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

Inspired by human brain, neuromorphic computing technologies have made important breakthroughs in recent years as alternatives to overcome the power and latency shortfalls of traditional digital ...

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, ...

AI, machine learning, and ChatGPT may be relatively new buzzwords in the public domain, but developing a computer that functions like the human brain and nervous system -- both hardware and software ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now While much of the tech world remains ...

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 ...

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 ...

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 ...

A look at the latest generation of neural networks called spike neural networks (SNNs), their operation, and the hardware necessary to run those algorithms. The variety of advantages SNNs have over ...

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 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 ...