111–120 of 188 posts
It is smart, but it is not impossible to crack algorithmically imo. In particular, one can take two consecutive frames and run perturbations moving one frame around (ie shift the indexes) to find where the difference between the two consecutive frames minimises. Then subtract these two (perturbed) frames and ocr it. Works easily if the movement is linear/one-directional. I did this in 20 lines of code (checking only…
GPT-5.6 had no problem seeing the text when giving it a video recording of it. "No problem" as in using temporal analysis with optical flow and vertical-displacement maps to estimate how the image moved, and combine those into a motion map with increased contrast to see the text. I didn't give it any instructions though, just asked it what it said.
Do you have a link to this chat?
Earlier quoted context omitted.
Do you have a link to this chat?
The chat contains the video, which may reveal som meta data about me. But the shared chat also doesn't include any of the images in the thinking steps that my original chat has, where you can see the different maps it generated. Pretty cool seeing it go from noise to patterns to the final image which clearly shows the text as black on white.
Earlier quoted context omitted.
The chat contains the video, which may reveal som meta data about me. But the shared chat also doesn't include any of the images in the thinking steps that my original chat has, where you can see the different maps it generated. Pretty cool seeing it go from noise to patterns to the final image which clearly shows the text as black on white.
What text did it find?
It is smart, but it is not impossible to crack algorithmically imo. In particular, one can take two consecutive frames and run perturbations moving one frame around (ie shift the indexes) to find where the difference between the two consecutive frames minimises. Then subtract these two (perturbed) frames and ocr it. Works easily if the movement is linear/one-directional. I did this in 20 lines of code (checking only…
Earlier quoted context omitted.
Yes, it may be useful to replace current CAPTCHA, but this does not provide the positive side-effects of CAPTCHA where user-submitted data is used to train the unknown images or reinforce the labelling of existing image segments.
It’s been years since captcha was contributing to labeling.
So the next time you're asked to click the pictures with the bicycles or traffic lights? Please do so before it's too late.
(/s, if that's necessary)
GPT-5.6 had no problem seeing the text when giving it a video recording of it. "No problem" as in using temporal analysis with optical flow and vertical-displacement maps to estimate how the image moved, and combine those into a motion map with increased contrast to see the text. I didn't give it any instructions though, just asked it what it said.
Took me a long time to realise that "Written In Ghost Text" wasn't actually the text I was meant to be reading, and that was only the decoy message. I can barely read the actual message, and it's about as "readable" to me as the Magic Eye 3D pictures. Actually I think I have a headache from looking at it on a mobile screen. As a research idea it's cool though. But I do wonder if/when AI models will figure out how to…
> ”Took me a long time to realise that "Written In Ghost Text" wasn't actually the text I was meant to be reading, and that was only the decoy message.” Wait, what? Seriously? That’s the only text I can see. Am I an AI?
But a still frame doesn't contain the information necessary to see the actual message, so when it's paused, I can only barely see something which I suppose says something along the lines of "written in ghost text".