drhead [he/him]

  • 2 Posts
  • 73 Comments
Joined 4 years ago
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Cake day: July 25th, 2020

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  • I literally have been using the majority of my spare time to work with AI-generated images for almost two years now. I have a very thorough understanding of what exactly you’d need to pull off a stunt like this.

    The background is part of the image, the obviously given clothing is part of the image, both of those things are fairly consistent across all of the images and look like what would be used for facial recognition, which is something that we know most countries do when they have the technological means to do so, China included. If you want that consistent background and clothing, it needs to be part of the training images. Otherwise, your next best option is a lot of tedious manual editing, which would be more effort than it is worth if the images are to look plausible.

    I also have looked at the images myself, and vividly remember GenZedong trying to point out skin lesions as proof that an image is AI generated (definitely not their proudest moment, though they may have thought otherwise). If you’d like to dig yourself into that hole, then show some examples. Most that I’ve seen pointed out can be more easily explained as skin lesions, markings on the background wall, something moving when the picture is taken. This is what real NN artifacts look like, I never saw anything like these in those images, and what I see far more of is consistency in details that neural nets struggle a lot with.



  • Had to review my notes on discord from when I was initially investigating this.

    You’d need to specifically train a model to output images that look specifically like these photos. If they had enough real images of prisoners to even try to finetune an existing model trained on a broad range of faces, they would have enough real images to make whatever point they’re trying to make. That’s a mark against these photos being synthetic on practical grounds, in that there is no point in using synthetic image generation to inflate the count.

    That database has around 2800 images on it. If we’re proposing that a substantial portion are synthetic, then that leaves only a couple hundred that could be used to actually train, which isn’t enough, you would severely overfit any model large enough to generate sufficiently high quality images. And the images shown are clearly beyond something like the photos on thispersondoesnotexist. Everything in the background of all images shown, for example, is coherent, including other people in the background. There are consistent objects across different pictures - many subjects were having pictures taken on the same background, and many have similar clothing. The alleged reason for these pictures is facial recognition (which is entirely believable since yeah, China does that, as does everyone else, and isn’t notable), having dark clothing on hand to ensure contrast makes sense, as does taking pictures in the same spot. This is all another mark against the photos being synthetic, on the grounds that even current image generation technology can’t fully do what is shown in these pictures to the same degree. “But they have special technology that we don’t–” no, we have no reason to believe they do, this is unsubstantiated bullshit. Higher quality models generally are larger and require even more data, which would just get you an overfitted model faster with your few hundred photos.

    The only thing they really directly claim that these photos are is photos used for facial recognition. They show that at some point, Chinese police took photos of about 2800 people in Xinjiang, which isn’t surprising at all and doesn’t really prove much. That won’t stop them from trying to portray it as proof of an ongoing genocide, though, especially when they know that like 90% of people won’t question it at all. The base unit of propaganda is not lies, it’s emphasis. The most plausible explanation is that the photos are real, but are being misrepresented as something unusual.




  • Case by case is the only reasonable answer.

    I don’t think there’s anyone who would say that Full Metal Alchemist: Brotherhood is bad to watch dubbed, the dub as far as I can tell even has adjustments to preserve wordplay without it being awkward (think of how often “trump card” is used in anime) which is one of the hardest things to do with translation work. There’s some where both have merits, like early seasons of Jojo, part 2 was great dubbed but both part 1 and part 2 have tons of memes that are mostly from random English phrases in the original. Later seasons definitely sub only, literally what is the point of watching part 3 without ZA WARUDO? Why is there no Italian dub of Golden Wind? Also there’s very special cases like Ghost Stories.


  • Just something that I feel like I have to remind people of whenever it comes up: mainstream psychology does not recognize porn addiction as a real thing, based on the lack of evidence/lack of consensus to support a consistent diagnostic criteria. The only actually recognized related condition is compulsive sexual behavior disorder, which is not using an addiction model.

    I’m quite sure that there has to be at least someone who has problematic pornography use habits which aren’t just a symptom of another issue, but without anyone being able to pin down a consistent set of diagnostic criteria, then there’s barely any way to identify who those people are separately from people who report it but whose distress is coming from something else. One study done on self-reported pornography addiction found that the strongest predictor was moral objection to pornography, not amount of porn use. Another two studies found that antagonistic narcissism is an even better predictor (might read it when it isn’t 3AM). Your analysis is actually touching on this somewhat – a narcissist’s interest in “addressing their pornography addiction” is mostly that they think that it will elevate them above the porn addicts, or whatever other target.








  • Main difference is that blockchain never had an actual use case (speculation doesn’t count) beyond buying heroin and running ransomware. Machine learning had practical applications for years that nobody really thought much of at the time, and the marketers got a hold of it after it was fairly well established without them and right at the point of a massive wave of breakthroughs in the area.

    That being said, there is a fucking massive AI bubble. A large portion of the things we’re seeing will survive when that pops, but boy are there a lot of very overconfident investors who are going to get burned hard on this.




  • Should also probably include some recommendations for less expensive routers that can use OpenWrt along with this? Mine cost me $300… I don’t regret it because I have found at least that much utility in it, from this and from finally being able to intercept my smart TV’s hardcoded DNS requests and blocking the ads, but I’m pretty sure that there are better deals to be had that don’t involve paying $300 for one of the radios to not work due to bad driver support.


  • I think you forgot to include the part where he thinks this needs to be done so that we can, essentially, kill all of the dumb people who would get tricked by a rising superintelligent AI.

    There are so many cranks in “AI safety” stuff to the point where it is legitimately difficult to talk about what should be done that isn’t very obviously slanted for some industry’s benefit. You’ve got people like this, you’ve also got people like Gladstone that are LITERALLY EX-PENTAGON PEOPLE SPONSORED BY LOCKHEED MARTIN (who I am sure are very concerned about AI safety – the only way I could be more convinced is if it was Boeing), who have suspicious demands that the publication of open-source models should be made illegal (probably out of concerns about China, as if half of the papers I read on new developments aren’t already from them or the Noah’s Ark lab in Moscow). There is no well that is unpoisoned here.