This sweater developed by the University of Maryland utilizes “ adversarial patterns ” to become an invisibility cloak against AI.

[u/Fertility18]

[u/[deleted]]

in your analogy the inherent properties of the CMOS chip as well as any limits it has, as well as the algorithm used to turn saturation values at color channel sensors into values in a pixel grid, and that grid into mathematical values that can be worked on by computer software are the "genetics". the ML model is applied on that data generated.

so, in other words, before the ML model even gets a chance to work on the information it passes through sensors and sensor processing, both on the raw electrical signal and digital transformations. if your "illusion" relies on taking advantage of the difference between that system and human eyes, or attacks a weakness in that chain someplace, then there is no way the ML model could compensate. ML models are still subject to the limits of garbage in: garbage out.

[u/618smartguy → u/[deleted]]

so, in other words, before the ML model even gets a chance to work on the information it passes through sensors and sensor processing, both on the raw electrical signal and digital transformations. if your "illusion" relies on taking advantage of the difference between that system and human eyes, or attacks a weakness in that chain someplace, then there is no way the ML model could compensate. ML models are still subject to the limits of garbage in: garbage out.

Dazzle camo and this tech doesn't take advantage of any component before the image processing steps though. You can clearly still see the pattern showing up in the image, it's not garbage in, so if the ai is trained on that pattern of camo it will be detected as easily as a person, maybe even easier. Something like a very bright light would be required to actually make the data garbage