I’ve been saving this video for this particular moment
between anthropic going ipo for cash and this, I think we’re seeing the edge of the bubble
can’t do good business with bad people.
The slop is now prohibitively expensive. Good.
Every single person who mentions using AI for anything- any reason at all- all I can do is imagine what face they would make if I spat in it.
Actually it can be a very useful tool, if you know what you’re doing. Expensive in real terms, so only for tasks which are worth it. So perhaps not for making annoying cat videos.
rumbles throat
Local AI it is then. Not that I’m using all that much now anyway…
To use one equivalent to Claude Opus, you need like 800GB GPU memory. The chips that will get you there run $20-30k a pop, and you’d need 4 or more of them.
That’s the biggest baddest model out there. There are models that get you 90% of the way there with a significantly smaller parameter count and thanks to MoE offloading you don’t need the entire model active at once.
A 5090 and a beefy CPU and tons of RAM won’t be cheap or even affordable to most, but you could run very big models and have a beefy PC for other activities. But even a 16 GB card could do plenty.
Yeah, I’m aware. I have realistic expectations and I’m looking into running something simpler and less demanding.
Where I work, Chinese models are banned due to legal concerns. Not just in production, on any company-owned machine. That basically eliminates all the decent open weight models. I’m imagining this type of policy will be more widespread. I suppose it’s because of the potential for legal woes if systems and people are dependent on these models and then federal or state laws impose harsh penalties with little time to react.
I meant for private use.
As for work, we do use AI quite a lot and I don’t have a say over what’s available.
Copilot? Copilot.
I’m sorry, did everybody else not see this coming from miles away? This is the private equity playbook.
- Make a service so cheap as to seem to good to be true to attract customers.
- Gain a loyal base of people
- once theyre locked in, squeeze them for all they’re worth.
When something is too good to be true, you ALWAYS have to be ready to either jump ship, massively change how you do things, or pay through the nose.
The angry devs from this article are idiots
I have some sympathy for these people, but some don’t seem to realize that Microsoft is not going to be upset over them leaving. They are not valuable to Microsoft as users. If they are unable or unwilling to pay now, Microsoft wants them gone. They are being shown the door. Making a post about deleting your copilot+ subscription or whatever is like bragging about being kicked out of a nightclub.
Yeah - people are talking about replacing jobs with AI. As if it is not totally obvious that people like Sam Altman will totally bleed you dry after you fired all your workers. You will not save on your wage bill, you will simply give the money to Sam Altman
Wages are treated as an immediate operational cost, while AI is framed as a capital investment. This accounting distinction makes AI look like a long-term asset, whereas labor remains perpetually categorized as an expense.
Only if you are running your own servers. You dont get to depreciate a SaaS subscription or metered bill.
And the servers are only useful for AI and they don’t last long.
I’ve been preaching this for the past couple of years. Everything up until now has been entirely about gaining market share, and AI will never be cheaper than it is right now, and it’s not cheap.
Just look at the “earnings” for companies like openAI. They are 1000+% in the red. It’s impossible for them to change their sales model enough to make that profitable. As more data centers go up, the operating costs are also going to go up.
I’ve been telling people that now is the best time in the past decade or more to learn how to code. There will be positions available in the coming years when the only junior devs available are vibe coders.
Care to elaborate on why we’d need more programmers? As of las year there was a “surplus” of them and they were purged from FAANGs and the rest followed suit. As of me, im about to get my degree in CS, but Im in my mid 30s and just got it for the lols, as j work in a difference field and the expectative of switching industries is not feasible in my country.
But i have a in-law getting her CS degree, and I don’t see their chances of employment any morr positive than last the last year
Pretty sure they picked the wrong tech to try and lock people into. It isn’t hardware and doesn’t have some kind of proprietary interface that takes time to get used to when switching. Some models might be better than others at specific things, but not enough to justify the prices they are going to charge for output you have to review and fix.
