MLG 009 Deep Learning

This podcast episode delves into the world of deep learning and neural networks, highlighting their significance in the field of artificial intelligence. It explores the hierarchical structure of machine learning, with deep learning as a subset of supervised learning. The episode discusses the unique characteristics of deep learning, including its ability to subsume other AI spaces and automate complex tasks. It traces the historical origins and foundational concepts of artificial neural networks (ANNs), and provides an in-depth overview of multi-layer perceptron (MLP) architectures. The episode also explains how neural networks are used for feature learning and hierarchical representation of data, with examples such as face recognition. Overall, it emphasizes the superpowers of neural networks in finding optimal combinations of features and breaking down data into multiple levels of abstraction, bringing us closer to the realm of true artificial intelligence.