Abstract: The development of quantum technologies has now become a global race owing to its great promise to revolutionize our ability for information processing. On the other hand, the influence of quantum information science has concurrently penetrated into research areas of fundamental physics as well. In this talk, I will thus focus on a topic at the interface between Physics and Quantum Information. Specifically, I will present our approach to the study of quantum chaos from a quantum information point-of-view, and explore the implications of chaotic dynamics on the performance of quantum machine learning. Notably, quantum chaos is of fundamental interest and is crucial for answering several key questions in condensed matter physics, e.g., thermalization in isolated many-body systems. Similarly, quantum machine learning offers an appealing synergistic approach for combining and utilizing the potentials of machine learning and quantum computers. The interplay between these fields demonstrates how technical toolkits developed in Quantum Information can be applied to study problems in Physics, and vice versa insight from physics can strengthen our understanding of the limitations of quantum information processing. I will conclude this talk with a discussion about several relevant ongoing and future directions, including quantum networking and quantum correlations in quantum material.