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VFF-Net algorithm provides promising alternative to backpropagation for AI training

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...

WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram ...
Science Daily

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...

Algorithm precisely quantifies flow of information in complex networks

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically ...
Frontiers

Spiking Neural Networks at Scale: Learning Algorithms, Architectures, and Real-World Applications

Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
Semiconductor Engineering

Spiking Neural Networks: Hardware & Algorithm Developments

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

AI tool beats humans at detecting parasites in stool samples

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in ...
ascopubs.org

Analytical Validation of a Deep Neural Network Algorithm for the Detection of Ovarian Cancer

Early detection of ovarian cancer, the deadliest gynecologic cancer, is crucial for reducing mortality. Current noninvasive risk assessment measures include protein biomarkers in combination with ...
Quanta Magazine

Artificial Neural Nets Finally Yield Clues to How Brains Learn

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...