- Tell your employees to use AI without enough training.
- Tell them to keep doing it without enough money.
- Profit!
Ironic
I’ll admit I’m experiencing a degree of pleasure in thinking about how nervous Anthropic and OpenAI must be with their IPOs supposedly coming up.
They’re already billionaires many times over. Hard to feel nervous with that kind of wealth in your pocket
Based on the current valuations of their companies. They will likely remain 0.1%ers, but it will still hurt.
Place your bets
Place your bets
If they weren’t needlessly nervous (by that I mean paranoid), they would not be in that position. Whatever their wealth, those people cannot feel safe.
Idk about that. Musk and Zuck seem like very careless people.
They gotta pull Google and get into the advertising game. They are sitting on a gold mine of private data and I’m sure they know it.
Their IPOs are how they cash out and walk away. It’s just a matter of “does it crash before or after?”. Yes they’ll be anxious about getting there, but the fact the market is still behind them and they’re this close is very bad for the rest of us.
Looks like the market is now trying to get out from under them.
OpenAI already explicitly postponed their IPO somehow hoping for a better climate to IPO in…
A certainly… optimistic expectation.
You should not try to make sense of a decision they probably used chatGPT to make. It’s bad for your metal health
NASDAQ just crested a new high this month, before stumbling last week.
If the death of the tech industry is on the horizon, I can’t see it.
DJIA crested a new high September 3rd 1929 before stumbling 3% the next week.
If death of the market was on the horizon, they couldn’t see it.
The slide being attributable to some "I told you so"s coming to pass may bode ill for the bigger "told you so"s that come due in a few months.
But the market doesn’t act rationally, both going up and going down, so who knows.
DJIA crested a new high September 3rd 1929 before stumbling 3% the next week.
And over a century later, what has become of it?
If someone bought $100 of stock in 1929, how much would it be worth today?
$100 of Krueger and Toll? $0
$100 of the entire DJIA on September 3, 1929 adjusted annually: $13,633
If you’d invested in January of 1929: $16,913
If you’d invested in January of 1920: $72,275
January of 1930: $31,708
It’s never gone to $0
What’s stopping people from using open sourced trained models? Like, why are tokens going to be needed in the future? Isn’t this their whole business model?
You need 200GB of video memory :)
Honestly, I have a little tin-foil-hat theory that the used their infine supply of venture to fuck the memory market to make sure people couldn’t run giant chinese models on solar and eat their lunch.
training a top-level model takes harvesting petabytes / exabytes of revelant data and then months of continuous 100% power on a large server farm costing many millions of dollars.
That was my understanding. So how do local models work? (Been fucking with computers since the 80s, AI is all new to me.)
It’s a one-and-done process, then the normal Q&A usage has vastly lower requirements.
Local models generally means you download the result of all that , after it’s done, (the PT in ChatGPT stands for pre-trained) and then generate answers locally, but the training wasn’t done locally. The generating answers step is called “inference”.
Hardware cost to do inference with a top-level model is within reach of most small businesses. Hardware cost to do training of a top-level model is orders of magnitude higher.
So, there are open-source models that are trained by universities, and then used by affluent but not billionaire people at home.
There are open-source models that can do inference (answer questions) on a typical 8GB gaming graphics card, but they aren’t in the same order of magnitude of quality as the famous top-level models.
Thank you! That’s the best answer I’ve seen on any platform!
What would you recommend as a local model? Want to dip my toes in but I’m woefully ignorant. And again, I’ve done my time in IT, so you don’t have to dumb it down, uh, too much.
The hardware requirements are substantial. If companies or individuals want to run models locally, especially at the speed you’d expect from the big name models, then everyone needs a pretty serious GPU on their work station. That or the company needs to build and maintain a server capable of running whatever loads they expect to see.
None of this is impossible of course. But you pay for the tokens one way or another. Either you pay the upfront cost of the hardware and continuing cost of the electricity to run it, or you pay with the inconvenience of running a model very slowly on lower end hardware, or you pay a subscription for someone else to worry about all that.
This is why local models are still niche. Only hobbyists nerds are willing to go through the trouble of setting up and running a local model. Most companies still are not sure if AI is actually worth it for them. So it’s much easier to pay for tokens than the giant upfront cost required to build you own infrastructure.
If the numbers the AI companies are putting up as far as infrastructure cost vs revenue are anything to go by, it probably isn’t worth it to most companies.
