Computers have always been very good at performing very specific tasks in highly proscribed circumstances. What were learning to do is expand the circumstances within which the computer can operate, but as you say the tasks are still very highly specific.

We could probably have programmed a computer to drive a car back in the 70s, within an extremely specific configuration of roads and with no traffic or pedestrians. Now self driving cars have very advanced sensors, can cope with other traffic, pedestrians and a much wider range of road geometries. But it's still only useful for driving a car, you couldn't take the same program and teach it to even controll a boat or a plane let alone play Jeopardy, predict the weather or trade on the stock market. Systems like this are going to be very useful, but they are not taking us on a path to develop strong general AI.