Inside the Artificial Intelligence Revolution: A Special Report
Originally shared by Ward Plunet
Inside the Artificial Intelligence Revolution: A Special Report
LeCun was a pioneer in deep learning, a kind of machine learning that revolutionized AI. While he was working on his undergraduate degree in 1980, he read about the 1958 "perceptron" and the promise of neural-network algorithms that allow machines to "perceive" things such as images or words. The networks, which mimic the structure of the neural pathways in our brains, are algorithms that use a network of neurons, or "nodes," to perform a weighted statistical analysis of inputs (which can be anything – numbers, sounds, images). Seeing the networks' potential, LeCun wrote his Ph.D. thesis on an approach to training neural networks to automatically "tune" themselves to recognize patterns more accurately – ultimately creating the algorithms that now allow ATMs to read checks. In the years since, refinements in neural networks by other programmers have been the technological underpinning in virtually every advance in smart machines, from computer vision in self-driving cars to speech recognition in Google Voice. It's as if LeCun largely invented the nervous system for artificial life.
Read more: http://www.rollingstone.com/culture/features/inside-the-artificial-intelligence-revolution-a-special-report-pt-1-20160229#ixzz424xxh9ZS
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http://www.rollingstone.com/culture/features/inside-the-artificial-intelligence-revolution-a-special-report-pt-1-20160229
Inside the Artificial Intelligence Revolution: A Special Report
LeCun was a pioneer in deep learning, a kind of machine learning that revolutionized AI. While he was working on his undergraduate degree in 1980, he read about the 1958 "perceptron" and the promise of neural-network algorithms that allow machines to "perceive" things such as images or words. The networks, which mimic the structure of the neural pathways in our brains, are algorithms that use a network of neurons, or "nodes," to perform a weighted statistical analysis of inputs (which can be anything – numbers, sounds, images). Seeing the networks' potential, LeCun wrote his Ph.D. thesis on an approach to training neural networks to automatically "tune" themselves to recognize patterns more accurately – ultimately creating the algorithms that now allow ATMs to read checks. In the years since, refinements in neural networks by other programmers have been the technological underpinning in virtually every advance in smart machines, from computer vision in self-driving cars to speech recognition in Google Voice. It's as if LeCun largely invented the nervous system for artificial life.
Read more: http://www.rollingstone.com/culture/features/inside-the-artificial-intelligence-revolution-a-special-report-pt-1-20160229#ixzz424xxh9ZS
Follow us: @rollingstone on Twitter | RollingStone on Facebook
http://www.rollingstone.com/culture/features/inside-the-artificial-intelligence-revolution-a-special-report-pt-1-20160229
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