Symposium EL08—Neuromorphic Materials and Devices for Bio-inspired Computing and Artificial Intelligence
With the advent of effective artificial neural network implementations, impressive progress has been made in recent years in realizing human-level cognitive capabilities. However, solving cognitive problems on today’s digital computers is already considered as a challenging task which requires extended computation time and datacenter-scale computational resources. Therefore, there has been increasing interest in the field of neuromorphic computing to tackle such problems on native hardware and bio-inspired architecture, with an expectation of achieving a brain-like efficiency and large performance gain as well as artificial intelligence. This requires a systematic approach combining the expertise of material scientists to understand how learning happens in artificial neural networks and biological systems, and identify the key components which can be cast into material and device solutions. The goal of this symposium is to provide a forum to unite researchers who are engaged in the study of material research across neuromorphic computing technologies. This symposium will cover the scientific and technological exploration and advances of the development, characterization and system-level integration of new materials and devices for a variety of neuromorphic applications. Invited talks will attempt to bridge the gap between interdisciplinary topics such as material science, device engineering, computer science, algorithms, systems and architecture-level considerations in order to accelerate the discussion and development of neuromorphic materials toward practical applications.