The Deep Learning Revolution

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.

Introduction
The Story Begins
Computer Vision
The Brain
Frank Rosenblatt
The Perceptron
Minsky Papert
David Rummelheart
Jim DeCarlo
David Hubel
Toby Del Brooke
The Magic Sauce
Convolutional Network
Examples
Google Translate
Unsupervised Learning
The basal ganglia
The actor critic model
The basal ganglia model
The reward problem
The problem
The model
The glider
How it works
Social robots
Machine learning
Neuroscience
Brain Initiative