Researchers in the Murmann Mixed Signal Group have developed a pipelined chip architecture with inverted residual and linear bottlenecks-based networks for energy efficient Machine Learning inference on edge devices.
Stanford researchers have developed a method called KleinPAT, for creating sound models in seconds, making it cost effective to simulate sounds for many different objects in a virtual environment.