with rockets and electric vehicles however science & engineering had an "angle of attack" based on fundamental discoveries in physics, and centuries of continuous progress , that's not the case with AI.
Deep learning is great for a few narrow cases but there is no path to general human-like intelligence required for a complex human-like activity like self-driving which has an infinitely long tail of edge cases you can't train for with these large and "dumb" ML models equivalent to curve fitting.
The mistake of Tesla is betting on covering more and more of these edge cases incrementally but what's needed is qualitative change rather than incremental improvement.
By qualitative change I mean actual model of human-like intelligence, including reasoning and "common sense", which is a prerequisite for self-driving. The solution to this problem requires more than the sum of its parts.
It's kind of like planning to build an airplane before figuring out Newton' basic laws of physics.
