Brain-inspired chips can slash AI energy use by as much as 100-fold, but the road to mainstream deployment is far from ...

In this cross-journal collection, we aim to bring together cutting-edge research of neuromorphic architecture and hardware, computing algorithms and theories, and the related innovative applications.

Neuromorphic computing -- a field that applies principles of neuroscience to computing systems to mimic the brain's function and structure -- needs to scale up if it is to effectively compete with ...

Theoretically, simple computing devices with self-compliant neuromorphic processing chips could provide real-time automation and data processing for a scalable blockchain network on Mars.

What Is Neuromorphic Computing? Neuromorphic computing is designed to mimic the human brain, operating in a manner that allows the technology to solve problems in ways our brains would.

Yanbo Xie, a nanofluidics expert at Northwestern Polytechnical University in China, points out that the memristor is a critical component for a neuromorphic computer chip and plays a similar role to a ...

To-date, neuromorphic platforms -- an approach to computing inspired by the human brain -- have worked only for low-accuracy operations, such as inferencing in artificial neural networks.

This new class of device could play a major role in revolutionizing high-bandwidth neuromorphic computing, machine learning hardware, and artificial intelligence in the optical domain.

In fact, there’s a whole field dedicated to the concept: neuromorphic computing. But as the line between man and machine continues to blur, could the same be said in reverse?

RIT computer engineering faculty member contributes system testing expertise to USC’s Center of Neuromorphic Computing under Extreme Environments.

(See diagram.) “It’s a way of letting the physics do the computing,” says Matthew Marinella, a computer engineer at Arizona State University in Tempe who researches neuromorphic computing.