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The Deep Learning Revolution

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The Deep Learning Revolution

By: Terrence J. Sejnowski
Narrated by: Shawn Compton
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About this listen

How deep learning - from Google Translate to driverless cars to personal cognitive assistants - is changing our lives and transforming every sector of the economy.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

©2018 Massachusetts Institute of Technology (P)2019 Tantor
Biological Sciences Computer Science Machine Theory & Artificial Intelligence Science Technology Machine Learning Data Science Artificial Intelligence

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Critic reviews

"If you want to understand AI, you need to read The Deep Learning Revolution." (Erik Brynjolfsson, coauthor of The Second Machine Age)

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A comprehensive history of the deep learning / neural network field by someone who was there with Hinton et al. I particularly enjoyed the time discussing the biological / neuroscience origins of elements of NN architecture. There were useful conversations on intelligence too, so plenty to keep the reader entertained.

Don't read for a primer on neural networks, there are other more technical books out there for that.

It wasn't the best flowing book of all time, and the narrator was average at best, so I've given this 4 stars.

History of NNs & the overlap with bio/neuroscience

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Aanrader: Voor lezers die willen begrijpen hoe deep learning zich heeft ontwikkeld, vanuit menselijke drijfveren, technische ontdekkingen en persoonlijke verhalen, is dit een uitstekend startpunt.

Behandelt kernproblemen zoals het gebrek aan verklaring van hoe netwerken tot besluiten komen

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