A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2025.240152, discusses how multi-photon bionic skin ...

AI-generated legal and regulatory content should be backed by structured legal databases to avoid misinformation and legal ...

Art and science can be aligned in different ways. We describe one use of art as a tool: using ambiguity to evoke curiosity.

Industrial maintenance has evolved through three distinct phases. The first phase was purely reactive – fix it when it breaks ...

Highlights,Definition & Functionality,–,Neural networks, or neural nets, are computational models inspired by the human brain ...

Researchers outline a bold strategy to scale neuromorphic computing, aiming to match human brain functionality with minimal ...

Methods: To address these challenges, we propose PoseGCN, a Graph Convolutional Network (GCN)-based model that integrates ... we introduce an adaptive learning strategy that incorporates ...

A cornerstone of neural network computation is the concept of weights, which represent the “strength” or “importance” of each neuron’s connection in the network. NPUs integrate these weights directly ...

Learn More A new neural-network architecture developed by researchers at Google might solve one of the great challenges for large language models (LLMs): extending their memory at inference time ...

These hairs convert vibrations from sound waves into neural signals that your auditory nerve carries to your brain. Exposure to sounds louder than 85 decibels can damage these hairs. Eighty-five ...

Graph neural networks (GNNs), as a rising star in machine learning, are widely used in relational data models and have achieved outstanding performance in graph tasks. GNN continuously takes ...