"Humans are learning machines that live and experience the world and take in an enormous amount of information — what they see, what they taste, what they feel, and they're taking that in from the day they're born until the day they die," he said. "And they're learning from all the input all the time. We've never even created something that attempts to do that."
The ability of a machine to learn is the essence of the field of artificial intelligence. And there have been great advances in the field, but nothing near human thinking.
"I've been in this field for 25 years and no matter what advances we make, it's not like we feel we're getting to the finish line," said Carnegie Mellon University professor Eric Nyberg, who has worked on Watson with its IBM creators since 2007. "There's always more you can do to bring computers to human intelligence. I'm not sure we'll ever really get there."
Bart Massey, a professor of computer science at Portland State University, quipped: "If you want to build something that thinks like a human, we have a great way to do that. It only takes like nine months and it's really fun."
Working on computer evolution "really makes you appreciate the fact that humans are such unique things and they think such unique ways," Massey said.
Nyberg said it is silly to think that Watson will lead to an end or a lessening of humanity. "Watson does just one task: answer questions," he said. And it gets things wrong, such as saying grasshoppers eat kosher, which Nyberg said is why humans won't turn over launch codes to it or its computer cousins.
Take Tuesday's Final Jeopardy, which Watson flubbed and its human competitors handled with ease. The category was U.S. cities, and the clue was: "Its largest airport is named for a World War II hero; its second largest, for a World War II battle."
The correct response was Chicago, but Watson weirdly wrote, "What is Toronto?????"
A human would have considered Toronto and discarded it because it is a Canadian city, not a U.S. one, but that's not the type of comparative knowledge Watson has, Nyberg said.
"A human working with Watson can get a better answer," said James Hendler, a professor of computer and cognitive science at Rensselaer Polytechnic Institute. "Using what humans are good at and what Watson is good at, together we can build systems that solve problems that neither of us can solve alone."
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