Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...

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 ...

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

Tiny molecules that can think, remember, and learn may be the missing link between electronics and the brain. For more than ...

Neuromorphic computing aims to replicate the functional architecture of the human brain by integrating electronic components that mimic synaptic and neuronal behaviours. Central to this endeavour are ...

Scientists have developed molecular devices that can switch roles, behaving as memory, logic, or learning elements within the ...

This review describes various types of low-power memristors, demonstrating their potential for a wide range of applications. This review summarizes low-power memristors for multi-level storage, ...

As computing systems push beyond silicon limits, researchers seek materials that can do more than simply store and process ...

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 ...

The "The Global Market for Low Power/High Efficiency AI Semiconductors 2026-2036" has been added to ResearchAndMarkets.com's offering. The market for low power/high efficiency AI semiconductors stands ...

Engineers are starting to build hardware that does not just run artificial intelligence, it behaves like a primitive form of ...