Would you believe someone who in 1970 said, "We landed a man on the moon. In 50 years we'll surely have flying cars!"
I'm sure a lot of people believed that in 1970 but look where we are now. Technology accelerates at a much faster pace but often times in ways that you don't expect. The people in 1970 probably didn't imagine smartphones with a global 4G network but instead of flying cars we got this.
Or fusion power. Or natural language conversations with computers (as opposed to largely rote voice recognition).
Deep learning/machine learning have made remarkable advances in recent years--primarily because of both computational (esp. GPU) and storage/data advances.
However, in spite of a lot of money and talent expended on understanding organic brains and human-level cognition over the decades, progress has been slow and there's a general belief among scientists who work in AI spanning CS and neuroscience that there are aspects to human learning and reasoning that we just don't really understand yet.
And that more deep learning, data, and programmed rules won't get you to autonomous vehicles outside of some limited domains. (Which is valuable by itself; it just doesn't get you to robo-taxies.)
The problem isn't in the availability of technology but the (lack of) problem it solves. People can barely drive on roads safely and there are infinitely more regulations and skills required for flying, even with the relative little amount of air traffic. If anything, autonomous vehicles could be precursor for individual aerial transport.
I'm sure a lot of people believed that in 1970 but look where we are now. Technology accelerates at a much faster pace but often times in ways that you don't expect. The people in 1970 probably didn't imagine smartphones with a global 4G network but instead of flying cars we got this.