Researchers at the USC Viterbi School of Engineering and School of Advanced Computing have developed artificial neurons that ...

Could computers ever learn more like humans do, without relying on artificial intelligence (AI) systems that must undergo ...

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, ...

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 ...

Researchers at the USC Viterbi School of Engineering and the School of Advanced Computing have built artificial neurons that ...

(Nanowerk News) A novel device consisting of metal, dielectric, and metal layers remembers the history of electrical signals sent through it. This device, called a memristor, could serve as the basis ...

By borrowing ideas from the brain, UT Dallas researchers have created hardware that learns on its own with minimal energy use ...

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 new technical paper titled “An Ultra-Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective Vertical Channels for Neuromorphic Computing” was published by researchers at ...

The next competitive edge won’t come from brute force. It will come from systems that think more like markets themselves ...