For enterprise, I think same reasons why companies using paid software instead of open software. Someone else to maintain and blamed if something doesn’t work.
They thought they sold tokens, they actually sell marginally (6 months lead) improved models.
If you want it well rounded I can see the argument for enterprise but for me personally I programmed one on my workstation and it’s trained on very specific things I think it barely uses up all 24gb vram I have available.
come on, I’ve trained toy size models too, you can’t seriously say they’re even vaguely approaching the capability of models that takes a whole massive server farm weeks or months to train.
Right, and what proportion of enterprise use cases genuinely need an appreciable fraction of that power (because they are wide ranging and non-repeating)?
Anyone that says these things aren’t impressive is kidding themselves. But how do we get from impressive to productivity enhancing in excess of cost? I find smaller specialised models more plausible on that front, but jury is still out on the financials, we’ll find out I guess!
I’d love more of the msm to pick up these articles.
I need to convince my family this current state of AI is just smoke, mirrors and debt, but i need a normie-credible source to anchor it.
Does anyone know of one? Guardian would do.
MSM is too scared to talk about these topics. If the AI companies fall, the global markets will crash. Banks lend out too much money to those companies, same for retirement funds and the owners of those media.
This might be a case of too big to fail and “look out China will use it to destroy us”. That’s what those AI companies are betting on at this point. Their last hope, apart from continuing the deception for as long as possible.
Why do you need to convince them?
I don’t want them to plan their lives around it. My brother is thinking of switching career and my parents have some investments etc based around line-go-up.
But also I just look like a conspiracy guy until the bubble pops, but then im the “i told you so guy” and that sucks.
I would just tell them to think long term instead of focusing on the new shiny thing. Software development is still a perfectly valid skill to learn, and if your investments are in tech ETFs or mutual funds, they’ll be managed and hedged against avoid losing a significant amount of value.
If they still want to chase the shiny thing, you can’t logic them out of an illogical position. All you can do is recommend they have a fallback cushion, and only invest time/money/effort that they can afford to lose.
“hedged against… Losing a significant amount of value” boy do I have bad news for you about the ETF industry.
Can’t wait to see this exact headline another 50 times but none of the companies in question facing any consequences for their actions, profit driven society is so fucking stupid.
The consequence is that they waste money and time. Which actually matters for businesses strapped for money or time. But most of the megacorps are swimming in money and in time. They waste those all the time even without the AI because the upper management accepts kickbacks to contract with the worst (but also the bribiest) contractors. And mid management, and everyone else, put their own personal interests ahead of the company’s. Now that the AI hype is here, they have a new tool to waste time and money with, but nothing has fundamentally changed. Big business is a lumbering inefficient bureaucracy by its nature.
they cut our copilot budget to 19€ per person (you can request more. but of course it’s a hassle)
they still insist AI the future and more AI is better. they are just now shifting the blame to employees: “you need to think more about how you use it”, “you cannot just throw tokens at a problem”, etc
two months ago I got an email from a manager asking me why my AI spending was so low.
€19 sounds like a per user subscription deal, but I didn’t think they were available to commercial customers anymore? What am I missing?
it’s 19 USD, not €. got confused. I think it’s this one https://docs.github.com/en/copilot/concepts/billing-and-usage/organizations-and-enterprises/seats-and-billing-cycles
Wait, we’re not tokenmaxing anymore? So when the AI salesman said to make a leaderboard of people spening the hardest, it was to line their own pockets with cash? Huh. Color me surprised.
So next, you’ll tell me that it costs more to have an LLM produce the same quality of code as a senior developer.
sounds like they are creating another excuse for another round layoffs.
AI is coming: Time to lay off people
AI is costing too much: Time to lay off people
they are already in the middle of one. (huge It consulting company)
But you better keep that output high. In hindsight this was so obviously gonna happen
At our company, 12 months ago they said everyone wasn’t using enough AI. They even made a leaderboard to see who was using the most tokens in the business and encouraged more and more.
A couple of months ago, everyone’s AI spend was restricted to $100/month without warning. Entire workflows broken overnight because people had built theirs around Claude skills that used stupid amounts of tokens.
Now they’re starting layoffs. Go figure.
now they are laying of staff? What, did they blow their whole budget out?
They were burning over $250k every single day. So yeah, gotta pay the reaper I guess.
