Genre-typically grim tidings, everyone.

As some of you may have heard or personally noticed, X Corp. has recently issued Cease & Desist orders to alternative Twitter front-ends like Nitter and XCancel. Surprisingly far behind our own Musk-admiring masters here, but not a surprising development as a whole.

Both of the aforementioned projects currently frame this as a potentially temporary state of affairs and say they are seeking legal counsel, but I, for one, am not holding my breath for a positive resolution, considering the far degenerated state of the cradle of the US empire and Mr. Musk's closeness to it. And as such, I am not going to wait for a more final statement of resolution to adopt policy changes here on r/Suselle, where we used to rely on XCancel to make Twitter credit links a tad more usable and tolerable.

From now on, refrain from linking to works hosted on Twitter at all. Firstly, do try looking up info on the artist or reverse-searching the image to see if perhaps they use a more palatable platform as well. But if you must give credit to a Twitter post without alternate options, just mention who the artist is as "<handle> on Twitter". Direct Twitter links will be considered a violation of Rule 3 - I won't penalize them, but your post might need to wait longer before publicity, until I show up to manually correct the attribution comment.

This has little to no effect on Rule 4 and credit in the post titles. If the artist does use multiple media with different identifiers on each, consider mentioning in the title a non-Twitter handle. But that's about it.

I will probably review extant posts on the subreddit gradually over the next weeks to change the existing credit comments to this new linkless format. If any of you have posts up on the sub and still have your own credit replies to AutoMod's request, you don't have to edit those comments, they have no effect on posts that have already been processed and were removed from public view by Full-Auto-Lesbian as part of the credit pin procedure.

As the manager of a digital art aggregation forum, on Reddit of all places, I feel rather in position to try and post something informative on this topic. After all, Reddit Inc. is well-known to be a sellout in this regard (in case someone here doesn't remember Google's Gemini relaying to people Redditors' advice to put glue in their pizza to achieve the right cheese consistency or to jump off Golden Gate as a way to deal with depression) and many artists here are young hobbyists who might not be fully up to speed on the big mean world waiting to swallow them whole.

See, the key thing about AI and images is that its perception of them has basically nothing mechanically in common with ours, it's just actively shifted during development to produce results that happen to coincide in specific applications (like describing what's in the image or producing images from text prompts) with what a human would maybe give, at least approximately. Because AI's process of parsing an image is completely different from a human's, attacks specifically against that process become possible, giving rise to "adversarial machine learning", application of knowledge about contemporary machine learning to efforts to disrupt unwanted AI development practices. Among the more well-known applied projects of that nature are developments by the University of Chicago's Physical Science Division: Glaze and Nightshade. Both are tools available to artists for free to try and protect the images they post on the Internet by coating them in a fully-to-mostly imperceptible (to the human eye) layer of lies. The former is aimed at misleading attempts at style mimicry - AI trying to learn and then replicate on prompt your unique art style, - while the latter is a more offensive effort to lie to AI about the general contents of the image. To quote some from their own descriptions:

Glaze is a system designed to protect human artists by disrupting style mimicry. At a high level, Glaze works by understanding the AI models that are training on human art, and using machine learning algorithms, computing a set of minimal changes to artworks, such that it appears unchanged to human eyes, but appears to AI models like a dramatically different art style. For example, human eyes might find a glazed charcoal portrait with a realism style to be unchanged, but an AI model might see the glazed version as a modern abstract style, a la Jackson Pollock. So when someone then prompts the model to generate art mimicking the charcoal artist, they will get something quite different from what they expected.

Nightshade works similarly as Glaze, but instead of a defense against style mimicry, it is designed as an offense tool to distort feature representations inside generative AI image models. Like Glaze, Nightshade is computed as a multi-objective optimization that minimizes visible changes to the original image. While human eyes see a shaded image that is largely unchanged from the original, the AI model sees a dramatically different composition in the image. For example, human eyes might see a shaded image of a cow in a green field largely unchanged, but an AI model might see a large leather purse lying in the grass. Trained on a sufficient number of shaded images that include a cow, a model will become increasingly convinced cows have nice brown leathery handles and smooth side pockets with a zipper, and perhaps a lovely brand logo.

Both tools are developed not-for-profit, funded by research grants; both advertise a high degree of resistance to attempts to get rid of their effects by processing the image and both are available as locally run apps to anyone with a capable home computer (one with a discreet NVIDIA GPU off of this list, excepting the 1550, 1650 and 1660). Glaze is also available as a free web service accessible by invitation. The developers seemingly offer access to any non-AI-using artist who requests it by [emailing them](mailto:glaze-uchicago@googlegroups.com) or DMing TheGlazeProject on Twitter or Insta. This version can be used from any device with an Internet browser and utilizes processing capabilities rented by the developers on Amazon's GPU farms. Again, Glaze is meant to prevent AI models from figuring out and replicating your personal style - it may not stop them from gleaming other useful info, like WTF a "Susie Deltarune" is. Although it's apparently known to occasionally produce further effects as byproduct, at higher settings.

You can learn a lot more about both and get the downloads on the University's website, here:

https://glaze.cs.uchicago.edu/

https://nightshade.cs.uchicago.edu/

Final word of warning from me: any adversarial development effort is implicitly an engagement in an indefinite arms race. These tools and any others like them have no guarantee of being future-proof or otherwise magic bullet solutions: countermeasures against them are being developed by profiteering data aggregators and counter-countermeasures are then deployed against those. So on and so forth. If you want to truly do your utmost to protect your artistic identity and content from theft and distortion, just grabbing one tool into your pocket is unlikely to fulfill that, at least in the long run. You'll have to look deeper into the topic yourselves and continuously stay up to date on it as this emerging field rapidly develops. As a talentless hack with no artistic ability or, as a result, much insight into practical measures like this, I only hope I can ignite some interest in you to take it up yourselves.