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1
Introduction
2
The Story Begins
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Computer Vision
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The Brain
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Frank Rosenblatt
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The Perceptron
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Minsky Papert
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David Rummelheart
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Jim DeCarlo
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David Hubel
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Toby Del Brooke
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The Magic Sauce
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Convolutional Network
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Examples
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Google Translate
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Unsupervised Learning
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The basal ganglia
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The actor critic model
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The basal ganglia model
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The reward problem
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The problem
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The model
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The glider
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How it works
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Social robots
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Machine learning
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Neuroscience
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Brain Initiative
Description:
Explore the groundbreaking advancements in deep learning through this comprehensive lecture by Terrence Sejnowski from the Salk Institute for Biological Studies. Delve into the historical roots of artificial intelligence, tracing its evolution from early computer vision attempts to modern convolutional networks. Examine the parallels between artificial neural networks and the human brain, with insights into pioneering figures like Frank Rosenblatt and David Rumelhart. Discover the "magic sauce" behind deep learning's success and its applications in various fields, including Google Translate and unsupervised learning. Investigate the intricacies of the basal ganglia and its role in reinforcement learning, along with the challenges of reward-based learning in AI. Gain insights into cutting-edge topics such as social robots, the intersection of machine learning and neuroscience, and the ambitious Brain Initiative. This talk, part of the BMM Summer Course 2018, offers a comprehensive overview of the deep learning revolution and its far-reaching implications for artificial intelligence and our understanding of the human brain. Read more

The Deep Learning Revolution

MITCBMM
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