I've spent a bit of time trying to understand what Watson does, and couldn't find a clear answer. I'd really appreciate a concise technical explanation.
What I got so far is that it runs a ton of different algorithms and combines the results in some sort of probabilistic reasoning to make a bet on the most likely correct answer. Is that roughly correct? And what are those algorithms then?
Did you see this summary? (The actual description of the system starts on page 9.)
EDIT: Also, the list of papers citing that article may provide papers with further detail. For example, that list contained Question analysis: How Watson reads a clue, which goes into considerably more detail about the question analysis stage.
OK, so it covers only a few human occupations:
But the list is steadily growing.
Now, connect it with a self-driving AI, and your cab e-driver can make small talk, advise on a suspicious skin lesion, evaluate your investment portfolio and help you fix an issue with your smartphone, all while cheaply and efficiently getting you to your destination.
How long until it can evaluate verbal or written customer requirements and write better routine software than your average programmer?