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n Turing wondered what it would take for machines to become intelligent. John von Neumann wondered what it would take for machines to self-reproduce. Claude Shannon wondered what it would take for machines to communicate reliably, no matter how much noise intervened. Norbert Wiener wondered how long it wo
use, because this method lacks transparency. While recognizing the impressive achievements in deep learning by colleagues such as Michael Jordan and Geoffrey Hinton, he feels uncomfortable with this kind of opacity. He set out to understand the theoretical limitations of deep-learning systems and points out that
, “A Scientist Rebels,” Zhe Atlantic Monthly, January 1947. 31 Warren Weaver, “Recent Contributions to the Mathematical Theory of Communication,” in Claude Shannon & Warren Weaver, The Mathematical Theory of Communication (Urbana, IL: University of Illinois Press, 1949), p. 8 (emphasis in original). Shan
euroscience communities need to interact closely, something that is happening already. Some of today’s greatest exponents of machine learning—such as Geoffrey Hinton, Zoubin Ghahramani, and Demis Hassabis—have backgrounds in cognitive neuroscience, and their success has been at least in part due to attempts to mod
n Turing wondered what it would take for machines to become intelligent. John von Neumann wondered what it would take for machines to self-reproduce. Claude Shannon wondered what it would take for machines to communicate reliably, no matter how much noise intervened. Norbert Wiener wondered how long it wo
use, because this method lacks transparency. While recognizing the impressive achievements in deep learning by colleagues such as Michael Jordan and Geoffrey Hinton, he feels uncomfortable with this kind of opacity. He set out to understand the theoretical limitations of deep-learning systems and points out that
, “A Scientist Rebels,” Zhe Atlantic Monthly, January 1947. 31 Warren Weaver, “Recent Contributions to the Mathematical Theory of Communication,” in Claude Shannon & Warren Weaver, The Mathematical Theory of Communication (Urbana, IL: University of Illinois Press, 1949), p. 8 (emphasis in original). Shan
euroscience communities need to interact closely, something that is happening already. Some of today’s greatest exponents of machine learning—such as Geoffrey Hinton, Zoubin Ghahramani, and Demis Hassabis—have backgrounds in cognitive neuroscience, and their success has been at least in part due to attempts to mod
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