Today, a prominent child safety organization, Thorn, in partnership with a leading cloud-based AI solutions provider, Hive, announced the release of an AI model designed to flag unknown CSAM at upload. It’s the earliest AI technology striving to expose unreported CSAM at scale.

  • db0@lemmy.dbzer0.com
    link
    fedilink
    English
    arrow-up
    2
    ·
    16 hours ago

    Ye, a normal VPS would be too slow for production use, as a GPU is recommended. But you can plug in any home PC to do it without risks

    • hendrik@palaver.p3x.de
      link
      fedilink
      English
      arrow-up
      1
      ·
      edit-2
      16 hours ago

      Do you think this approach would be worth a try for the threaded Fediverse (aka Lemmy)? I mean your use-case is very different. We have some rudimentary image detection to flag other kinds of unwanted images in Piefed. I could experiment with something like https://github.com/monatis/clip.cpp. Have it go through the media cache and see if it can do something useful for us. But I don’t think it’d be worth all the effort unless the whole approach is somewhat accurate and runs in real time on average VPSes.

      • db0@lemmy.dbzer0.com
        link
        fedilink
        English
        arrow-up
        3
        ·
        edit-2
        16 hours ago

        This approach was developed precicely for threaded fediverse. The initial use-case was protecting my own lemmy from CSAM! Check out fedi-safety and pictrs-safety