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    "text": "I tried condensing it to a skeet, but found my description is too simple.\n\nit identifies what is in the image, then makes subtle adjustments to pixels that trick AI during training time to learn the wrong content from the image, with the wrong keyword.\nThe goal is to increase the cost of training AI",
    "$type": "app.bsky.feed.post",
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        {
          "alt": "Nightshade works similarly as Glaze, but instead of a defense against style mimicry, it is designed as an offense tool to distort feature representations inside generative AI image models. Like Glaze, Nightshade is computed as a multi-objective optimization that minimizes visible changes to the original image. While human eyes see a shaded image that is largely unchanged from the original, the AI model sees a dramatically different composition in the image. For example, human eyes might see a shaded image of a cow in a green field largely unchanged, but an AI model might see a large leather purse lying in the grass. Trained on a sufficient number of shaded images that include a cow, a model will become increasingly convinced cows have nice brown leathery handles and smooth side pockets with a zipper, and perhaps a lovely brand logo.\n\nAs with Glaze, Nightshade effects are robust to normal changes one might apply to an image. You can crop it, resample it, compress it, smooth out pixels, or add noise, and the effects of the poison will remain. You can take screenshots, or even photos of an image displayed on a monitor, and the shade effects remain. Again, this is because it is not a watermark or hidden message (steganography), and it is not brittle. ",
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    "langs": [
      "en"
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    "reply": {
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        "uri": "at://did:plc:dkh643asru53huyrgpjmobgl/app.bsky.feed.post/3loohyg5m3227"
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    },
    "createdAt": "2025-05-08T21:06:15.215Z"
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}