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Researchers are trying to plant a digital seed for artificial intelligence by letting a massive computer system browse millions of pictures and decide for itself what they all mean.存倉The system at Carnegie Mellon University in Pittsburgh is called NEIL, short for Never Ending Image Learning. In mid-July, it began searching the Internet for images 24/7 and, in tiny steps, is deciding for itself how those images relate to each other. The goal is to recreate what we call common sense — the ability to learn things without being specifically taught.It's a new approach in the quest to solve computing's Holy Grail: getting a machine to think on its own using a form of common sense. The project is being funded by Google and the Department of Defense's Office of Naval Research."Any intelligent being needs to have common sense to make decisions," said Abhinav Gupta, a professor in the Carnegie Mellon Robotics Institute.NEIL uses advances in computer vision to analyze and identify the shapes and colors in pictures, but it is also slowly discovering connections between objects on its own. For example, the computers have figured out zebras tend to be found in savannahs and that tigers look somewhat like zebras.In over four months, the network of 200 processors has identified 1,500 objects and 1,200 scenes and has made about 2,500 associations.Some of NEIL's co儲存puter-generated associations are wrong, such as "rhino can be a kind of antelope," while some are odd, such as "actor can be found in jail cell" or "news anchor can look similar to Barack Obama."But Gupta said having a computer make its own associations is a different type of challenge than programming a supercomputer to do one thing very well, or fast. For example, in 1985, Carnegie Mellon researchers programmed a computer to play chess; 12 years later, a computer played and beat world chess champion Garry Kasparov.Catherine Havasi, an artificial intelligence expert at the Massachusetts Institute of Technology, said humans constantly make decisions using "this huge body of unspoken assumptions," while computers don't. She said humans can also quickly respond to some questions that would take a computer longer to figure out."Could a giraffe fit in your car?" she asked. "We'd have an answer, even though we haven't thought about it."Robert Sloan, an expert on artificial intelligence and head of the Department of Computer Science at the University of Illinois, Chicago, said the NEIL approach could yield interesting results because using language to teach a computer "has all sorts of problems unto itself."Gupta is pleased with the initial progress. In the future, NEIL will analyze vast numbers of YouTube videos to look for connections between objects.迷你倉