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@goodside

ChatGPT o3-pro identifies a 1965 quote by I. J. Good hand-written in a mix of print and cursive on a note ripped into four strips in reverse order rotated 90° in alternating directions: https://t.co/sTjRUz7ZUB

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                                  "full_text": "@devDanaher It doesn’t provide the exact code used, but assuming it behaves like o3 (which does) — yes, that’s exactly what it’s doing, repeatedly and iteratively using the model’s perception of transformed output.\n\nHere’s the start of reasoning summary for the “crumpled” example: https://t.co/MRqNGa3uFV",
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                              "full_text": "@goodside Super cool. I wonder if it can do it for text that it couldn't have seen in it's training data? Still super cool, and scary. I'm gonna need a proper paper shredder rather than using my hands and assuming nobody cares enough to piece it together 😅",
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                                  "full_text": "A few replies have asked to what extent the model error-corrects to the known text of the quote (implying it might not generalize as well to novel text).\n\nAn unintended error in my note suggests this is indeed happening—mine reads “ever need,” not “need ever,” as Good wrote: https://t.co/ZymkGn03DK",
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                              "full_text": "@ShaulGoo Not in this case, but given my specific prompt here, ignoring small errors is arguably the right behavior.\n\nSee this reply I just added to the thread:",
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