Reminder that this is made by Ben Zhao, the University of Chicago professor who illegally stole open source code.

This tool would be the first to allow content owners to push back in a meaningful way against unauthorized model training

-Ben Zhao

This statement is strange. This is far from the first paper attempting this. This isn’t even this author’s first attempt. A few months ago he contributed to the glaze paper attempting the same thing, marketed the same way.

Runs the image through an AA filter

Hmmm, seems the nightshade effect’s gone now. Wonder why?

In a month this will be a hot new A1111 extension for hybridizing visual concepts.

This is the best summary I could come up with:

The goal is to help visual artists and publishers protect their work from being used to train generative AI image synthesis models, such as Midjourney, DALL-E 3, and Stable Diffusion.

The open source “poison pill” tool (as the University of Chicago’s press department calls it) alters images in ways invisible to the human eye that can corrupt an AI model’s training process.

Those with access to existing large image databases (such as Getty and Shutterstock) are at an advantage when using licensed training data.

But as the Nightshade team sees it, research use and commercial use are two entirely different things, and they hope their technology can force AI training companies to license image data sets, respect crawler restrictions, and conform to opt-out requests.

“The point of this tool is to balance the playing field between model trainers and content creators,” co-author and University of Chicago professor Ben Y. Zhao said in a statement.

Shawn Shan, Wenxin Ding, Josephine Passananti, Haitao Zheng, and Zhao developed Nightshade as part of the Department of Computer Science at the University of Chicago.

The original article contains 656 words, the summary contains 179 words. Saved 73%. I’m a bot and I’m open source!

Also related This new data poisoning tool lets artists fight back against generative AI