Ubiquitous on-device artificial intelligence (AI) is the next step in transforming the myriad of mobile computing devices in our everyday lives into a new class of truly “smart” devices capable of constantly observing, learning, and adapting to their environment. Through advances in AI technology, these intelligent devices will provide proactive assistance and enable new applications, as well as make our lives safer and the world around us more energy efficient.
Present day AI features, such as voice-based user interfaces on smartphones, often rely on a connection to the cloud. In contrast, on-device AI promises to increase the energy efficiency, privacy, responsiveness, and autonomy of embedded and edge devices by severing their tether to the cloud. The 3rd on-device intelligence workshop aims to advance the state-of-the-art by bringing together researchers and practitioners to discuss the key problems, disseminate new research results, and provide practical tutorial material. Due to the multidisciplinary nature of on-device AI, collaboration across the traditional computing stack is crucial.
We aim to bring together experts to discuss solutions to the following key challenges:
How do we design, train, and optimize ML models tailored to fit a plethora of edge devices with constrained compute, storage, and energy budgets?
How can we ensure privacy and security in ways that are interpretable to users?
How should mobile computing hardware evolve to support the increasing prevalence of on-device AI workloads?
How can industry and academia collaboratively develop standards and benchmarks to stimulate the development of an on-device AI research ecosystem?
Organizing Committee
Harvard
Qualcomm
Meta
Stanford - Userful Sensors
Program Committee
Igor Fedorov - Meta
Shawn Hymel - Edge Impulse
Shvetank Prakash - Harvard University
Zhihe Zhao - Chinese University of Hong Kong
Chuteng Zhou - ARM