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
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    5 days ago

    IFTAS is already working with Thorn towards this goal. But you already have access to such technology through my toolset.

    • hendrik@palaver.p3x.de
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      5 days ago

      This one? I loosely followed your work… Maybe I should try it someday. See how it does on a regular VPS. Thanks for the link to the IFTAS. Seems they have curated some useful links… I’ll have a look at their articles. Hope they get somewhere with that. At this point, I don’t think there is any blocklist accessible to the average Fediverse admin?!

      Edit: Thx, saw your other comment with the link to horde-safety.

      • db0@lemmy.dbzer0.com
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        5 days 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
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          5 days 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
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            5 days 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