The discussion is fun and all, but the work that Tesla computer vision and machine learning teams are doing is ground breaking and they are way way ahead on the bleeding edge of what is possible, compared to Detroit, Tokyo and Germany.

I've worked in trying to use CNNs and image and depth sensor fusion to accomplish way more simple tasks then FSD and this stuff is really hard and takes a vast commitment of time, energy and capital.

But it indeed might take another decade for a general solution that is at least as good as an average human. But interim performance milestones with minimal but critical occasional human assist could still be very acceptable to some of us

Meh, size of research team does not strongly correlate outcome quality and innovation. Furthermore bulky teams can reinforce momentum on a certain approach that turns into a dead end long term. Meanwhile small teams elsewhere start from a completely orthogonal approach and sometimes truly innovate. I'm not convinced Google has the right approach for the long term, organizationally or technically. Not saying ChatGPT is a Google killer either, yet.