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Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
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 ...
Quanta Magazine

Researchers Build AI That Builds AI

Artificial intelligence is largely a numbers game. When deep neural networks, a form of AI that learns to discern patterns in data, began surpassing traditional algorithms 10 years ago, it was because ...
The Conversation

What is a neural network? A computer scientist explains

Dr. Tam Nguyen receives funding from National Science Foundation. He works for University of Dayton. There are many applications of neural networks. One common example is your smartphone camera’s ...
JSTOR Daily

Impact of Artificial Neural Networks Training Algorithms on Accurate Prediction of Property Values

The Journal of Real Estate Research, Vol. 40, No. 3 (July – September 2018), pp. 375-418 (44 pages) This study extended the use of artificial neural networks (ANNs) training algorithms in mass ...
Quanta Magazine

How Do Machines ‘Grok’ Data?

For all their brilliance, artificial neural networks remain as inscrutable as ever. As these networks get bigger, their abilities explode, but deciphering their inner workings has always been near ...