Future computing systems will capitalize on our increased understanding of the brain through the use of similar architectures and computational principles. During this workshop, we bring together recent developments in this rapidly developing field of neuromorphic computing systems, and also discuss challenges ahead.
In the neuromorphic systems field, emulation of neural systems is done using the implementation of neural elements in silicon. Typically, parallel analog and/or digital very large-scale integration (VLSI) circuits are used; and the stochastic behavior of event driven communication between simple devices resembling neurons embedded in massively parallel and recursive network architectures is exploited. Such hardware systems, whose design is inspired by the brain, have the potential to create a paradigm shift in terms of energy efficiency, fault tolerance, adaptability as well as information processing capabilities.
For example, neuromorphic systems may in the future be able to mimic the capabilities of adaptive pattern recognition and motor control capabilities found in the vertebrate brain. Also, already today neuromorphic systems allow emulation and simulations of computational neural models in real time or faster.
This workshop, held in 2015 in Cairns, Australia, covers recent developments in this rapidly developing field of neuromorphic computing systems, as well as challenges ahead.