Yiran Chen develops brain-inspired semiconductor hardware to enable faster, greener AI at the edge.

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 ...

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

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

Adding zinc ions to lithium niobate crystals cuts the energy needed for polarization switching by 69%, enabling visible-light programming of memristors for brain-inspired computing.

A new publication from Opto-Electronic Technology; DOI   10.29026/oet.2025.250011, discusses integrated photonic synapses, neurons, memristors, and neural networks for photonic neuromorphic computing.

A team of researchers at Queen's University has developed a powerful new kind of computing machine that uses light to take on ...

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...

Large scale datasets and information processing requirements, within complex environments, are continuously reaching unprecedented levels of sophistication, especially in the advent of artificial ...

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 ...

BANGALORE, India, Jan. 28, 2026 /PRNewswire/ -- According to Valuates Reports, In 2024, the global market size of Neuromorphic AI Semiconductor was estimated to be worth USD 30.5 Million and is ...