Explore the limitations and new frontiers of deep learning in this lecture from MIT's Introduction to Deep Learning course. Delve into the history of AI hype, rethinking generalization, and the capacity of deep neural networks as function approximators. Examine adversarial attacks on neural networks and their limitations. Discover the importance of uncertainty in deep learning and learn about Bayesian deep learning techniques for uncertainty estimation. Investigate model uncertainty applications and the concept of learning to learn. Gain insights into the power of neural networks and emerging ideas in the field of deep learning.