Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Analogue in-memory computing (AIMC) with resistive memory devices could reduce the
latency and energy consumption of deep neural network inference tasks by directly …

Many in-memory computing frameworks demand electronic devices with specific switching
characteristics to achieve the desired level of computational complexity. Existing memristive …

Neuromorphic perception systems inspired by biology have tremendous potential in
efficiently processing multi-sensory signals from the physical world, but a highly efficient …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Artificial intelligence (AI) is accelerating the development of unconventional computing
paradigms inspired by the abilities and energy efficiency of the brain. The human brain …

The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …

The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …