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 ...

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 ...

Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

Scientists have taken a major step toward mimicking nature’s tiniest gateways by creating ultra-small pores that rival the dimensions of biological ion channels—just a few atoms wide. The breakthrough ...

Our latest and most advanced technologies — from AI to Industrial IoT, advanced robotics, and self-driving cars — share serious problems: massive energy consumption, limited on-edge capabilities, ...

Efforts to build brain-inspired computer hardware have been underway for decades, but the field has yet to have its breakout moment. Now, leading researchers say the time is ripe to start building the ...

Scientists demonstrate neuromorphic computing utilizing perovskite microcavity exciton polaritons operating at room temperature. (Nanowerk News) Neuromorphic computing, inspired by the human brain, is ...

It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive. That ...

A computing approach that requires up to 8,000 times less energy than conventional methods is emerging as a potential answer to one of technology’s most significant challenges: the unsustainable ...

What are spiking neural networks (SNNs)? Why the Akida Pico neural processing unit (NPU) can use so little power to handle machine-learning models. Why neuromorphic computing is important to ...