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John Hopfield and Geoffrey Hinton have won the Nobel Prize in Physics for his or her pioneering work on artificial intelligence, which has contributed to scientific advances but raised fears in regards to the risks of misuse.
The award highlights the elemental role that the AI ​​field of machine learning is now playing in research as a consequence of the volumes of information it may possibly process quickly. Hinton, who left Google last 12 months to talk more freely, said he was “amazed” by Tuesday's honor and spoke of the ability and dangers of AI.
“It will likely be wonderful in some ways,” Hinton said by phone on the awards ceremony in Stockholm, pointing to AI-driven advances in healthcare and industrial productivity. “But we also should worry about a spread of possible dire consequences – particularly the chance of this stuff spiraling uncontrolled.”
Hopfield and Hinton won the SKr11 million ($1.06 million) prize for “fundamental discoveries and inventions” in machine learning because the Eighties, the Nobel Assembly said. Their work contributed to the event of so-called artificial neural networks, which mimic the human brain's biological wiring to process information.
Hinton, revered in technology circles as considered one of the “godfathers” of AI, said its impact was of historic proportions.
It may have a huge impact. . . comparable to the economic revolution,” he said. “But as an alternative of surpassing humans in physical strength, they’ll surpass humans in mental ability. We don’t have any experience of what it’s wish to have things smarter than us.”
Hopfield, an American physicist, has developed a synthetic neural network to store and restore patterns.
Hinton, a British-Canadian computer scientist, used Hopfield's research to construct a brand new network often called the Boltzmann machine. This will be used to categorise images or create latest examples of learned pattern types.
Together they helped “initiate the present explosive development of machine learning,” said the Nobel organizers.
Rhodri Cusack, a cognitive neuroscientist at Trinity College Dublin, said a “thriving interaction” between brain science and artificial intelligence had helped drive progress in each fields.
“In short, machines help us understand ourselves, which in turn opens latest avenues for technology,” Cusack said. “None of this may be possible without the groundbreaking work of Hopfield and Hinton.”
Adrian Smith, president of the British Royal Society, which elected Hinton as a fellow in 1998, referred to the Nobel laureate's research comparing brain damage in humans with lack of function in neural networks.
“(He) found striking similarities to human impairments, corresponding to name recognition and lack of categorization,” Smith said. “This could well be the start of autonomous intelligent brain-like machines.”
“Machine learning has develop into a part of our day by day lives in areas corresponding to facial recognition, language translation and medical diagnosis,” said Ellen Moons, chair of the Nobel Committee for Physics.
But the technology's scope and ever-increasing capabilities have stoked fears starting from its use in political repression to the chance that machines might sooner or later evolve to operate independently of human instructions.
“While machine learning has tremendous advantages, its rapid development has also raised concerns about our future,” Moons said. “Together, people have a responsibility to make use of this latest technology in a protected and ethical manner for the best advantage of humanity.”
Hinton and his AI colleagues Yoshua Bengio and Yann LeCun won computer science's highest prize, the Turing Award, in 2018. Hinton currently works on the University of Toronto and Hopfield at Princeton.
