IBM's Watson

Why IBM's Watson Is Smarter Than Google

While working on my book about IBM's Jeopardy-playing computer, the most common question I encounter is this: Doesn't Google already answer questions?

The short answer is no. Google depends on our brains in two ways: It gets us to think like a computer when formulating our query, picking three or four words that will make most sense to the machine. Then it directs us to the neighborhood of the answer we're looking for, but leaves it to our infinitely more nuanced brains to find exactly what we're looking for there.

Watson, which will face off against two Jeopardy legends, Ken Jennings and Brad Rutter, in February, has to handle all that work by itself. It must decipher complex English, hunt down possible answers, choose one, and decide if it has enough confidence to bet on it.

Here's an example: "When 60 Minutes premiered, this man was U.S. president. That's a tough one for a computer. It has to understand what "premiered" means and that it's associated with a date. Then it has to figure out the date when an entity called 60 Minutes premiered, and then find out who was U.S. president at that time. In short, it requires a ton of contextual understanding -- or a statistical simulation of it -- and then two different hunts, one for the date, the second for the president.

Once Watson has a list of possible answers (or "responses," as they call them on Jeopardy!), it has to figure out which one merits the most confidence, and if it's sure enough of the answer to place a bet on it. All these takes place in about 3 seconds. (By the way, the answer is Lyndon Johnson.)

Watson has more than 100 algorithms leading it to solve these Jeopardy clues. Each one has its specialty. One of them helps it with specifically this kind of question. It's called "nested decomposition," and it involves breaking the clue into two different hunts. This may sound really obscure, and only marginally useful. But if you listen to people asking questions, a lot of them require this type of hunt. "What's the best pizza joint near campus? Which southern state has a big steel industry? etc.

So you might think that Watson could become the next Google. One big problem. To solve that clue, Watson uses more than 2,000 processors and consumes loads of electricity. Google, in those same three seconds, responds to millions of search queries. Google uses perhaps one-billionth of Watson's resources, or less, to handle each query. So the two approaches don't compete. But in coming years, Google and the other search engines will start to answer questions, more like Watson. (They're starting with simple ones. Nested decomposition is still a ways off.) And to get Watson jobs outside of show biz, IBM will have to figure out how to run such machines for a fraction of the cost.