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Deep Learning Revolution: Turing Award Lecture by Geoffrey Hinton and Yann LeCun

Association for Computing Machinery (ACM) via YouTube

Overview

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Watch a captivating Turing Lecture delivered by Geoffrey Hinton and Yann LeCun, two of the three recipients of the 2018 ACM A.M. Turing Award for their groundbreaking work in deep neural networks. Explore the evolution of artificial intelligence, from symbolic and biological paradigms to the revolutionary advancements in neural networks. Delve into various learning algorithms, including supervised learning and backpropagation, and discover how these techniques have transformed fields such as acoustic modeling, object recognition, and machine translation. Gain insights into the future of computer vision, handwriting recognition, and medical image analysis. Learn about cutting-edge applications in reinforcement learning, including training robots and self-driving cars. This comprehensive lecture also touches on developmental psychology concepts and concludes with thought-provoking discussions on the broader implications of AI advancements.

Syllabus

Intro
ACM President
Two paradigms for AI
Symbolic and biological paradigms
Programming
Neural nets
Random weights
Rosenblatt
Winter
How Neural Networks Work
Types of Learning Algorithms
Supervised Learning
Back Propagation
Backpropagation
Silly Theories
Conference Rejection
Technical Advances
Acoustic Modeling
Object Recognition
Machine Translation
Future of Computer Vision
Future of Neural Networks
Handwriting Recognition
Perceptual World
Hierarchy
Bill Recognition
Face Detection
Pedestrian Detection
Segmentation
Panopticon Network
Medical Image Analysis
Breast Cancer Detection
MRI Data Collection
Translation with Neural Networks
Image Segmentation
Reinforcement Learning
Training a Robot
Training a Car
Developmental Psychology
Object permanence
Wheres the salvation

Taught by

Association for Computing Machinery (ACM)

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