If I smash a thousand orphan skulls against a house and wet it, it’ll have the same effect as a decent limewash. But people might have a problem with the sourcing of the orphan skulls.
It doesn’t matter if you’we just a wittle guwy that collects the dust from the big corporate orphan skull crusher and just add a few skulls of your own, or you are the big corporate skull crusher. Both are bad people despite producing the same result as a painter that sources normal limewash made out of limestone.
Even if all involved data is explicity public domain?
What if it’s not public data at all? Like artifical collections of pixels used to train some early upscaling models?
That’s what I was getting: some upscaling models are really old, used in standard production tools under the hood, and completely legally licensed. Where do you draw the line between ‘bad’ and ‘good’ AI?
Also I don’t get the analogy. I’m contributing nothing to big, enshittified models by doing hobbyist work, if anything it poisons them by making public data “inbred” if they want to crawl whatever gets posted.
The energy consumption of a single AI exchange is roughly on par with a single Google search back in 2009. Source. Was using Google search in 2009 unethical?
Total nonsense. ESRGAN was trained on potatoes, tons of research models are. I fintune models on my desktop for nickels of electricity; it never touches a cloud datacenter.
At the high end, if you look past bullshiters like Altman, models are dirt cheap to run and getting cheaper. If Bitnet takes off (and a 2B model was just released days ago), inference energy consumption will be basically free and on-device, like video encoding/decoding is now.
Again, I emphasize, its corporate bullshit giving everything a bad name.
Yeah? Well what if they got very similar results with traditional image processing filters? Still unethical?
The effect isn’t the important part.
If I smash a thousand orphan skulls against a house and wet it, it’ll have the same effect as a decent limewash. But people might have a problem with the sourcing of the orphan skulls.
It doesn’t matter if you’we just a wittle guwy that collects the dust from the big corporate orphan skull crusher and just add a few skulls of your own, or you are the big corporate skull crusher. Both are bad people despite producing the same result as a painter that sources normal limewash made out of limestone.
Even if all involved data is explicity public domain?
What if it’s not public data at all? Like artifical collections of pixels used to train some early upscaling models?
That’s what I was getting: some upscaling models are really old, used in standard production tools under the hood, and completely legally licensed. Where do you draw the line between ‘bad’ and ‘good’ AI?
Also I don’t get the analogy. I’m contributing nothing to big, enshittified models by doing hobbyist work, if anything it poisons them by making public data “inbred” if they want to crawl whatever gets posted.
Dude. Read the room. You’re literally in a community called “Fuck AI” and arguing for AI. Are you masochistic or just plain dumb?
Even if the data is “ethically sourced,” the energy consumption is still fucked.
The energy consumption of a single AI exchange is roughly on par with a single Google search back in 2009. Source. Was using Google search in 2009 unethical?
Total nonsense. ESRGAN was trained on potatoes, tons of research models are. I fintune models on my desktop for nickels of electricity; it never touches a cloud datacenter.
At the high end, if you look past bullshiters like Altman, models are dirt cheap to run and getting cheaper. If Bitnet takes off (and a 2B model was just released days ago), inference energy consumption will be basically free and on-device, like video encoding/decoding is now.
Again, I emphasize, its corporate bullshit giving everything a bad name.