Tech Xplore on MSN

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
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 ...
EurekAlert!

Backpropagation training achieved in photonic neural network

Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the way ...
InfoQ

Google Uses AutoML to Discover More Efficient AI Training Algorithm

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
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 ...
Seeking Alpha

WiMi Developed a Quantum Computing-Based Feedforward Neural Network (QFNN) Algorithm

BEIJING, Apr. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, announced the development of a ...

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
pv magazine International

PV energy forecasting based on genetic algorithms, dynamic neural network

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...