CS50's Fundamentals of AI - Lecture 3 - Sensing (live, unedited) | CS50

The podcast explores how artificial intelligence perceives the world through visual and auditory data, mirroring human senses. It begins with how computers process images as individual pixels with numerical values representing brightness. The discussion moves to handwriting recognition as an early AI application, solved using neural networks that classify digits. Deep learning, employing multi-layer networks, is introduced to handle large image datasets, using convolutional and pooling layers to extract complex features. The podcast further extends AI's sensory capabilities to processing color images and videos by applying similar strategies used for image analysis. It concludes by addressing training processes, overfitting dangers, data bias, and efficient training methods like transfer learning and hardware acceleration using GPUs.

Outlines

Part 1: Introduction, Visual Basics

Part 2: Convolutional Neural Networks

Part 3: Advanced Processing, Training

Part 4: Audio Perception

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CS50's Fundamentals of AI - Lecture 3 - Sensing (live, unedited)

CS50

Part 1: Introduction, Visual Basics

Introduction to AI Perception: Enabling Computers to See and Hear the World

Visual Data Processing: From Pixels to Deep Learning for Image Understanding

Multi-Layer Neural Networks: Identifying Complex Features in Handwritten Digits

Part 2: Convolutional Neural Networks

Image Analysis: Sliding Windows, Convolutions, and Edge Detection

Convolutional Layers: Enhancing Neural Networks for Image Processing

Pooling Layers: Reducing Data and Capturing Essential Image Features

Convolutional Neural Networks: Combining Convolution and Pooling for Image Analysis

Part 3: Advanced Processing, Training

Processing Color Images and Video with Convolutional Neural Networks

Training Neural Networks: Data Organization, Overfitting, and Bias

Hardware Acceleration and Transfer Learning for Efficient Neural Networks

Part 4: Audio Perception

AI Perception: Processing Sound with Fast Fourier Transforms and Spectrograms

CS50's Fundamentals of AI - Lecture 3 - Sensing (live, unedited)

CS50

Part 1: Introduction, Visual Basics

12:33Introduction to AI Perception: Enabling Computers to See and Hear the World

Introduction to AI Perception: Enabling Computers to See and Hear the World

15:16Visual Data Processing: From Pixels to Deep Learning for Image Understanding

Visual Data Processing: From Pixels to Deep Learning for Image Understanding

27:28Multi-Layer Neural Networks: Identifying Complex Features in Handwritten Digits

Multi-Layer Neural Networks: Identifying Complex Features in Handwritten Digits

Part 2: Convolutional Neural Networks

33:15Image Analysis: Sliding Windows, Convolutions, and Edge Detection

Image Analysis: Sliding Windows, Convolutions, and Edge Detection

47:54Convolutional Layers: Enhancing Neural Networks for Image Processing

Convolutional Layers: Enhancing Neural Networks for Image Processing

55:13Pooling Layers: Reducing Data and Capturing Essential Image Features

Pooling Layers: Reducing Data and Capturing Essential Image Features

1:15:44Convolutional Neural Networks: Combining Convolution and Pooling for Image Analysis

Convolutional Neural Networks: Combining Convolution and Pooling for Image Analysis

Part 3: Advanced Processing, Training

1:22:32Processing Color Images and Video with Convolutional Neural Networks

Processing Color Images and Video with Convolutional Neural Networks

1:27:57Training Neural Networks: Data Organization, Overfitting, and Bias

Training Neural Networks: Data Organization, Overfitting, and Bias

1:37:37Hardware Acceleration and Transfer Learning for Efficient Neural Networks

Hardware Acceleration and Transfer Learning for Efficient Neural Networks

Part 4: Audio Perception

1:44:22AI Perception: Processing Sound with Fast Fourier Transforms and Spectrograms

AI Perception: Processing Sound with Fast Fourier Transforms and Spectrograms