I tried AI-everything (apart from code review of course). But it’s just too hard. Letting the AI do bigger things results in subtle, hard to find, but devastating design fails and errors. It’s fractal. No matter what layer I look at, it’s always sort-of working but also bugged in subtle and sometimes hard-to-fix ways.
So I don’t do that. Instead I use the AI as an assistant while I still do most of the actual work. I downgraded my account too because I never reached the limits for a while.Ding ding ding. It’s fucking GREAT for eliminating the menial bullshit like scaffolding, data cleanup, sifting through overly verbose documentation… Anything that requires abstract thought still needs to be done by a human.
January: We’re going AI native, please use AI as much as possible.
March: Everyone needs to attend workshops on how to maximize AI productivity.
July: Some models are only available for special (properly justified) cases. Speak to your manager. Turns out that some people did everything (even commits) with top cost models.
August: Ok, we’re setting some limits on token usage, due to some people spending 1000% over the average.
September: we are creating additional frameworks and limits to AI use.
It took a bit of time for the actual AI cost/benefit to reach the top management and put some hard numbers in contrast with the hype machine, but it’s happening.
Keep spending that shit left and right!
My company is at the July stage. Who knew giving people unrestricted access to Claude enterpise with no training would blow through budgets in days
Our management is so “forward-looking” that we are still in the March stage: they want AI used everywhere, and added everywhere in the product.
Saying that sometimes you still need to use the brain for big decisions will make some people question your prompting skills publicly.
Hell, we even rebranded the whole company to be an “”“AI company”“”. I hate it there and I sense layoffs coming soon, but finding a job in this period is hard. Wish me luck.
Still in March over here. My management is pushing hard for us to start doing shit in copilot, and I’m humoring them, but I’m looking at current news with a very Ralph Wiggum “I’m in danger” mindset
Everyone who was paying attention even a little bit has known this would be the trajectory from the beginning. And we haven’t even gotten to the crazy price hikes per token that are coming.
And we haven’t even gotten to the crazy price hikes per token that are coming.
Why do you think that?
IMHO, API prices are likely to drop over time as we scale up and efficiencies are found, combined with general pricing pressure from the competition… SOTA models will continue to have SOTA prices, of course, but reasonable priced distilled and open weights models are already common.
A consequence of API prices dropping is that “heavily discounted” consumer plans will also adjust and won’t be so generous relative to API prices.
IMHO, API prices are likely to drop over time as we scale up and efficiencies are found, combined with general pricing pressure from the competition… SOTA models will continue to have SOTA prices, of course, but reasonable priced distilled and open weights models are already common.
Some of this seems like wishful thinking to me.
“as we scale up” We already have large data centers, and, if anything, “scaling up” is just driving up expenses for debt and hardware. The real problem with AI, relative to the internet boom, is that the more you use it, the more expensive it is. The economies of scale to be taken advantage of are minimal.
I do think price of compute will come down, but exactly because people will be running their own open source models on their own hardware instead of Sam Altman to stack GPUs in a warehouse, but it will still be too expensive and inaccurate.
And we’re still headed for a financial cliff in this scenario.
Of course they want to turn the corner and ideally keep all their infra, but they might need to restructure their debts if/when the creditors come knocking.
BUT: they have a money printing machine with inference… Enterprise is where most of the money is made, as they pay (closer to) API prices… consumer & small business plans are heavily discounted in comparison, with mostly underutilized use-it-or-lose it plans. They’d be stupid if they were making an opex loss on inference.
As for why API prices are dropping? Competition is a bitch… but they seem willing and able to play the game for now.
If we’re talking about the survivability of AI as a technology, I agree.
If you’re talking about the viability of the hyperscaling business model, I think we are looking at wildly different sets of information.
Like a fraction of a percent of people will run their own models. It won’t influence price. Remember that coders/tech people are only a minority of users.
Oh, I see. I was mistaken. I thought tech companies were OpenAI’s major customers, and they certainly could make their own data centers for internal work, and that coders–that minority of users–were the only ones likely to pay full price for tokens, the rest of us wouldn´t be willing to pay full fare for a machine that is right most of the time sort of. Thanks for setting me straight on that.
Some large companies do it … but I think you greatly overestimate the willingness of large enterprises to build and maintain their own infra. Once a company has lost the competency (and many have), it’s hard to get it back. There are always pockets of people with the right skillset in a large org, but they mostly don’t want to do DC work anymore. Team/personal servers and beefy laptops, otoh…
Because these companies started selling at a loss from the start to get people hooked. Neither Claude nor OpenAI are turning a profit right now.
