Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors.

Neuromorphic computing, inspired by the brain, integrates memory and processing to drastically reduce power consumption compared to traditional CPUs and GPUs, making AI at the network edge more ...

US researchers solve partial differential equations with neuromorphic hardware, taking us closer to world's first ...

For how powerful today’s “smart” devices are, they’re not that good at working smarter rather than working harder. With AI constantly connected to the cloud and the chip constantly processing tasks ...

Brain-inspired computing promises cheaper, faster, more energy efficient processing, according to experts at a Beijing conference, who discussed everything from reverse engineering insect brains to ...

New research shows that advances in technology could help make future supercomputers far more energy efficient. Neuromorphic computers are modeled after the structure of the human brain, and researche ...

The NeuRRAM chip is not only twice as energy efficient as state-of-the-art, it's also versatile and delivers results that are just as accurate as conventional digital chips. Neuromorphic computing—a ...

Large scale datasets and information processing requirements, within complex environments, are continuously reaching unprecedented levels of sophistication, especially in the advent of artificial ...

Tested against a dataset of handwritten images from the Modified National Standards and Technology database, the interface-type memristors realized a high image recognition accuracy of 94.72%. (Los ...

A review paper by scientists at Beijing Institute of Graphic Communication presented  a thorough review of the existing ...