I can understand how a neural network can be trained to recognize a really complex pattern that is almost impossible to describe in code, and I can understand how code can be written to create really complex decision trees that are clearly understood and easily modified without the need for vast amounts of training data.  When it comes to the full AI solution for self driving cars, I have a hard time imagining where the neural nets stop and the code starts and how you find that balance.  I would love to see a video giving a detailed overview of the AI architecture and what parts are neural nets and what parts are code.,(reply>), If you're assuming that a full solution to autonomous driving can exist, I'm not sure that's a valid assumption.  Andrej Karpathy's comments at last year's AI day hinted at a mix of neural networks and stochastics, but yes, the current mix would be interesting.  Overall, I'm skeptical that the problem of autonomous driving is significantly more soluble than Artificial General Intelligence.