I was never convinced by the "vision only" approach - I don't see the point of throwing out or refusing to have additional data from other sensors.

I suppose that with modern ML they can just toss it in the blender and reap the benefits ...

I'm not talking about vision (cameras) vs lidar etc, just the Tesla FSD architecture that separates the "vision" component (turning camera/sensor inputs into symbolic road/sign/vehicle/pedestrian/etc data), and the driving component which takes the vision data, plus current location and destination, and uses that to actually drive the car - switch lanes, make turns, avoid obstacles etc etc.