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I don't use AI for anything except translating language. I just use the local models. I have no fucking idea how an entire language (and the info needed to properly transform to another language) can be contained in a file of 10-70mb. But it works adequately on my trashy old hardware.
Also tried a bit of text to speech, transcription and similar. Those were more of a pain in the ass and needed a lot more stuff to download and set up but it isn't clear to me if that is the nature of it or maybe the front end user experience just hasn't been polished yet. But my laptop can handle it anyway. It seems like these companies really want the SAAS model and that is directing how they build. More than it being an inherent requirement.
To me it kind of seems like most individual people have a limited set of tasks they want to accomplish so you could just have whatever you need locally. Probably could even generate a custom local model and send it updates from an interface of some kind. If you want something to write emails or whatever you have it pull and digest what it needs once and then by incremental upgrades after that.
Its hard for me to imagine individual users really need so much power from a data center because its not like you are using the whole thing yourself. Probably data centers are really for huge comprehensive tasks that humans could never do unaided like analyzing massive datasets.
Yeah you're kind of getting where I think or at least am hoping the market will go. You can already retrain public models locally but the tooling is either way too low level, or completely vibe coded.
I think the main contradiction in the market is that AI models are too big and expensive to run profitabily. But if they make them more efficient then the models can run on consumer hardware and that fucks up the SaaS AI business.
Don't worry, all the data centers will be put back to use mining crypto as god intended.
Too expensive to run profitably + efficient models undermine the SaaS model + Chinese tech is always threatening to surpass them for a fraction of the cost. Even if they try to gatekeep efficient and local models, deepseek is right there.