The biggest problem isn’t cost of running the models right now, the biggest problem is all the debt they built up on training and data center buildouts. That’s what they need to recoup and that’s what’s going to drive prices up. And once it’s recouped they’ll need to make pure profits.
And I hope that debt kills them because all the big AI companies are terrible in one way or another, and the eventual price disparity will make it uneconomical to use their models. Then we might return right back to development focusing on small models, not large ones.
And I’m sure you’ve noticed how all the revenue and profit numbers that leak out ignore “one off” costs like training and data centre building.
But look how dangerous these models are. They need to be regulated so that only responsible closed model providers can produce them.
Just ignore that the responsible closed model providers are the ones opening their sandboxes and training their models on blackhat sources.
They were supposed to do their IPO and have positive cash flow already. Time is running out before investors are getting antsy and there’s no more money available for scaling up.
They gobbled up the easy money… now they have to work harder for more, and yeah, they may have to slow down a bit and embrace fiscal responsibility… I expect to see restructuring of debts along the way, but I’d be very surprised to see any of the major US based players implode.
Both Anthropic & OpenAI have debt repayments coming up in 2027 that:
- cannot be restructured
- cannot be postponed
- they absolutely cannot pay back without even more VC money, and that faucet is being cut off right now.
I feel like we’re co-workers, with how perfectly that timeline matched the day-job’s progression.
We’re at “did you take the seminar on looping that uses tokens like a firehouse so you can use less tokens? Why are you using too little (/not enough) tokens, and why is it not magically 10x-ing all of your (fucking ansible) config?” Or some shit.
Do we work at the same company??
I think this was the standard management reaction across all the companies that embraced AI as if it was the second coming of Jesus Christ.
C-Suit are herd animals. Same schools, same country clubs, same conference. They all are formed the same. And they don’t take advise from people who earn a few orders of magnitude less.
Fortunately, the people above them care about numbers, and these don’t add up.
They thought it was their ticket to fire everybody, and the more they made you use it the sooner they could fire you.
Soon, the guys upstairs will realise that the real savings are in replacing the middle management with agents, not replacing the workers. Fingers crossed.
That will just become a different kind of hell
I don’t doubt that for a second, my friend.
I was a PM at a major now-hyperscaler and one of the engineers on my team was pretty vocal about PM not contributing.
He ended up leaving for a team that didn’t have one. A few years later I happened to be in his new building, he saw me, and came up with this huge grin on his face, “oh wow are you joining our team?”
You always hate the chick writing the specs until you don’t have one any more. 😂
No no no. Most companies already knew this. Most bosses just pretended it wasn’t happening so they could ride the bubble and bonus themselves… We all said this was what would happen, and it did happen, and only complete suckers would still have fallen for it. Of course some CEOs are suckers, but many of them are simply greedy.
We all said this was what would happen
They only listen to people who’s wage or billable hours are close to the order of magnitude as their own.
You mean malicious compliance works for the mid management too? I believe it.
Management spent two years demanding everyone use AI, then discovered everyone was using AI. Now they’re shocked the office is a conveyor belt of hallucinated PowerPoints reviewed by other bots. The real productivity breakthrough will be executives learning that buying subscriptions isn’t a business strategy.
Yeah, turns out the executive class, the would-be nobility, are incompetent idiots by their own standards, and are primarily driven by their own malignant sociopathic narcissism, not any of the stories they tell about themselves.
If you want competent executives, they’d need an actually effective selection pressure that punishes incompetence and rewards competence… but they already destroyed that.
So, either we, or somebody, builds some mechanism or system that does that… or they all preen themselves rigourously while steering the ship directly into an iceberg, with all of us onboard.
They will genuienly not understand why we hate them for killing us all.
I just wish my company would start hiring again. I have been using the AI out of necessity, because we are short-staffed in certain areas. I’ve asked several times, directly, how much my AI use is costing and nobody is in a position to know. It’s certainly helped in some areas but I want to build a case that hiring a college grad or two can help more…
Being short staffed is the whole point. They believe (where they are right or wrong) AI will replace large number employees. For example in my company where that are pushing vibe coding, my boss said that now they believe that the large projects need less people.