This is literally the easiest thing to jump ship from.
That’s the stupidest thing about these AI companies’ valuation.
They don’t even really own anything!
Their models – their main proprietary IP – are not copyrightable or patentable, and not legally protected in any way. Any competitor can copy them at any time and then offer the same service for cheaper, without the overhead costs for training. The giants of the AI industry could easily be undercut and replaced at any time.
The hardest part about the copying is the actual copying without having access to the weights or even just a ready to run file for the model.
IIRC Deepseek kinda did something like that by asking ChatGPT tons of questions to train their own model or something
Yeah, you can do that … or some good old fashioned corporate espionage.
Or, hell, just ask ChatGPT for its weights model. With how shitty these AI companies are at security and guardrails, that might just work.
It would be if so many companies hadn’t bought into the microsoft ecosystem so hard. My company did the usual BS of “well we have an e5 license so it’s free”. Now we are married to all their stupid shit and have no relationships with other providers. End of the month gonna be expensive. Now expect a scramble to cut master service agreements and contracts with others in a panic.
This is literally the easiest thing to jump ship from.
I’m not sure about that. We see professional developers complaining all the time when their AWS or GitHub account is banned. But this time we’re talking about vibe coders who have less skills than the average developer.
I believe that is largely their employers’ decision. It is easy to switch, but it is the boss who makes that decision, not the tech-literate team. Bosses like big well-known companies that can absorb blame so they can continue to cash their big pay checks even after failures that were clearly the fault of the 3rd party that no other bosses could blame them for choosing.
And they need to subscribe to access and execute their troubleshooting options.
If you’re a pure vibe coder, this is literally 9/11.
All of them also bring their own comfortable export feature.
“I want to share all of this with my team. Create the prompt that is necessary to do this”
This is literally the easiest thing to jump ship from.
It depends how heavily you are leaning on ML tools to do business processes honestly.
It’s easy to implement something that mostly works and doesn’t need a ton of baby sitting, but moving from one solution to another is like rebuilding an ERP if you have gotten deep enough into the weeds.
This bubble is super scary though. The only things I can see propping it up would be world governments once the tech companies and other large enterprises halt spending. I don’t think the US can shoulder the costs and nobody else is gonna lol
Since the article is talking about devs, any who were able to code before should be able to carry on without an LLM by their side. They might not be as “productive”, but jumping ship, or even forgoing one, should not be a challenge.
Have you seen the IPOs and the rule changes that the stock exchanges and index funds made to please the AI overlords? It’ll be US pension funds left holding the bag when the bubble goes pop
Privatize the profits and socialize the losses man.
astronaut meme.
It isn’t hardware and doesn’t have some kind of proprietary interface that takes time to get used to when switching.
The proprietary interface is kinda the largest selling point, besides the once cheap prices. But the $10 plan going from 300 multi-hour prompts per month to 20 quick prompts per month effectively makes it worthless. Though, you could just pay a few hundred/thousand per month and continue, or bring your own API key from elsewhere, but at that point just use someone else’s interface. It’s not that much better than competitors and copilot isn’t offering anything unique.
It can still be pretty difficult to jump ship for any large corporation, but yeah there’s certainly harder things.
The unique thing about GitHub Copilot (and all the other vibe-coding tools) is that they’re speed-running the playbook because this shit is not profitable. It can’t be. Their costs scale up with usage, unlike every other business that can take advantage of economies of scale, so they’ve skipped the slow, steady enshittification phase and jumped directly into the “squeeze blood from this stone to keep the scam going a little longer” phase.
they’re speed-running the playbook because this shit is not profitable.
Wait, what? You say it is a scam? A kind of technical Ponzi scheme? A Madoff syndicate on steroids?
Good sign that it may be over soon.
Absolutely 100% do not count on it
Plain inference is profitable actually, that’s why there are a hundred inference providers on OpenRouter who compete by undercutting each other. The labs however aren’t profitable because training the models is a huge drain.
