Google’s DeepMind unit is unveiling today a new method it says can invisibly and permanently label images that have been generated by artificial intelligence.

  • beta_tester
    link
    fedilink
    English
    arrow-up
    41
    arrow-down
    1
    ·
    1 year ago

    Why it matters: It’s become increasingly hard for people to distinguish between images made by humans and those generated by AI programs. Google and other tech giants have pledged to develop technical means to do so.

    You don’t need a watermark for good intentions. A bad actor doesn’t put a watermark on it. A watermark may hurt because the broad mass will think “if there’s no watermark, the image is real”.

      • Sethayy@sh.itjust.works
        link
        fedilink
        English
        arrow-up
        4
        ·
        1 year ago

        You heard of stable difusion? They got 1 line installs nowadays then all you have to enter is a prompt and go.

        Entirely open source so anyone could improve the model or not, and it’d be more than legal to release a non watermarked version (if a watermarked version even ever appeared).

        I saw down the chain it was compared to deuvono, which I’d argue is a bad analogy - cause whos gonna run a rootkit on their PC just to create an image, especially when there’s a million options not to (unlike games which are generally unique)

          • Sethayy@sh.itjust.works
            link
            fedilink
            English
            arrow-up
            1
            ·
            1 year ago

            I see what you mean yes, but of course such large resources are required to train the model - not run it. So reasonably as long as a bunch of users can pool resources to compete with big tech, there will always be an ‘un-watermark-able’ crowd out there, making all the watermakrs essentially useless because they only got half the picture.

            And how training these models works is insanely parallel, so reasonably - if (ideally a FOSS) project pops up allowing users to donate cpu time to train the model as a whole - users could actually have more computational power than the big tech companies

              • Sethayy@sh.itjust.works
                link
                fedilink
                English
                arrow-up
                2
                ·
                1 year ago

                I think youre mixing together a couple angles here to try n make a point.

                ‘Unless the open source model is the best…theyre using proprietary code’ youre talking about a hypothetical program hypothetically being stolen and referencing it as a definite?

                As per the companies, of course they only use certain resoures, theyre companies they need returns to exist. A couple million down the drain could be some CEO’s next bonus, so they won’t do anything theyre into sure they’ll get something from (even if only short term)

                As per the 4chan, was that a coincidence or are you referencing unstable diffusion? Cause they did do almost exactly that (before of course it got mismanaged cause the nsfw industry is always been a bit ghetto)

                And like sure fold it at home or donate for aws, same end result really doesn’t matter what the user’s are comfortable with

                And whew finally sure ms bought github but like you think stable diffusion bought the internet? Courts have proven webscraping is legal…

                Ik this is a wall of text but like I said these arguments all feel like a bunch of thoughts tangentially related

      • nodsocket@lemmy.world
        link
        fedilink
        English
        arrow-up
        1
        ·
        1 year ago

        This is Google were talking about. We’re probably going to find out that you can remove the mark by resizing or reducing the color depth or something stupid like that. Remember how YouTube added ContentID and it would flag innocent users while giving actual pirates a pass? As said in a related article:

        “There are few or no watermarks that have proven robust over time,” said Ben Zhao, professor at the University of Chicago studying AI authentication. “An attacker seeking to promote deepfake imagery as real, or discredit a real photo as fake, will have a lot to gain, and will not stop at cropping, or lossy compression or changing colors.”

        https://www.maginative.com/article/google-deepmind-launches-new-tool-to-label-ai-generated-images/