this post was submitted on 15 Sep 2025
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And then AI will just go away and everything will go back to normal again, yes? It'll suddenly stop working and so people will stop using it for all the things they're currently using it for.
They will when AI companies can no longer afford to eat their own costs and start charging users a non-subsidized price. How many people would keep using AI if it cost $1 per query? $5? $20?
OpenAI lost $5 billion last year. Billion, with a B. Even their premium customers lose them money on every query, and eventually the faucet of VC cash propping this whole thing up is gonna run dry when investors inevitably realize that there's no profitable business model to justify this technology. At that point, AI firms will have no choice but to pass their costs on to the customer, and there's no way the customer is going to stick around when they realize how expensive this technology actually is in practice.
I run local LLMs and they cost me $0 per query. I don't plan to charge myself more than that at any point, even if the AI bubble bursts.
Realy? I get what you want to say, but at least the power consumption of the machine you need the model to run on will be yours forever. Depending on your energy price it is not 0 per query.
It's so near zero it makes no difference. It is not a noticeable factor in my decision on whether to use it or not for any given task.
The training of a brand new model is expensive, but once the model has been created it's cheap to run. If OpenAI went bankrupt tomorrow and shut down the models it had trained would just be sold off to other companies and they'd run them instead, free from the debt burden that OpenAI accrued from the research and training costs that went into producing them. That's actually a fairly common pattern for first-movers like that, they spend a lot of money blazing the trail and then other companies follow along afterwards and eat their lunch.
It's cheap to run for one person. Any service running it isn't cheap when it has a good number of users.
That's great if they actually work. But my experience with the big, corporate-funded models has been pretty freaking abysmal after more than a year of trying to adopt them into my daily workflow. I can't imagine the performance of local models is better when they're running on much, much smaller datasets and with much, much less computing power.
I'm happy to be proven wrong, of course, but I just don't see how it's possible for local models to compete with the Big Boys in terms of quality... and the quality of the largest models is only middling at best.
You're free to not use them. Seems like an awful lot of people are using them, though, including myself. They must be getting something out of using them or they'd stop too.