Unstructured learning on Image+Text pairs has exploded and set STOTA on benchmark across the field. While the data coming from LIDAR may be better. There is no where near the amount of LIDAR data in the world. Images and cameras have the advantage here where internet is full of weakly labeled data that turns out to be the key for building model backbones that you can retrain for downstream tasks.
For example, if a a car is stopped at a red light and it sees a child across the street running and the child runs behind a truck it will take her 5 seconds to get past at her last observed rate of speed, and the light turns green at a moment when the car would hit the child as she emerges from behind the truck (given the preceding) as it drives by the truck, do any ML systems have the ability to predict this?
People would likely be cautious if they saw the same scene, and would approach slowly. I don't think that current ML systems are able to do that, but would like to hear some informed opinions.
About 2/3rds down the page features 'Object tracking' and 'Robotic control'