Could someone who understands this space weigh in on how technically interesting this is? (Or isn't?) In particular, their research paper on "End to End Learning for Self-Driving Cars"[1] seems to yield a system that requires an unacceptable amount of manual intervention: in their test drive, they achieve autonomous driving only 98% of the time. But I have no real expertise in this space; perhaps this result is impressive because it was end-to-end or because of the relatively little training? Is such a system going to be sufficiently safe to be used in fully autonomous systems? Or is NVIDIA's PX 2 interesting but not at all for the way it was used in their demonstration system?
It's incredibly freaking amazing if they are using deep learning to drive via mainly cameras only 98 percent of the time. No one else can do that. 98 percent is obviously a lot.
Thanks -- that answers the question! So fair to say that it's impressive because of the absence of LIDAR and/or other sensors -- and that by adding LIDAR to such a system one could presumably get towards 0% manual intervention?
The difference between 98% and 99.999% is very difficult to solve, and it's not going to happen in the next 5 years. LIDAR can't help, for example, with obeying a police officer gesture.
[1] http://images.nvidia.com/content/tegra/automotive/images/201...