Comment on Astronomers discover technique to spot AI fakes using galaxy-measurement tools

teawrecks@sopuli.xyz ⁨3⁩ ⁨months⁩ ago

• elfpie@beehaw.org ⁨3⁩ ⁨months⁩ ago

  Does it really work like that? I would say that they are not trying to fool any test, just getting harder to be detected. The goal being looking completely realistic.

  source

  • AndrasKrigare@beehaw.org ⁨3⁩ ⁨months⁩ ago

    Looking completely realistic and being able to discern between real and fake are competing goals. If you can discern the difference, then it does not look completely realistic.

    I think what they’re alluding to is generative adversarial networks …wikipedia.org/…/Generative_adversarial_network where creating a better discriminator that can detect a good image from bad is how you get a better image.

    source
  • jarfil@beehaw.org ⁨3⁩ ⁨months⁩ ago

    This is one of the basic techniques to spot AI fakes:

    • Correct number of body features (limbs, fingers, eyes…)
    • Non-intersecting body features
    • Surface continuity (skin, clothes, walls…)
    • Eye reflections
    • Consistent illumination of features
    • Consistent shadows

    The “test” they’re trying to fool, is kind of the Turing test: whether humans can tell them apart.

    source

    • Sina@beehaw.org ⁨3⁩ ⁨months⁩ ago

      Consistent illumination and shadows is a rabbit hole we really don’t want to hop into.

      Outside of very obvious anomalies even a trained eye will have a hard time discerning what’s going.

      source

      • jarfil@beehaw.org ⁨3⁩ ⁨months⁩ ago

        Some are very easy to spot, like a shadow of a character, that’s missing a limb on the shadow, or has different placement or pose. Illumination or parallel surfaces where they vary in shadowing without a reason, is also a dead giveaway. But the mist damning evidence is having one scene, then a slightly different scene in a reflection.

        There are reasons for human authors to do any of these on purpose, but unless that purpose is part of the work, they’re most likely AI mistakes.

        Of course it’s kind of funny how there is already a large overlap between the best AI art, and the most senseless “modern art”.

        source
    • barsoap@lemm.ee ⁨3⁩ ⁨months⁩ ago

      It’s quite easy to trick people with untrained eyes… for one, they have no idea what “consistent illumination” and stuff means. And something being off doesn’t mean that an AI made that mistake because humans make mistakes, too – photographs don’t, but the general problem is not just about telling realistic stuff apart but also illustrations. You’re looking specifically for mistakes that AI is likely to make, but humans are practically never going to make. And yes humans get hands wrong all the time.

      Here’s a good video about what to look for and what not.

      source

      • jarfil@beehaw.org ⁨3⁩ ⁨months⁩ ago

        Yes, my comment applied more to photorealistic AI images.

        Illustrations are a different beast, where people have much more creative freedom… and that video is reasonably good at explaining that, but I find it falls short at some points:

        1. AI image generators don’t “consult” source images to generate an output. At training time, they extract patterns from the training set, which is never again used for generation, only the extracted patterns are.
        2. Modern AI generators are increasingly good at generating text. They still struggle a bit, but compared to a year ago, they can now generate headlines and large text correctly, while the mess gets shoved into smaller and less important text. This isn’t all that different from human artists adding “filler gibberish” text.
        3. Layers. While a naive (and cheaper) approach to AI generation doesn’t use layers, there are generators which do use layers, and can keep object consistency across obscured or cut-off sections.

        As AI generators advance, all these differences are likely to disappear… by following this same criticisms to fix things.

        source

        • -> View More Comments