[TeMPOraL]

The often forgotten difference between ML and humans is that we learn from stereoscopic video streams, not from a bunch of static pictures. There's a lot more information in a few seconds of watching cars on the road than in a thousand pictures of different cars. We get to see the 3D picture (we have dedicated circuits for that), hear 3D audio and perceive temporal data. We correlate all that and many more data sources to form categoties.

ML trained on bunch of static pictures is like humans dealing with those abstract geometrical riddles that are used on IQ tests. They're difficult for us, because they're not related to our normal, everyday experience.