01.03.2018
Public programming: Panel discussion (22.02.2019)
"Deep learning has led to rapid progress in open problems of artificial intelligence—recognizing images, playing Go, driving cars, automating translation between languages—and has triggered a new gold rush in the tech sector. But some scientists raise worries about slippage in scientific practices and rigor, likening the process to “alchemy.” How accurate is this perception? And what should the field do to combine rapid innovation with solid science and engineering?"
Speakers:
Michael Collins, Google Research, Columbia University
Yann LeCun, Facebook, New York University
Joelle Pineau, Facebook, McGill University
Zachary Lipton, Carnegie Mellon University
Shai Shalev-Shwartz, Hebrew University of Jerusalem
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https://youtu.be/N_g-ZBWUy_k
-
Public programming: Panel discussion (22.02.2019)
"Deep learning has led to rapid progress in open problems of artificial intelligence—recognizing images, playing Go, driving cars, automating translation between languages—and has triggered a new gold rush in the tech sector. But some scientists raise worries about slippage in scientific practices and rigor, likening the process to “alchemy.” How accurate is this perception? And what should the field do to combine rapid innovation with solid science and engineering?"
Speakers:
Michael Collins, Google Research, Columbia University
Yann LeCun, Facebook, New York University
Joelle Pineau, Facebook, McGill University
Zachary Lipton, Carnegie Mellon University
Shai Shalev-Shwartz, Hebrew University of Jerusalem
-
https://youtu.be/N_g-ZBWUy_k
-
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Эту запись оставил(а) на своей стене Алексей Дурнев
