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 ...
Queen's University

Neural Networks: When good enough is better than best

A Queen’s research team has developed a new way to train AI systems so they focus on the bigger picture instead of specific, optimized data.
Science Daily

A new neural network makes decisions like a human would

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...
EurekAlert!

RUDN University mathematicians reduced neural network size six times without post-training

image: A team of mathematicians from RUDN University found a way to reduce the size of a trained neural network six times without spending additional resources on re-training it. The approach is based ...
The Next Web

Deep learning models DON’T need to be black boxes — here’s how

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...
VentureBeat

The debate over neural network complexity: Does bigger mean better?

Artificial intelligence (AI) has made tremendous progress since its inception, and neural networks are usually part of that advancement. Neural networks that apply weights to variables in AI models ...