This idea is really brilliant I think, quite promising that it could work. It requires the image AI to understand the entire image, it is hard to divide it up into one frame per bill/coin. And it can’t use the intelligence of LLM models easily.
To aid the user, on the side there could be a clear picture of each coin and their worth, that we we could even have made up coins, that could further trick the AI.
All this could be combined with traditional image obfucation techniques (like making them distorted.
I’m not entirely sure how to generate images of money efficiently, Dall-E couldn’t really do it well in the test I ran. Stable diffusion probably would do better though.
If we create a few thousand real world images of money though, they might be possible to combine and obfuscate and delete parts of them in order to make several million different images. Like one bill could be taken from one image, and then a bill from another image could be placed on top of it etc.
To aid the user, on the side there could be a clear picture of each coin and their worth, that we we could even have made up coins, that could further trick the AI.
A user aid showing clear pictures of all available legal tender coins is a very good idea. It avoids problems more obscure coins which may have been only issued in a single year—so the user is not sitting there thinking “wait a second, did they actually issue a Ulysses S. Grant coin at some point or it that just there to fool the bots?”.
I’m not entirely sure how to generate images of money efficiently, Dall-E couldn’t really do it well in the test I ran. Stable diffusion probably would do better though.
If we create a few thousand real world images of money though, they might be possible to combine and obfuscate and delete parts of them in order to make several million different images. Like one bill could be taken from one image, and then a bill from another image could be placed on top of it etc.
I agree that efficient generation of these types of images is the main difficulty and probable bottleneck to deploying something like this if websites try to do so. Taking a large number of such pictures in real life would be time consuming. If you could speed up the process by automated image generation or automated creation of synthetic images by copying and pasting bills or notes between real images, that would be very useful. But doing that while preserving photo-realism and clarity to human users of how much money is in the image would be tricky.
Perhaps an advanced game engine could be used to create lots of simulations of piles of money. Like, if 100 3d objects of money are created (like 5 coins, 3 bills with 10 variations each (like folded etc), some fake money and other objects). Then these could be randomly generated into constellations. Further, it would then be possible to make videos instead of pictures, which makes it even harder for AI’s to classify. Like, imagine the camera changing angel of a table, and a minimum of two angels are needed to see all bills.
I don’t think the photos/videos needs to be super realistic, we can add different types of distortions to make it harder for the AI to find patterns.
This idea is really brilliant I think, quite promising that it could work. It requires the image AI to understand the entire image, it is hard to divide it up into one frame per bill/coin. And it can’t use the intelligence of LLM models easily.
To aid the user, on the side there could be a clear picture of each coin and their worth, that we we could even have made up coins, that could further trick the AI.
All this could be combined with traditional image obfucation techniques (like making them distorted.
I’m not entirely sure how to generate images of money efficiently, Dall-E couldn’t really do it well in the test I ran. Stable diffusion probably would do better though.
If we create a few thousand real world images of money though, they might be possible to combine and obfuscate and delete parts of them in order to make several million different images. Like one bill could be taken from one image, and then a bill from another image could be placed on top of it etc.
A user aid showing clear pictures of all available legal tender coins is a very good idea. It avoids problems more obscure coins which may have been only issued in a single year—so the user is not sitting there thinking “wait a second, did they actually issue a Ulysses S. Grant coin at some point or it that just there to fool the bots?”.
I agree that efficient generation of these types of images is the main difficulty and probable bottleneck to deploying something like this if websites try to do so. Taking a large number of such pictures in real life would be time consuming. If you could speed up the process by automated image generation or automated creation of synthetic images by copying and pasting bills or notes between real images, that would be very useful. But doing that while preserving photo-realism and clarity to human users of how much money is in the image would be tricky.
Perhaps an advanced game engine could be used to create lots of simulations of piles of money. Like, if 100 3d objects of money are created (like 5 coins, 3 bills with 10 variations each (like folded etc), some fake money and other objects). Then these could be randomly generated into constellations. Further, it would then be possible to make videos instead of pictures, which makes it even harder for AI’s to classify. Like, imagine the camera changing angel of a table, and a minimum of two angels are needed to see all bills.
I don’t think the photos/videos needs to be super realistic, we can add different types of distortions to make it harder for the AI to find patterns.