Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors.

Research into alternative computer architectures is getting a new boost thanks to work by Sandia National Laboratories.

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 ...

Analysts project the global neuromorphic computing market to skyrocket – from roughly $7.5 billion in 2024 to nearly $59 billion by 2033. This explosive forecast set the stage for an unexpected ...

A December 10–12 working group met to bring together researchers from two fields — neuromorphic computing and stochastic ...

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 ...

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 ...

An integrated spiking artificial neuron, with rich neuron functionality, single-transistor footprints, and low energy consumption for neuromorphic computing systems, can be created by stacking one ...

The UK will establish a new center to develop brain-inspired, neuromorphic computing technologies. The UK Multidisciplinary Center for Neuromorphic Computing is led by Aston University and will ...

As artificial intelligence platforms like OpenAI’s ChatGPT and Microsoft’s Copilot go mainstream, power bills from their usage are exploding. In response, researchers are racing to build hardware that ...