A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data - eviltoast
As it turns out, it’s impossible to remove a user’s data from a trained A.I. model. Deleting the model entirely is also difficult—and there’s little regulation to enforce either option.

I’m rather curious to see how the EU’s privacy laws are going to handle this.

(Original article is from Fortune, but Yahoo Finance doesn’t have a paywall)

  • Asymptote@lemmy.dbzer0.comEnglish
    51·
    1 year ago

    “removing a specific feature from a compiled binary executable”

    That’s how patches used to be 😆

    • spikespaz@programming.devEnglish
      42·
      1 year ago

      Patches today patch source code. The kind of binary patching you talk about only works with deterministic builds, which sadly there’s not enough of out there.

      • __dev@lemmy.worldEnglish
        2·
        1 year ago

        I don’t see how that’s related at all. Having deterministic builds only matters if you’re building a binary from source, if you’re working with some distributed binary you’ll be applying the patch to identical binaries anyway. And if a new binary is distributed, that’s going to be because something in the source was changed; deterministic builds will still give you a different binary if the source changes.

        Binary patching is still common, both for getting around DRM and for software updates.