Neuromorphic computer solves differential equations ...

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 ...

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

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.

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 ...

When you buy through links on our articles, Future and its syndication partners may earn a commission. Although neuromorphic computing was first proposed by scientist Carver Mead in the late 1980s, it ...

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.

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 ...

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 ...

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, ...

Researchers Brad Theilman, center, and Felix Wang, behind, unpack a neuromorphic computing core at Sandia National Laboratories. While the hardware might look similar to a regular computer, the ...