In 2015 Elon Musk, Tesla's boss, predicted his cars would be capeble of "complete autonomy" by 2017. Mr Musk is famous for missing his own deadlines. But he is not alone. General Motors said in 2018 that it would launch a fleet of cars without steering wheels or pedals in 2019; in June it changed its mind.
The future, in other words, is stuck in traffic. Partly that refects the tech industry's preference for grandiose promies. But self-driving cars were also meant to be flagship for the power of AI. Their struggles offer valuable lessons in the limits of the world's trendies technology.
One is that, for all the advances in machine learning, machines are still not very good at learning. Most humans need a few dozen hours to master driving. Waymo's cars ahve had over 10m miles of practice, and still fall short. And once humans have learned to drive, even on the easy streets of Phoneix, they can, with a little effort, apply that knowledge anywhere, rapidly learning to adapt their skills to rush-hour Bangkok or a gravel-track in rural Greece. Computers are less flexbile. AI researchers have expended much brow-sweat searching for techniques to help them match the quick-life learning displayed humans. So far, they have not succeeded.
Another lesson is that machine-learning systems are fragile. Learning solely from existing data means they struggle with situations that they have never seen before. Humans can use general knowledge and on-the-fly reasoning to react to thing that new to them. Autonomous-car researchers all these unusual situations "edge cases". Driving is full of them, though most are less dramatic. Mishandle edge cases seem to have been a factor in at least some of the deaths caused by autonomous cars to date. The problem is so hard that some firms think it may be easier to re-engineer entire to support limited self-driving than to build fully autonomous cars.
The most general point is that, like most technologies, what is currently called "AI" is both powerful and limited. Recent progress in muchine learning has been transformative. At the same time, the eventual goal-the creation in a machine of a fluid, general, human-like intelligence-remains distant. Few doubt that a completely autonomous car is possible in principle. But the consensus is, increasingly, that it is not coming very soon.
