In a historic moment for AI, computers gain ability to generalize learning between activities

With the many meteoric victories artificial intelligence has scored in the recent past, it’s easy to forget the story line has basically been one of evolution rather than revolution. The deep neural networks upon which the likes of Apple’s Siri and Google Now are built have been in existence since at least the late 1950s, when the Frank Rosenblatt pioneered a multi-layer neural network called the perceptron and suggested additional layers with mathematical notations. Much of the advances made in the field since then can be traced to better data sets for training neural nets and more sophisticated applications of the underlying technology. However, one pièce de résistance has always remained: No matter how good at prediction a neural network became, it lacked the ability to generalize that ability to…


Link to Full Article: In a historic moment for AI, computers gain ability to generalize learning between activities

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