locally. If hyperscalers succeed, that is the only way they make their money back. And if we will be able to afford local AI hardware, that also means they must fail.
I’m pretty sure the earth will expel us long before AI has a chance to do it. 😭🔥
Win win?
I don’t see how that’s a win for anyone except the assholes peddling AI.
Yeah, schedenfreud is nice but it is not a filling meal. Seeing AI addicts get taken advantage of can make me smug but it cannot make me happy. People are still being exploited.
Idk, the cat is kind of out of the bag here with local open-weights models. Even if all the providers shut down, someone who really wanted an AI could use one of those with not too much effort. A good model would require some impressive hardware, but a bad one is “good enough” for some people.
I’m not talking about personal use.
Ok, why do you expect providers wouldn’t use cheap open models if they can’t sell the expensive ones?
They are profitable on inference (at least anthropic). Inference is cheap, it’s not susbsidized. It’s training that’s expensive, but if the bubble really does pop then current open source models (which are pretty much sold at inference rate + small margin) will actually go down in price since the cost of hardware will have gone down (assuming less demand for GPUs). Considering that the current best open model is roughly one month behind, we won’t revert to pre-ai anywhere. It’s just too cheap for that.
Still, it’s lovely seeing people spreading misinformation based on something they saw on tiktok years ago. Keep up with the times or don’t spread outdated info.
Yeah. That $80 billion loss was all for training I guess 🙄
Well that and the fact that they have a company to run and people to pay. Do you seriously believe inference is not profitable, despite evidence to the contrary being everywhere you look?
It’s not exactly $80 billion, $72 billion of that loss is accounting for the rising valuation giving early investors larger paybacks, aka Google and Amazon. The same people who give Anthropic its compute, at a very very healthy discount, are the ones who benefit most from a high valuation.
Only for the hyper scale centralized compute llms. Real machine learning tools predate and will persist past the bubble pop, but data center cloud based llms will go the way of the dodo one way or the other. Which is a disaster for the big companies that want to sell you compute as a utility, but really totally fine for most everyone else.
And none of those are “tool” level for the average company, so it’s not what’s being discussed.
Why not a local model on owned hardware?
Because the hyperscaler cartel is dumping cloud AI below cost, while simultaneously buying up essentially all the RAM, in order to deliberately and artificially destroy the local AI market.
Because its more expensive than openAI giving 90% discounts.
I don’t think businesses want the overhead, but maybe some will. The capabilities will be much lower, though. The subsidized costs are high because of the hardware and power needed to generate the content it does. Companies willing to upgrade to comparable hardware and oversight would probably be just as willing to pay a higher subscription. Also, I would hope any company considering it would be able to see by then that the results aren’t worth the costs.
I am now wondering how would it be nicer to have a local scheduled solution, an LLM as an office printer. Slow moving common queue that makes people get more conservative in their LLM usage, plan it’s rent for themselves, send inputs to have outputs later that day. Some inconvinience to tone down hardware costs and establish a more mindful consumption.
It could be fun to run experiments with that as one of test groups, and others unlimited or limited in some way, to compare how people adapt and how it affects workflows.
I dread to find out what the new thing will be that will distract everyone from the actual problems. Brain-computer-interfaces?
Oh musk did that one already. That’s why he has helpers ;)
Robots, flying cars, quantumAI, Epstein Files…
I look forward to LLM brained techbros having their paychecks be left behind
Even that chart is unintentionally misleadingly optimistic for AI, since it’s showing nearly a trillion dollars in revenue. Nearly all of that, however, is from hardware suppliers like Nvidia, Micron and AMD. That number should be revenue for the final AI services only and hardware suppliers should be a different category.
You can’t claim digging for gold in a gold rush is a profitable profession by counting the money you pay for a shovel as income.
Looks like selling razor blades is profitable while the others are still trying to improve their brand of razor.
I think with that metaphor it’s selling steel, and what everyone’s trying to desperately forget is that revenue is peaking and the steel they spent so much buying is, by design, disposable.
deleted by creator
Corporations pretend to the public that their business is providing services when in reality their business is making profit. Corporations are just starting to realise AI research has pulled a similar switch on them, it pretended to be in the business of making profit but actually its business was something else, something about switching the means of production.
My conspiracy theory is that investors are letting the air out of the bag so that democrats will win and give everyone bail outs.
wouldnt it be more useful for them to bet on gop, who will be forced to bail out, more likely to. with Ds, its wishy washy.
