This is why I personally feel like Tesla's approach is more likely to "win". The fundamental blocker to self-driving cars is not sensing / sensor fusion, it is intelligence. And the Tesla approach seems much more likely to achieve functional intelligence than Waymo's.
While I agree with basically all of this, and find the FSD on my Tesla to be quite useful, a question pops into my mind.
Why can't Waymo ALSO develop the same smarts and just also solve the sensor fusion issue such that they can use the right set of sensors in the right environmental conditions, and then leapfrog Tesla's capabilities?
You can have intelligence with lidar.
You can have even more intelligence with both.
Naaah, Tesla has no edge in intelligence either. It's just a PR piece to sell to investors.
I like both approaches. The fact that both exist is a clear win for consumers.
Tesla's approach seems like a bet that A) AI will reach human-level driving intelligence before lidar becomes cost-efficient, in which case their current sensors will be sufficient to achieve at least human-level performance; and B) ~human-level performance will be sufficient to achieve large-scale consumer and regulatory acceptance. Waymo seems to be taking the other side of that bet.
If Tesla is right, their solution should scale faster, and they can worry about adding superhuman sensory capabilities later. If Waymo is right, all the Cybercabs that Tesla is pumping out right now are destined for the scrapyard, or at best will spin their wheels in beta testing for years while Waymo speeds ahead.
Tesla is putting its money on the bull case for self-driving as a whole. If Tesla wins that bet, it means we all get access to a useful version of the tech years earlier. If Waymo wins, that's great too, but it means that for better or worse lidar will be a bottleneck to scaling the tech.
The whole thing is basically a rehash of Intel vs TSMC on EUV in the 2010s.