- 3 hours
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.
- 35 minutes
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.
- 2 hours
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.
- [deleted]@piefed.worldEnglish3 hours
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.
- OwOarchist@pawb.socialEnglish2 hours
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, 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.
- boonhet@sopuli.xyzEnglish1 hour
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
- one_old_coder@piefed.socialEnglish2 hours
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.
- Buddahriffic@lemmy.worldEnglish1 hour
And they need to subscribe to access and execute their troubleshooting options.
- jagermo@feddit.orgEnglish3 hours
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”
- 3 hours
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
- 2 hours
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
3 hoursThe 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.
- 2 hours
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.
- Cenotaph@mander.xyzEnglish1 hour
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
In a vacuum maybe but are they profitable if you add the infrastructure investments to the mix? What about model development? There was a shit ton of money that was spent. Covering the running costs is not enough. At some point someone has to pay for the investments.
- CosmoNova@lemmy.worldEnglish3 hours
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.
- boonhet@sopuli.xyzEnglish1 hour
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
Single prompt takes 25% of the monthly usage in like 30 seconds even though I have Pro haha
- Grandwolf319@sh.itjust.worksEnglish2 hours
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
- teslasdisciple@lemmy.caEnglish3 hours
"For basically nothing’… If it’s basically nothing then use your damn brain to do it.
- Rentlar@lemmy.caEnglish2 hours
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?
- boonhet@sopuli.xyzEnglish1 hour
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.
- Rentlar@lemmy.caEnglish12 minutes
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.)
- Pumpkin Escobar@lemmy.worldEnglish3 hours
I was still using my copilot account, figured I’d see how the new pricing worked. I blew through 60% of my max+ limit in 1 day on absurdly light usage, promptly cancelled rather than upgrade from the $39 / month plan to the $100 /month plan.
I do think there’s a productivity help from AI but vibe coding everything is miserable and gives awful results. Targeted AI usage makes sense and I’ll refine my local AI usage and tooling for that.
- flamingo_pinyata@sopuli.xyzEnglish4 hours
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.
- Mushimas@lemmy.mlEnglish3 hours
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.
- ryper@lemmy.caEnglish3 hours
They’ll move to another service, the service’s expenses will spike, and then that service will switch to usage based billing, and then they’ll have to look for another service again, and repeat the loop until they can run a good enough model locally.
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
