Visual Studio Magazine

Neural Network Dropout Training

A major challenge when working with a neural network is training the network in such a way that the resulting model doesn't over-fit the training data -- that is, generate weights and bias values that ...
Visual Studio Magazine

Neural Network Training Using Back-Propagation

Neural networks can be used to classify data and make predictions. For example, you might want to predict the political party affiliation (Democrat, Republican, Independent) of a person based on ...
Ars Technica

Training a neural network in phase-change memory beats GPUs

Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots of ...
Yahoo Finance

MicroAlgo Inc. Adopts Quantum Phase Estimation (QPE) Method to Enhance Quantum Neural Network Training

SHENZHEN, China, June 6, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), explored the possibilities of quantum technology in various application scenarios, ...
Semiconductor Engineering

How Neural Super Sampling Works: Architecture, Training, And Inference

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
Ars Technica

Light-based neural network does simple speech recognition

While there are lots of things that artificial intelligence can't do yet—science being one of them—neural networks are proving themselves increasingly adept at a huge variety of pattern recognition ...