Any doubts that computers can do natural language processing ended dramatically yesterday as IBM’s Watson computer defeated the world’s two best players in the TV quiz show Jeopardy. Although the task was constrained, it clearly shows that it won’t be too long before we’ll have computers that can understand most of what we say. This Nova episode gives a nice summary of the project. A description of the strategy and algorithms used by the program’s designers can be found here.
I think there are two lessons to be learned from Watson. The first is that machine learning will lead the way towards strong AI. (Sorry Robin Hanson, it won’t be brain emulation). Although they incorporated “hard coded” algorithms, the engine behind Watson was supervised learning from examples. The second lesson is that we may already have all the algorithms to get there. The Watson team didn’t have to invent any dramatically new algorithms. What was novel is the way they integrated many existing algorithms. This is analogous to what I called the Hopfield Hypothesis in that we may already know enough biology to understand how the brain works. What we don’t understand yet is how these elements combine.
Addendum: Here is a YouTube link for the show last night.