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

The human brain, with its remarkable general intelligence and exceptional efficiency in power consumption, serves as a constant inspiration and aspiration for the field of artificial intelligence.

Computers have come so far in terms of their power and potential, rivaling and even eclipsing human brains in their ability to store and crunch data, make predictions and communicate. But there is one ...

(Nanowerk Spotlight) The human brain's remarkable efficiency and cognitive abilities have long inspired researchers to create computing systems that can rival its performance. Yet, despite significant ...

Cerebellar granule cell and its response to a pair of 50-Hz stimuli. (A) Biological neuron. (B) Computational model used for simulation. (C) Simulated neuron. (D) Electronic neuron. The biological ...

A team of researchers from Texas A&M University, Sandia National Lab - Livermore, and Stanford University are taking lessons from the brain to design materials for more efficient computing. The new ...

Intel Corp. has achieved another key milestone on the road to developing neuromorphic processors modeled on the human brain that are designed to provide a more energy-efficient alternative to existing ...

An open source code library for brain-inspired deep learning, called 'snnTorch,' has surpassed 100,000 downloads and is used in a wide variety of projects. A new paper details the code and offers a ...

Physicists are developing an innovative approach that will significantly improve the energy efficiency of computers. They take their inspiration from the human brain. (Nanowerk News) The rapid ...

Artificial intelligence (AI) machine learning algorithms consist of neural networks that are inspired by the biological brain. However, today’s standard computing hardware architecture is not, hence ...

Editor’s note: “Brain-Inspired AI Is Coming Faster Than You Think” was previously published in July 2025 with the title, “Beyond GPUs: Why Neuromorphic Chips Could Power the Future of AI.” It has ...