I think Uber's essential mistake is to go from "autonomous vehicles are the only way our business model makes sense" to "we should be building autonomous vehicles".
Their expertise is in UI, routing algorithms, and business development. There is nothing in their background that indicates they should have any competitive advantage in building autonomous vehicles over Google/Waymo, the proverbial 800-pound gorilla of everything AI, or GM/Cruise, with experience in safety-critical engineering and oodles of capital to throw at the problem.
Sure, base your business model on the eventual development of driverless cars, but buy the damned things from the professionals, eh?
They essentially bought CMU's robotics department which ranks #1 (in terms of universities) in almost all AI conferences. They also bought part of UToronto's ML department which is where GHinton was teaching.
I think uber has been on a hiring push the last few years for quality engineers so it's not inconceivable they could make this work. I also think them working on this mostly makes business sense. To me it sounds like they rushed the development and tried going too far way too fast.
Their expertise is in UI, routing algorithms, and business development. There is nothing in their background that indicates they should have any competitive advantage in building autonomous vehicles over Google/Waymo, the proverbial 800-pound gorilla of everything AI, or GM/Cruise, with experience in safety-critical engineering and oodles of capital to throw at the problem.
Sure, base your business model on the eventual development of driverless cars, but buy the damned things from the professionals, eh?