• @tetris11@lemmy.ml
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    2 months ago

    (nice ad hominem) Christ. When you reduce a high dimensional object into an embedded space, yes you keep only the first N features, but those N features are the most variable, and the loadings they contain can be used to map back to (a very good) approximation of the source images. It’s akin to reverse engineering a very lossy compression to something that (very strongly) resembles the source image (otherwise feature extraction wouldn’t be useful), and it’s entirely doable.

    • @ReCursing
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      12 months ago

      So you can’t pull an image out as it went in? Because it’s not stored there? Yeah that’s what I FUCKING SAID! Stop spreading bullshit. Just stop it.

      • @tetris11@lemmy.ml
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        2 months ago

        (Ah, the joyful tantrum). Educate yourself on how a simple JPEG works and exactly how little features are needed to produce an image that is almost indistinguishable from the source.