Explore the challenges deep learning poses to statistical learning theory in this IEEE FOCS 2020 tutorial presented by Peter Bartlett. Delve into the complexities of understanding deep learning algorithms and their implications for traditional statistical learning approaches. Gain insights into the current limitations of theoretical frameworks in explaining the success of deep learning models and the potential directions for future research in this field. Over the course of 1 hour and 28 minutes, examine the intersection of deep learning and statistical theory, uncovering the key questions and obstacles that researchers face in developing a comprehensive understanding of these powerful machine learning techniques.