The growing energy use of AI has gotten a lot of people working on ways to make it less power hungry. One option is to develop processors that are a better match to the sort of computational needs of ...

A new technical paper titled “A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware” was published by ...

An artificial neural network (ANN) that is said to be more like the human neural system, on which today's AI systems are loosely modeled. Rather than each neuron sending out a continuous value, the ...

LAGUNA HILLS, Calif.--(BUSINESS WIRE)-- BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic ...

What’s the difference between analog and digital spiking neural networks (SNNs)? Why analog and digital SNNs are complementary. Details about Innatera’s Pulsar SSN-based microcontroller. Spiking ...

A new publication from Opto-Electronic Advances, 10.29026/oea.2023.230140 discusses photonic integrated neuro-synaptic core for convolutional spiking neural network. Brain science and brain-like ...

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 ...

Assistant Professor of Electrical and Computer Engineering Jason Eshraghian. Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial ...

Anyone exploring technological advances in artificial intelligence (AI) will inevitably encounter spiking neural networks (SNNs) — the next step toward energy‑efficient real‑time AI. The difference ...

(Nanowerk Spotlight) Effectively mimicking the unmatched visual capacities of the human brain while operating within stringent energy constraints poses a formidable challenge for artificial ...