Comment on This new data poisoning tool lets artists fight back against generative AI
MargotRobbie@lemmy.world 1 year ago
It’s made by Ben Zhao? You mean the “anti AI plagerism” UChicago professor who illegally stole GPLv3 code from an open source program called DiffusionBee for his proprietary Glaze software (reddit link), and when pressed, only released the code for the “front end” while still being in violation of GPL?
The Glaze tool that promised to be invisible to the naked eyes, but contained obvious AI generated artifacts? The same Glaze that reddit defeated in like a day after release?
Don’t take anything this grifter says seriously, I’m surprised he hasn’t been suspended for academic integrity violation yet.
who illegally stole GPLv3 code from an open source program called DiffusionBee for his proprietary Glaze software (reddit link), and when pressed, only released the code for the “front end” while still being in violation of GPL?
Oh, how I wish the FSF had more of their act together nowadays and were more like the EFF or ACLU.
You should check out the decompilation they did on Glaze too, apparently it’s hard coded to throw out a fake error upon detecting being ran on an A100 as some sort of anti-adversarial training measure.
That’s hilarious, given that if these tools become remotely popular the users of the tools will provide enough adversarial data for the training to overcome them all by itself, so there’s little reason to anyone with access to A100’s to bother trying - they’ll either be a minor nuisance used a by a tiny number of people, or be self-defeating.
Thank you, Margot Robbie! I’m a big fan!
You’re welcome. Bet you didn’t know that I’m pretty good at tech too.
Also, that’s Academy Award nominated character actress Margot Robbie to you!
ElectroVagrant@lemmy.world 1 year ago
Thanks for added background! I haven’t been monitoring this area very closely so wasn’t aware, but I’d have thought a publication that has been would then be more skeptical and at least mention some of this, particularly highlighting disputes over the efficacy of the Glaze software. Not to mention the others they talked to for the article.
Figures that in a space rife with grifters you’d have ones for each side.
Zeth0s@lemmy.world 1 year ago
People don’t understand AI. Probably all articles I have read on it by mainstream media were somehow wrong. It often feels like reading a political journalist discussing about quantum mechanics.
My rule of thumb is: always assume that the articles on AI are wrong. I know it isn’t nice, but that’s the sad reality. Society is not ready for AI because too many few people understand AI. Even AI creators don’t fully understand AI (this is why you often hear about “emergent abilities” of models, it means “we really didn’t expect it and we don’t understand how this happened”)
joel_feila@lemmy.world 1 year ago
By that logic humanity isnt ready for personal computers since few understand how they work.
Zeth0s@lemmy.world 1 year ago
Kind of true. Check the law proposals on encryption around the world…
Technology is difficult, most people don’t understand it, result is awful laws. AI is more difficult, because even creators don’t fully understand it (see emergent behaviors, i.e. capabilities that no one expected).
GenderNeutralBro@lemmy.sdf.org 1 year ago
That was certainly true in the 90s. Mainstream journalism on computers back then was absolutely awful. I’d say that only changed in the mid-2000 or 2010s. Even today, tech literacy in journalism is pretty low outside of specialist outlets like, say, Ars.
Today I see the same thing with new tech like AI.
ElectroVagrant@lemmy.world 1 year ago
Yeah, I view science/tech articles from sources without a tech background this way too. I expected more from this source given that it’s literally MIT Tech Review, much as I’d expect more from other tech/science-focused sources, albeit I’m aware those require scrutiny just as well (e.g. Popular Science, Nature, etc. have spotty records from what I gather).
Also regarding your last point, I’m increasingly convinced AI creators’ (or at least their business execs/spokespeople) are trying to have their cake and eat it too in terms of how much they claim to not know/understand how their creations’ work while also promoting how effective it is. On one hand, they genuinely don’t understand some of the results, but on the other, they do know enough of how it works to have an idea of how/why those results came about, however it’s to their advantage to pretend they don’t insofar as it may mitigate their liability/responsibility should the results lead to collateral damage/legal issues.