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London: A computer that is able to "learn" like a human brain and recognize the picture of a cat, is being touted as a breakthrough in technology by Google scientists.
The computer is based on a "neural network" of 16,000 processing cores with more than a billion interconnections , each very roughly simulating a connection in a human brain.
A team from Google's cutting-edge research lab, Google X, and Stanford University , fed the system 10 million thumbnail images taken from YouTube as "training" and then tested whether it was able to recognize 20,000 objects in new images.
According to The New York Times, it performed more than twice as accurately as any previous neural network . Among the objects the system learned to recognize was a cat, one of the most regulars star of viral clips uploaded by YouTube members. "We never told it during the training, "This is a cat" , the Telegraph quoted Google fellow Jeff Dean as saying.
"It basically invented the concept of a cat," he said.Overall, the neural network achieved 15.8% accuracy . As well as cats' faces, it learned the "concepts" of human faces and bodies, by compiling a ghostly image of their general features.
The research differed from how most artificially intelligent systems are trained, in that it was given no help by human supervisors labelling features.
"The idea is that instead of having teams of researchers trying to find out how to find edges, you instead throw a ton of data at the algorithm and you let the data speak and have the software automatically learn from the data ," Andrew Ng of Stanford University added.
The computer is based on a "neural network" of 16,000 processing cores with more than a billion interconnections , each very roughly simulating a connection in a human brain.
A team from Google's cutting-edge research lab, Google X, and Stanford University , fed the system 10 million thumbnail images taken from YouTube as "training" and then tested whether it was able to recognize 20,000 objects in new images.
According to The New York Times, it performed more than twice as accurately as any previous neural network . Among the objects the system learned to recognize was a cat, one of the most regulars star of viral clips uploaded by YouTube members. "We never told it during the training, "This is a cat" , the Telegraph quoted Google fellow Jeff Dean as saying.
"It basically invented the concept of a cat," he said.Overall, the neural network achieved 15.8% accuracy . As well as cats' faces, it learned the "concepts" of human faces and bodies, by compiling a ghostly image of their general features.
The research differed from how most artificially intelligent systems are trained, in that it was given no help by human supervisors labelling features.
"The idea is that instead of having teams of researchers trying to find out how to find edges, you instead throw a ton of data at the algorithm and you let the data speak and have the software automatically learn from the data ," Andrew Ng of Stanford University added.
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