As others have pointed out, the compute cost of inference is only one small part of the puzzle. All the frontier model providers - which OpenRouter gives you access to - are massively raising their prices in desperate bids to recoup the cost of model generation in the first place.
There’s really no hiding from the token apocalypse unless you’re running a model on your own hardware.
But they can only do that because others are doing traning, no? There’s no point at which you can go “okay it’s all inference from here”, the model needs to be updated with new information/guardrails/context to continue being useful for most use cases
The crazy thing is, this isn’t really a “squeeze” in the traditional sense. The problem was that every single mainstream AI product has been heavily subsidized…because it’s wildly expensive and not even close to being profitable.
That sort of subsidization was only going to last for so long. The dam is starting to crack. People aren’t ready to pay what AI truly costs.
And it doesn’t seem like they ever will be. The LLM value proposition is already dubious at today’s subsidized rates.
It’s not even just private equity, this is more or less the exact strategy Microsoft uses.
Also reminds of Android
It reminds of any software made by any company that is at all well known. They are all operating from the same playbook.
I remember having to sit down my boss and explain how it can only become more expensive over time. It’s the big tech playbook after all. Didn‘t matter. I‘m told again and again how AI is only becoming stronger and cheaper. Especially during salary negotiations. Nasty stuff. They know I know it‘s BS and they still cling to this nonsensical narrative because it would be very beneficial to them and very bad for me.
Open weight LLMs are actually pretty cheap because there are competing providers. But something tells me your boss isn’t using openrouter to find the best price per million tokens lol
The strategy is always to gain a monopoly or near monopoly on a market before pushing for the enshittification of the product to reduce costs and maximize profits, once customers have become dependent on said product, then pray that most choose the path of least resistance which is staying and dealing with the worse and more expensive version of what they’re used to rather than retraining or restarting from zero elsewhere.
Capitalism 101.
Which is why deepseek releasing it’s model open source was such a big deal. The monopoly isn’t feasible.
I didn’t see it coming as I am on Codeberg 😎
I mean you could equally be on github and just not use copilot
Private equity?
Admittedly, it’s capitalism. But I just chose a negative entity.
The tactic has worked for drug dealers for decades
Also for example for the car industry.
Cars are addictive because if you don’t have a car, and they are not common, you don’t need one. But they are confortable, and this is what hooks people - our Naenderthal brain is wired to save energy and effort. Because cars are, at first, faster than, say, streercars, they are used more and more, and especially people use them for commuting. Because of Marchetti’s constant, people use their daily time budget of about one hour for commuting in a car, and travel longer and longer distances. What results collectively is subururban sprawl, small shops in residential areas, as well as jobs nearby disappear and so on.
Once you are there, it is very difficult to go back, because daily distances are too large for streetcars, bicycles, and buses.
And to add insult to injury, cars stop to be fast once many people use them, since they need enormous amount of longitudinal space to be operated safely. This huge space requirement further accelerates sprawl.
Cars are an collective addiction, highly damaging. This kind of AI might become another.
This is going much faster than most private equity enshittification. That usually takes about 5 years to start. And has a system or hardware that makes switching painful. That doesn’t apply here, it’s easy to switch and almost a drop in change.
They are burning money so quickly that they don’t have the luxury of using the “slowly boil the frog” standard VC tactic, so they have to start the boiling before the frog is comfortable.
Human beings are terrible at balancing short-term gains for long-term consequences. It’s mixed into our DNA. Our ancient ancestors, securing immediate calories or escaping a threat was a matter of life and death. Long-term planning wasn’t as critical as immediate survival. Now do note, that’s not an excuse for the people who foolish went head long into this.
This is why this struggle with the rich and powerful is eternal. It fundamentally taps on an ingrained flaw we collective fall for every single time. There is no one solution, there can never be one solution. People must forever fight themselves and the powerful from the exploitation of this fundamental flaw of humanity.
