this post was submitted on 16 Jun 2024
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Usefulness is one thing, but it costs an astronomical amount of energy.
These companies are trying to make taxpayers pay for their infrastructure by pretending it's to benefit everyone. It won't benefit everyone that's for sure.
It's possible for local AI models to be very economical on energy, if used for the right tasks.
For example I'm running RapidOCR which uses a modern transformer architecture, and absolutely blows away traditional OCR at capturing data from character displays.
Doesn't even need a GPU and returns results in under a second on a modern CPU. No preprocessing needed, just feed it an image. This little multimodal transformer is just as much "AI" as bloated general purpose GPTs, but it's cheap, fast and useful.
As usual with "AI", there's no intelligence involved with OCR. It's just more data processing / classification being lumped into the hype.
Right, we need to come up with better terms for talking about "AI". Personally at the moment I'm considering any transformer-type ML system to be part of the category, as you stated none of them are any more "intelligent" than any others. They're all just a big stack of tensor operations. So if one is AI, they all are.
Remember long ago when "fuzzy logic" was all the hype and considered to be AI? Just a very early form of classifier network but everyone was super excited at the time.