Jeopardy!, a game that requires vast human knowledge, has been conquered by a computer. Watson, a machine built by IBM, is able to answer most Jeopardy! questions with remarkable accuracy, often beating seasoned human champions at the trivia game.
While humans have long been able to build computers and computer systems that can mimic mechanical functions and predict outcomes, Watson can understand language like no machine ever has.
The game of Jeopardy! is full of puns and wordplay that many thought only humans could ever understand. But, working over the course of four years, computer scientists filled Watson with a series of complex algorithms that made the computer able to understand and compute even the most complicated puns. Watson's design team filled its memory banks with the entire "World Book Encyclopedia," Wikipedia, the Internet Movie Database, much of The New York Times archive and the Bible. (Watson cannot access the Internet for information).
Although they programmed it, the scientists behind Watson admit that the machine often surprises them with what answers it answers correctly and which answers it misses. But, they add that although Watson is a formidable Jeopardy! opponent, the computer's knowledge of language barely scratches the surface of how humans are able to communicate.
"If you look at the brain, it's like 40 different computers. In fact, if you look in a big book on neuroscience, you will find maybe 300 or 400 descriptions of different parts of the brain that do different things." - Marvin Minsky, MIT
"This way of learning is very powerful, and we have made great advance with it. But if you compare that to the enormity of the ways that humans learn, again, just scratching the surface." - David Ferrucci, Watson Project, IBM
1. What is artificial intelligence?
2. What sorts of tasks do computers help humans with?
3. What kind of knowledge do you think you would need to be successful at Jeopardy?
1. Do you believe that humans will ever build robots that are smarter than us or could threaten us? Why or why not?
2. Why do you think the engineers behind the Watson project are often "surprised" by Watson's answers to questions? What does that tell you about the complexity of Watson?
3. Why might elements of language like puns and wordplay be especially hard concepts for a computer to grasp?