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Dean was referring to the rapid increase in machine learning algorithms' accuracy, driven by recent progress in deep learning, and the still untapped potential of these improved algorithms to change the world we live in and the products we build.
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A lot of the big developments in deep learning, for example, a lot of the progress that happened in speech at Apple, Microsoft and so on, all those people where summer school students who ended up doing internships at these companies.
This paper critically examines the main advances in deep learning.
Recently, dropout has seen increasing use in deep learning.
The "black box" problem is endemic in deep learning.
There are some bottlenecks in deep learning.
In deep learning, words are embedded to represent words.
In deep learning, deep neural network (DNN) hyperparameters can severely affect network performance.
What has your journey been like in deep learning?
In deep learning, applications use an algorithm called deep neural networks.
Language remains a very tricky problem for artificial intelligence, but in recent years researchers have made progress in applying deep learning to the problem (see "AI's Language Problem").
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