The Evolution of Neural Networks

Take listeners through the history of neural networks, tracing their journey from the early perceptrons of the 1950s to the powerful deep learning networks of today. Discuss the major breakthroughs that led to the popularity of neural networks, such as backpropagation, convolutional networks for image processing, and recurrent networks for sequential data. Touch on significant milestones like ImageNet, AlphaGo, and BERT, explaining how each helped push the boundaries of what neural networks could achieve. End with a discussion on the future of neural networks, including research on reducing their computational costs and improving interpretability.