Semiconductor Engineering

Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics

Brain-inspired Spiking Neural Networks (SNN) and the parallel hardware necessary to exploit their full potential have promising features for robotic application. “Animal brains still outperform even ...

From ‘Optical Synapses’ to a ‘Photonic Brain’ — Integrated Photonic Neural Networks Toward Low-Power General-Purpose

SHANNON, CLARE, IRELAND, February 5, 2026 /EINPresswire.com/ -- A new publication from Opto-Electronic Technology; DOI ...
Semiconductor Engineering

Optimizing Event-Based Neural Network Processing For A Neuromorphic Architecture

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...
TMCnet

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") ...
Electronic Design

Neuromorphic NPU Sips Power to Handle Edge Machine-Learning Models

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 ...
Popular Science

Engineers finally peeked inside a deep neural network

Breakthroughs, discoveries, and DIY tips sent six days a week. Terms of Service and Privacy Policy. Say you have a cutting-edge gadget that can crack any safe in the ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
VentureBeat

The debate over neural network complexity: Does bigger mean better?

Artificial intelligence (AI) has made tremendous progress since its inception, and neural networks are usually part of that advancement. Neural networks that apply weights to variables in AI models ...