zlacker

>>kevema+(OP)
I have to wonder how much releasing these models will "poison the well" and fill the internet with AI generated images that make training an improved model difficult. After all if every 9/10 "oil painted" image online starts being from these generative models it'll become increasingly difficult to scrape the web and to learn from real world data in a variety of domains. Essentially once these things are widely available the internet will become harder to scrape for good data and models will start training on their own output. The internet will also probably get worse for humans since search results will be completely polluted with these "sort of realistic" images which can ultimately be spit out at breakneck speed by smashing words from a dictionary together...

>>qz_kb+AI
People training newer models just have to look for the "Imagen" tag or the Dall-E2 rainbow at the corner and heuristically exclude images having these. This is trivial.

Unless you assume there are bad actors who will crop out the tags. Not many people now have access to Dall-E2 or will have access to Imagen.

As someone working in Vision, I am also thinking about whether to include such images deliberately. Using image augmentation techniques is ubiquitous in the field. Thus we introduce many examples for training the model that are not in the distribution over input images. They improve model generality by huge margins. Whether generated images improve generality of future models is a thing to try.

Damn I just got an idea for a paper writing this comment.

>>rg111+TX
Most images you see from these services will not have a watermark on them. Cropping is trivial.