Didn’t we know already since the early '00s at least with the DARPA Grand Challenge - Wikipedia that a machine learning approach is more robust? What are you doing if not trying to make an AI pilot?
My assumption has always been that AWE will lag behind full self driving a bit, you’re trying to solve the same kind of problem but you have smaller teams and budgets, so you have little choice but to try to apply the advances of self driving to your system. But then your system is perhaps easier, you’re perhaps less dependent on vision, except for spotting birds, and can do more with accelerometers and other sensors.
One of the many takeaways that I liked about the talk is that you can design a kind of Grand Theft Auto for your car to move around in and learn to navigate. For an AWE that might be an extremely gusty and congested sky with tethers constantly failing.