Scientists Use AI To Supercharge Ultrafast Laser Simulations by More Than 250x

Researchers have developed a deep-learning-based surrogate model that dramatically speeds up simulations of nonlinear optical ...
Hosted on MSN

AI Researchers Are Shifting From Expanding Capabilities to Understanding Core Limits

In 2026, AI research is moving from simply scaling models toward probing their fundamental limits, with benchmarks like MLRegTest revealing gaps in logical generalization and causal reasoning.
Hosted on MSN

MLRegTest Reveals How Neural Networks Struggle With Rule Comprehension

A study using the MLRegTest benchmark tested 1,800 artificial languages to evaluate whether neural networks can learn underlying rules rather than just patterns. The results show that while models ...
Ohio University

The first to build what’s next: How the initial grads of OHIO’s Artificial Intelligence degree are shaping the future of AI

As members of the inaugural graduating class in Ohio University’s artificial intelligence program, three students share what ...
mwnation

MEC told to engage multiple networks

Information and Communications Technology Association of Malawi (Ictam) has advised Malawi Electoral Commission (MEC) to engage multiple network providers to ensure smooth transmission of results in ...
IEEE

PicoSleepNet: An Ultra Lightweight Sleep Stage Classification by Spike Neural Network Using Single-Channel EEG Signal

Abstract: This study introduces PicoSleepNet, an ultra-lightweight sleep stage classification method that utilizes a spiking neural network (SNN) with single-channel electroencephalogram (EEG) signals ...
IEEE

Osteoarthritis Classification Using Hybrid Quantum Convolutional Neural Network

Abstract: This work explores the integration of quantum computing within a classical Convolutional Neural Network (CNN) framework, leveraging a VGG16 model enhanced with a quantum Convolutional Neural ...
GitHub

Image Classification with Neural Networks in Python

This project demonstrates image classification using Convolutional Neural Networks (CNNs) in Python with TensorFlow and Keras, trained and tested on the CIFAR-10 dataset. The CIFAR-10 dataset consists ...