The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. Is intended as a way to fight back against AI companies that use artists’ work to train their models without the creator’s permission.
ARTICLE - Technology Review
ARTICLE - Mashable
ARTICLE - Gizmodo
The researchers tested the attack on Stable Diffusion’s latest models and on an AI model they trained themselves from scratch. When they fed Stable Diffusion just 50 poisoned images of dogs and then prompted it to create images of dogs itself, the output started looking weird—creatures with too many limbs and cartoonish faces. With 300 poisoned samples, an attacker can manipulate Stable Diffusion to generate images of dogs to look like cats.
Can you explain what the chart means? It seems like it’s supposed to show that it will degrade the output of the models when the number of poisoned samples increases, however it shows a different subject above than below. Does it morph the subject into another concept?
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The problem is that the chart is shit. There’s a prompt on the top and then text on the bottom that looks identical to the prompt, but is actually just what the top prompt was poisoned to look like after 100 or 300 samples.
If users have to read a paragraph of text to understand a chart, the chart is shit.
A less salty way to put it would be that the chart is missing two labels: “Original prompt” and “Poisoned prompt”.
The second isn’t even a prompt. I can’t fault you for getting it wrong though, because the chart is so shit!
Not very clear indeed. Each column is a determinate image who is been poisoned and as the lvl of poisoning increase the generated images degrade and turn in something completely different.
Im just gonna be direct. If you cannot understand that chart you severely lack understanding of context.
If you just look at 3 pictures in one row and read the text you should easily be able to understand what the chart is about… That’s like 10 year old logical thinking, if not even younger.
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