As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …

Neuromorphic computing holds promise for building next‐generation intelligent systems in a
more energy‐efficient way than the conventional von Neumann computing architecture …

Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …

Recent progress in deep learning extends the capability of artificial intelligence to various
practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis …

Efficient information processing in the human brain is achieved by dynamics of neurons and
synapses, motivating effective implementation of artificial spiking neural networks. Here, the …

HfO 2-based resistive switching memory (RRAM) combines several outstanding properties,
such as high scalability, fast switching speed, low power, compatibility with complementary …

Neural network technologies have taken center stage owing to their powerful computing
capability for supporting deep learning in artificial intelligence. However, conventional …

Nonvolatile memory (NVM)‐based neuromorphic computing has been attracting
considerable attention from academia and the industry. Although it is not completely …

While artificial intelligence, capable of readily addressing cognitive tasks, has transformed
technologies and daily lives, there remains a huge gap with biological systems in terms of …

Although the structure and function of the human brain are still far from being fully
understood, brain‐inspired computing architectures mainly consisting of artificial neurons …