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@sentientcanvas
To have a computer reliably recognize a picture of a red-winged blackbird the computer must first imagine the universe.
I am having complicated and frustrating thoughts on AI again (as always).
I don't know if I've expressed this but part of the thing that has been making me bugfuck insane about discussions around AI image generation is knowing people who have worked with computer vision for decades.
I should fire up my 2005 macbook with CS2 installed on it and edit a photo entirely with "AI tools."
This is a 1980 computer science master's thesis by Ellen Hildreth on computer image recognition and creation. (Link downloads PDF)
The paper demonstrates the development, training, and testing of the Marr-Hildreth algorithm for edge detection in digital images.
Every time I'm gearing up for a good academic rant on this subject I further entrench my hatred of copyright.
Look. I understand that people are concerned about training models. I really do get that, that people have intense feelings about their photos or drawings or image being used to train AI. I even kind of get wanting to weaponize copyright against that because you don't know what else to do with those feelings.
I am currently building a multi-decade chain of papers on computer vision and image generation to have this discussion, and I would like to do so in a moderately calm manner.
Unfortunately if I want to cite a journal article from 1983 in a tumblr post, the copyright holders of this article about image restoration and pixel randomization want $248 per section of excerpted text (<500 words).
So the calm has now gone away.
Anyway. The flesh pit guy appears to be an asshole but I'm very frustrated seeing people react to photoshop compositing tools as an unethical use of AI tools that undermines the craft or artistry of a project.
This is a 2024 paper by one of the Adobe developers who worked on those compositing tools going over how the tools work. For the record, this model was trained on licensed and public domain images only and the tools are run on device, so the copyright and environmental complaints that people frequently make about AI don't apply to these specific tools.
That paper uses research from this 2015 paper on AI detection of composited images. That paper uses the ImageNet dataset.
ImageNet's dataset is a combination of images sourced from image searches starting in 2009 and description tags generated by Amazon Mechanical Turk workers. The images are not owned by ImageNet, but were scraped from various internet sources in the late 2000s.
That project uses algorithms and processes described in this 2007 paper on the utility of a general image database and image segmentation.
This 2000 paper on image segmentation developed some of the models used in the later paper, based on a collection of 1000 Corel stock images.
That segmentation was based on statistical models in this paper from 1994, which used a small training dataset collected by the researchers.
That 1994 paper made use of the model in this foundational paper from 1984 on predictive pixel selection for algorithm-based image restoration.
That paper helped to refine the boundary-finding methods used in this 1986 paper, which was an improvement on methods from the 1980 Hildreth paper.
Both Hildreth and Canny cite this 1971 memo from the MIT Artificial Intelligence lab, which describes the process of using a computer to find lines in an image.
Personally I like this note from a revised version of that 1971 memo that shows that we are still currently dealing with some of the same problems in computer vision that people were 50 years ago.
"This program has no idea what a reasonable line-drawing should look like when it represents an image of polyhedra. Instead it is very general and will find arbitrary line-drawings. Observing the particular way in which things sometimes go wrong, one quickly comes to the conclusion that higher-level understanding of the scene being analysed could greatly improve the line and vertex creating phase of this program. As thing stand now this understanding comes only after the line-finder has done its work."
Okay so what's my point?
My point is that there is a long chain of models, statistics, and research that, stretching back to the beginning of computer vision, has been centered around figuring out the likelihood that one pixel next to another pixel is black instead of white. The computers have never been very smart, they have never understood context, and the improvements we have made from the line finder in 1971 to "harmonize" in photoshop in 2026 is a very traceable chain of refining how the statistics are calculated.
They hallucinate extra elements, they don't know what shadows are.
Computers are still stupid, they just do math a lot faster than they did in the seventies.
Harmonize is apparently a new "AI" tool available in photoshop that is capable of matching lighting, texture, and other qualities in photos that are composited together. One of the things that the flesh pit guy is currently being dragged for (aside from really seeming to be a pretty tremendous asshole) is using this particular type of AI tool as a time saver on his ongoing art project.
I want to have a conversation about this, by which I mean I want to make some arguments about this.
I'm writing this specifically about the harmonize compositing tool in photoshop (and similar tools like upscaling). This is not about using grok or generating whole images or whole elements of images, this is not about whether or not the flesh pit guy is an asshole. I will grant that he is an asshole and I personally find whole images generated with AI tools like grok to just kind of look bad and be really boring.
Work with me on this, and let's accept the premise that adobe's Firefly is an ethically trained model (up to 5% of the images used to train firefly may be midjourney images that were licensed to adobe as stock images after being generated by midjourney, but adobe pays creators standard licensing fees to train data and does not train on client data), and that the tools are run on-device and do not consume any more resources than creating a 20-layer document in photoshop would.
(Also I acknowledge that training a model uses a lot of power and resources but creating a video game or an animated movie uses power at a much higher level than playing the game or watching the movie on your own machine; i've got to limit the scope somewhere so I can actually ask the question I've got)
Again, we are granting the following before you respond to the poll:
If the model was trained on ethical data and
If the tool runs locally and does not use more power than your computer uses and
The art the tool is used on is a personal, individual project and does not lead to poor treatment of workers
With that context I think those AI Tools
Are unethical and reduce the artistry of a work
Are unethical but do not reduce the artistry of a work
Are ethical but reduce the artistry of a work
Are ethical and do not reduce the artistry of a work
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If they don't already, the various prediction market websites should offer bets on unsolved mathematical conjectures (buy "true" or "false", pays out 50:50 if the conjecture is unresolved by some cutoff date, or proven independent of ZFC)
Advantages:
Insider trading provides novel source of income for mathematical research.
People will get to argue about whether knowing a tautology can count as "material non-public information"
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"This person has a secret onlyfans!" "This artist does NSFW commissions!" "This author writes porn on the side!" I cannot begin to tell you how swag and awesome that is.
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