George Hotz puts it quite neatly, companies like Waymo have spent millions so far and someone sitting at home could not use their product highlighting their inefficiency. He further states to think about how a human would drive a car, does a human need LiDAR to drive a car? No, not really. The legitimacy in his statements come from the fact ( imo ) that comma.ai ( his self-driving startup ) outperforms with less funding than one could imagine by solving the problem absolutely as a Computer Vision problem. They treat it slightly different than Tesla but in all, it goes on to show that you don't really need to use LiDAR to solve the problem, it can potentially solve the problem, but it's an inefficient way to do it.
I hate this argument. It doesn't hold for several reasons:
- A human driver has blind spots (which btw Tesla avoids by having cameras surrounding the car)
- Human reactions times are very poor at even moderate speeds
- Human vision is affected by glare
- Humans are terrible at driving in low light conditions
- Humans are terrible at driving in inclement weather - snow storms or heavy rainfall
LIDAR doesn't solve many of these problems but to claim that self driving is solvable by vision alone is a bad take. Multiple sensors add redundancies and reduce errors. Teslas are already equipped with ultrasound sensors and radar so it's not technically solving a Computer Vision only problem.
Radar+sonar do.
Musk needs to team up with the Biden Administration and work in tandem on infrastructure - that may be the only way we see self-driving road-ready cars before 2040.
Elon: "A major part of real-world AI has to be solved to make unsupervised, generalized full self-driving work, as the entire road system is designed for biological neural nets with optical imagers"
Seems like he's inching closer to reality by the day.