The editorial discusses the advancements in neuromorphic computing applications, focusing on the challenges faced by Artificial Neural Networks (ANNs) in terms of computational demands and energy consumption. N
mdpi.com/si/163209 Electrical characteristics for memristors; Nanomaterials and nanocomposites for memristors; Two-dimensional structures for memristors; Crossbar array of memristors; Neuromorphic-behaving memristors; Integration and neuromorphic computing system based on memristors; Low-power consumption of memr...
Scott Bair is a Senior Technical Creative Director for Intel Labs, chartered with growing awareness for Intel’s leading-edge research activities, like AI, Neuromorphic Computing and Quantum Computing. Scott is responsible for driving marketing strategy, messaging, and asset cr...
Farshchi claims that neuromorphic and analogue computing will make a comeback in the fields of AI and robotics. Neural networks and deep learning algorithms that researchers are attempting to implement in robots are more suitable to analogue designs. Such analogue systems will make robots faster, sma...
At present, electronic computing is still the most important computing power support for the implementation of artificial intelligence algorithms, especially deep ANN model. Although the specific hardware architectures are different, in a word, they all adopt the von Neumann type computing principle to ...
During the pandemic, many industry participants expected next-gen tech like game streaming and extended reality (XR) to overtake mobile, but lackluster consumer adoption has shown that we’re not quite ready to live in the metaverse. It’s actually gaming’s most traditional platforms — PC and...
(integration schemes, novel circuit design schemes and novel memory architectures that enhance memory performance) Use and reliability of memristive devices for artificial intelligence and design architectures for in-memory and neuromorphic computing (neural networks) Memristor devices physics and theoretical ...
Tuesday, April 21, 2015 In order for brain-inspired computing to become a reality, the underlying hardware must become sufficiently powerful to do in-silicon what the brain does naturally. One of the important advances in this field was the 2014 debut of the first neuromorphic chip, “True No...
The capacity of neuromorphic computing to handle large amounts of data with low power consumption has garnered a lot of interest during the last few decades. For neuromorphic applications, 2D layered semiconductor materials have shown a pivotal role due to their distinctive propertie...
Neuromorphic devices are the key hardware units of neuromorphic chips to implement the intelligent computing. In recent years, the development of optogenetics and photosensitive materials has provided new avenues for the research of neuromorphic devices. The emerging optoelectronic neuromorphic devices have ...