I disagree (that it was inevitable...obviously it ended up not being a good fit, ha). This comment from the original announcement has an insightful point of view on how much sense it could make to have someone concerned with correctness and reliability heading the AI/Autonomous Driving team.
If the main source of problems was related to software architecture, it may have made sense. Academic AI people may be stronger on theory and end up with unmaintainable bridges. OTOH good architecture will be responsive to the fundamental underlying problems being solved, and that requires depth.
Compilers give a good base for transferring to things like databases, operating systems and IO heavy systems with lots of transforms / filters etc. They also ingrain a way of thinking that isn't native to most devs - writing code that generates code. Monads and other approaches to dynamically composing a computation - they come easy.
I agree on that. I personally think AI (and especially topics like deep learning) only makes up for a small part of autonomous driving or driver assistance in general. The remaining parts will be lots of old-fashioned control theory, signal-processing, general good software engineering practices, having a good software and system architecture, being able to build a fully deterministic (hard-realtime capable) system. For the latter topics a highly experienced person with more of an engineering background would be a better fit than a researcher with with a mostly-algorithm background.