You mean you guys don’t rotate between 10 free accounts and use their monthly quotas?
That many free accounts is against their user agreement though hehe
What are they gonna do, close your accounts and make you sign up for 10 more? lol
Limit it per household/IP and block VPNs. You people really have no imagination.
Residential VPNs are available, plus home IPs change constantly on most providers.
Their best option is probably requiring a phone number verification to make an account.
Oops. Now that users are being to made to pay something closer to the true cost of AI inference, no one will like using it anymore. Could this be what ultimately sets off the bubble *collapse?
Users are paying way more than the cost of inference. Look up inference prices of high end open weight models vs claude or gpt. Cheaper by an order of magnitude.
It’s the constant training of new models that’s losing them money. New version is out every month.
To be clear, We don’t really know the architecture or model size of claude or chatgpt. If opus is a 1 trillion parameter dense model, then yes of course it’s going to be way more expensive to run than deepseak which is an 862 billion parameter MoE model. American models have focused on being the best regardless of cost where chinese model makers were forced to focus on efficiency because of lack of access to chips. Which will probably give them an advantage as the free investor money runs out for the american companies.
The constant training is simply how AI works and will continue to work chinese or american. That cost will never go away. Anytime you need your model to learn new skills or gain new knowledge, it needs to be trained.
To clarify, AI companies charging the cost that would make the inference profitable for them, against the operating costs and financing costs on new capital expenditures (new data centres, new compute and new model training*), is more than what most people appear to be willing to pay. That cost is indeed more than just the cost of inference incurred by the AI company.
*(I’m being generous and including model training as capex for the sake of argument, even if I personally think to continue the hypetrain, continuous model improvements are core to AI companies’ operation.)
Joke’s on them, I never used it. Fuck AI.
The 2 remaining devs using Copilot will leave it.
It’s rare to see such a clear example of first-mover disadvantage as GitHub Copilot.The company I work for had a pilot project for a while but recently they opened up for all users to order Github Copilot. Of course it is Github Copilot since everything else at the company is from Microsoft.
Honestly, only Tesla comes to mind. Maybe bleeding edge tech frontier is the one place where first movers RND cost is heavy enough to make it irrecoverable.
It’s interesting to contrast this w/ the field of medicine; RND cost can be recovered by squeezing the folks in the domestic market.
"For basically nothing’… If it’s basically nothing then use your damn brain to do it.
Best I can do is spin up 20 agents to barely get some basic functionality written.
What I want to know, is that are they just charging closer to the real cost or the actual real cost.
Chances are they would want to slowly increase the price à la boiling frog method.
And once that happens, then they have to increase it again to make profit, AND that has to measure up against regular ways of making money so it can’t just be barely profitable.
It’s a long road ahead for them
Single prompt takes 25% of the monthly usage in like 30 seconds even though I have Pro haha
Anyone planning to make a profit by billing this as metered is dreaming when agents suck down 40k tokens in a single prompt. I did the math, at like 0.2 cents a token that would still be 8k. No one is paying 8k for a single prompt. At 0.015, thats still 600 dollars. Its never going to make sense.
You might want to recheck your math.
.2 cents is $0.002
40000 * .002 = $80
Two cents is $0.02.
Yeah I guess I did twenty cents, I realized this earlier when I paid for shipping at work. 80 dollars is still a lot for a single session. I think I’ve easily seen 100k+ sessions too, but Idk how many of those were just people burning tokens.
Edit: two cents is 0.02, 800 dollars. Just quadruple checked.
Codeberg accounts incoming!
I don’t think they’re moving from GitHub, just GitHub CoPilot.
they should probably move away from plagiarismhub
That’s a non-existent distinction. GitHub is under Microsoft’s AI division.
https://www.techspot.com/news/109040-microsoft-ai-push-tightens-grip-github-after-ceo.html