I can shed some light on this phenomena: These models are trained on many images but no thought is put into the "generalisation" aspect the ML community was so

I can shed some light on this phenomena: These models are trained on many images but no thought is put into the "generalisation" aspect the ML community was so obsessed with during the deep-learning era. Whatever Kinbaku is... haha I think a key part that's missing currently is the agent training approach: https://youtu.be/v3UBlEJDXR0?si=8w4Jt0bNEBfIXkZl https://youtu.be/v3UBlEJDXR0?si=8w4Jt0bNEBfIXkZl It's very easy to create a "Stochastic Parrot" but I'm quite sure these models are capable of learning underlying information such as correct layout of a knot - given the right data and curriculum of course. Maybe slight architecture tweaks. I'm sure this is the reason we're starting to see a normal amount of fingers or ability to write text. Proof of concept was 2015 until 2022 now we're starting to see interesting things come out of the workshops.