  This article presents a vision where \textit{real-time} digital twins of the
physical wireless environments are continuously updated using multi-modal
sensing data from the distributed infrastructure and user devices, and are used
to make communication and sensing decisions. This vision is mainly enabled by
the advances in precise 3D maps, multi-modal sensing, ray-tracing computations,
and machine/deep learning. This article details this vision, explains the
different approaches for constructing and utilizing these real-time digital
twins, discusses the applications and open problems, and presents a research
platform that can be used to investigate various digital twin research
directions.
