Session

DescriptiontinyML encapsulates and nurtures the fast-growing branch of ultra-low power machine learning technologies and approaches dealing with machine intelligence at the very edge of the cloud. These integrated "tiny" machine learning applications require "full-stack" solutions including machine learning architectures, techniques, tools, and approaches capable of performing on-device analytics. A variety of sensing modalities are used with extreme energy efficiency, to enable machine intelligence right at the boundary of the physical and digital worlds. We see a new world with trillions of distributed intelligent devices enabled by energy efficient machine learning technologies that sense, analyze, and autonomously act together to create a healthier and more sustainable environment for all! This special session provides a birds eye view of the current state of the art through an overview talk and two industrial perspectives from leaders of this exciting paradigm, identifying the challenges and opportunities surrounding this rapidly growing area.