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All of your examples are limited in some way, but GPT-3 wouldn't have any meaningful limits.

Stable Diffusion: Marks images as AI-generated. (invisible watermark, but still, it's there)

Photoshop: Requires time & effort from a human.

Fake news website: Requires time & effort from a human.



I wouldn't really say Stable Diffusion marks images as AI-generated. There's a script in the Stable Diffusion repository that will do that, but it's not connected to the model itself in a meaningful way. I use Stable Diffusion a lot and I've never touched this script.

https://github.com/CompVis/stable-diffusion/blob/69ae4b35e0a...


What "script" are you using for doing txt2img? The watermark function is automatically called when you use the CLI in two places, https://github.com/CompVis/stable-diffusion/blob/69ae4b35e0a... and https://github.com/CompVis/stable-diffusion/blob/69ae4b35e0a...

Trivial to remove, I give you that. But AFAIK, the original repository + most forks put the watermark automatically unless you've removed it on your own.


>Trivial to remove, I give you that. But AFAIK, the original repository + most forks put the watermark automatically unless you've removed it on your own.

almost all of the 'low-vram' variant forks either have an argument to turn off the watermark (it saves a bit of memory) or come with it disabled all together.


I linked to the same file you did, that is the "script" I was referring to. And I said that I didn't use it.

My point is that the Python API is more interesting than the txt2img script, and it doesn't add any watermarks.


SD only does that if you don't delete the line of code that does it...


It would be pretty trivial to have an invisible watermark in GPT3 output-- though you don't really need one: just score text with gpt3 to find out if it was likely gpt3 generated or not.




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