  Koopman operator based models emerged as the leading methodology for machine
learning of dynamical systems. But their scope is much larger. In fact they
present a new take on modeling of physical systems, and even language. In this
article I present some of the underlying mathematical structures, applications,
connections to other methodologies such as transformer architectures
