AI/ML+Physics: Recap and Summary
Steven L. Brunton · 2024
This video provides a brief recap of this introductory series on Physics Informed Machine Learning. We revisit the five stages of machine learning, and how physics may be incorporated into these stages. We also discuss architectures, symmetries, the digital twin, applications in engineering, and the importance of dynamical systems and controls benchmarks. SLB acknowledges support from the National Science Foundation AI Institute in Dynamic Systems and from The Boeing Company.