Still, artificial intelligence experts agree that the Carnegie Mellon approach is innovative. Many semantic learning systems, they note, are more passive learners, largely hand-crafted by human programmers, while NELL is highly automated. Whats exciting and significant about it is the continuous learning, as if NELL is exercising curiosity on its own, with little human help, said Oren Etzioni, a computer scientist at the University of Washington, who leads a project called TextRunner, which reads the Web to extract facts.
Computers that understand language, experts say, promise a big payoff someday. The potential applications range from smarter search to virtual personal assistants that can reply to questions in specific disciplines or activities like health, education, travel and shopping.
The technology is really maturing, and will increasingly be used to gain understanding, said Alfred Spector, vice president of research for Google. Were on the verge now in this semantic world.
With NELL, the researchers built a base of knowledge, seeding each kind of category or relation with 10 to 15 examples that are true. In the category for emotions, for example: Anger is an emotion. Bliss is an emotion. And about a dozen more.
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