#ai tools

Anon's explanation:

I’m curious because I see a lot of people claiming to be anti-AI, and in the same post advocating for the use of Glaze and Artshield, which use DiffusionBee and Stable Diffusion, respectively. Glaze creates a noise filter using DiffusionBee; Artshield runs your image through Stable Diffusion and edits it so that it reads as AI-generated. You don’t have to take my work for it. Search for DiffusionBee and Glaze yourself if you have doubts. I’m also curious about machine translation, since Google Translate is trained on the same kinds of data as ChatGPT (social media, etc) and translation work is also skilled creative labor, but people seem to have no qualms about using it. The same goes for text to speech—a lot of the voices people use for it were trained on professional audiobook narration, and voice acting/narration is also skilled creative labor. Basically, I’m curious because people seem to regard these types of gen AI differently than text gen and image gen. Is it because they don’t know? Is it because they don’t think the work it replaces is creative? Is it because of accessibility? (and, if so, why are other types of gen AI not also regarded as accessibility? And even then, it wouldn’t explain the use of Glaze/Artshield)

Additional comments from anon:

I did some digging by infiltrating (lurking in) pro-AI spaces to see how much damage Glaze and other such programs were doing. Unfortunately, it turns out none of those programs deter people from using the ‘protected’ art. In fact, because of how AI training works, they may actually result in better output? Something about adversarial training. It was super disappointing. Nobody in those spaces considers them even a mild deterrent anywhere I looked. Hopefully people can shed some light on the contradictions for me. Even just knowing how widespread their use is would be informative. (I’m not asking about environmental impact as a factor because I read the study everybody cited, and it wasn’t even anti-AI? It was about figuring out the best time of day to train a model to balance solar power vs water use and consumption. And the way they estimated the impact of AI was super weird? They just went with 2020’s data center growth rate as the ‘normal’ growth rate and then any ‘extra’ growth was considered AI. Maybe that’s why it didn’t pass peer review... But since people are still quoting it, that’s another reason for me to wonder why they would use Glaze and Artshield and everything. That’s why running them locally has such heavy GPU requirements and why it takes so long to process an image if you don’t meet the requirements. It’s the same electricity/water cost as generating any other AI image.)

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