I agree, though I think there's an obvious path towards that higher order understanding of the road that humans have. Suppose they eventually have this current

I agree, though I think there's an obvious path towards that higher order understanding of the road that humans have. Suppose they eventually have this current system dialed in and they get really good, accurate bounding boxes around all interesting objects on the road. So now, in addition to their 10 second samples of video data they're collecting, they start collecting 10 second samples of scene representations. These samples of scene representations are time series of how various objects in the scene are moving and behaving over time. Many examples of just what you describe: cars with older drivers having slower reaction times; cars with distracted drivers driving recklessly; etc. Now you train a model on all that data, asking it to make predictions through time. It's going to quickly pick up on the same or similar cues that humans do. It sees an older person in a car and says that slower, cautious paths through the scene are more likely for that vehicle. They see a large, lifted truck and assume a 90% probability of a "cut off every car possible" path through the scene. Etc. So I see what Karpathy is building now as a foundation upon which they can build the higher order stuff.