For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Local AI applications can greatly simplify everyday tasks, but they require an NPU to run smoothly. This article explains why ...

The latest generative AI models such as OpenAI's ChatGPT-4 and Google's Gemini 2.5 require not only high memory bandwidth but also large memory capacity. This is why generative AI cloud operating ...

Discover how neuromorphic computing mimics the brain to deliver ultra-efficient, adaptive AI for edge devices, robotics, ...

A Comparative Study of AI-Powered Chatbot for Health Care. Journal of Computer and Communications, 13, 48-66. doi: 10.4236/jcc.2025.137003 . The need for this research arises from the increasing ...

To solve the time-variant Sylvester equation, in 2013, Li et al. proposed the zeroing neural network with sign-bi-power function (ZNN-SBPF) model via constructing a nonlinear activation function. In ...

Solving optimal power flow is essential to ensure stable and cost effective power system operations. However, frequently solving optimal power flow under numerous scenarios using conventional solvers ...