[gibsonf1]

Exactly, that is how that stuff works. Past patterns in the Ml neural net generated from massive data and training try to figure out the label of things from various sensors, and then given that label, try to figure out other things that might happen based on the label and event stream. These patterns can recognize with a certain probability similar patterns, but they have no way to cope with brand new patterns. Those brand new patterns, although they may only occur 1 out of 100 experiences - or lets say 3 days a year when your're driving, something fully novel occurs, this will kill you if you are relying on FSD. Until the systems try to think like humans, they simply wont.