If you use AI and still have to work overtime you are your own problem. As long as you deliver why would they change anything? Don’t deliver. It is not worth sacrificing your health for someone’s else’s profits. You have only one life.
I see people who embraced vibe coding still working overtime and over weekends, more than before.
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Careful they might just hire two AI using interns to replace you. Maybe bad mouth how much the AI is making mistakes and get them to make you stop using it and then ask for help when production slows.
This just in, Management are complete morons. Film at 11.
Trend chasing upper class idiots
This. You’d almost think people are dumb enough to blame bad management decisions on software.
Ernst and Young say 36% of companies using AI have experienced catastrophic incidents.
Hopefully some of them go bankrupt. That would be a stellar way to get rid of some bad management.
Hahaha. No. Management is not losing jobs over this. Not in the quantities needed.
If anyone important does get fired they’ll just get re-hired by another company who needs some doofus to fill a position in upper management.
“And why did you leave your last job?”
“The company went bankrupt due to severe mismanagement.”
“How did you get your management position at that company?”
“My dad was rich.”
“You’re hired.”
No I know it’s a mostly futile hope.
get rid of some bad management.
Good luck. Like cockroaches, they’d probably survive a nuclear holocaust.
Is it because they turn bad once they become management? Or were they like that from the beginning?
Personally I think it’s both, but mostly the latter.It’s a feedback loop.
Upper management can’t tell what good work is, and thus whomever is the most shameless in talking themselves up wins, unless they royally screw up in a way that can’t be missed. If you have any shred of humility or nuance about your work, you are almost certainly not management material.
I have met like 3 or 4 people that I actually had respect for in management roles, but overwhelmingly they were there solely on an overinflated sense of self importance rather than substance.
It also attracts narcissistic people without empathy (and sadic people), a bit like the church attracts pedophiles. Not everyone is, but in the end it’s too many (over 0).
It also attracts narcissistic people
This has AFAIK actually been documented.
If you have more information about that, I’ll be all ears!
I wrote AFAIK, which means I don’t have a source at hand, only memory of having seen the claim documented by research somewhere…
It is well observed that psychopaths (a.k.a. sociopaths) are found both in prison and in managerial positions.
That comment is made by a PhD psychologistm and confirms it.
Feel free to investigate further, at least you now know there is something for sure.
Both. Whether you’re considering empathy or competency.
Increased power—in pay or in authority—may be followed by decreased empathy (they turn bad). Conversely, dark triad traits have been linked with success like promotion to management (they were bad already). The research on this side has been criticized, mainly for methodology. I think the underlying idea makes intuitive sense.
On the competency side, there’s the Peter Principle, originally satirical but subsequently researched. Good employees are promoted to a position of incompetence (they turn bad, or rather, are promoted until they are no longer good). Or, they were incompetent and promoted anyway to get them out of the way (they were bad).
And the mechanisms are not mutually exclusive. E.g., a good employee is promoted, they are bad as a manager, then entrench as their new authority leads to less empathy.
Frankly, I think we all have a bad manager inside of us, and the problem is that being put in a manager position exposes you to humanity-draining incentives that feed the bad manager parts of you, until it defines you. Higher compensation and promotions for focusing on costs and not quality, and short-term gains rather than long-term stability.
If you’re unusually self-aware and smart, and put effort into grounding yourself, you may counteract it, but most people probably just float through life and let those incentives define them and their choices.
Interesting point.
Both. People who are promoted to management because they are good individual contributors are often lacking in management skills (they turn from something they are good at to something they are bad at), and people who crave and hard pursue management positions rarely have management skills (always bad).
That sounds extremely plausible. 👍
I think they get promoted to management because they’re bad.
They’re not going to promote the guy who knows what he’s doing, because they need him to keep working in his current role. The guy who slacks off, bosses people around, and gets chummy with the boss though? Perfect candidate for promotion.
is that guy yawning
I think he’s waiting for someone to insert a penis into his mouth
Alright, I’ll do it…
Careful… lots of teeth showing
We are ruled by idiots. It’s probably been that way for the majority of history.
Most places I’ve worked, management has been a negative force.
Management is good at accumulating and maintaining power. Competence in actually getting stuff done doesn’t really help with that.
Competence would require pointing out flaws someone else is responsible for, which would certainly enganger your career eventually. So, not only is competence unnecessary in management, it is actively selected against.
