Protege raises $30M to grow governed marketplace for AI training data

Through 2025, Protege expanded its data partner network to hundreds of organizations to provide aggregated access to new data ...
Science Daily

AI may not need massive training data after all

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
AZoCleantech on MSN

New Framework for Predicting TAIs in Hydrogen Combustion

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
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 ...
TechCrunch

Microsoft is exploring a way to credit contributors to AI training data

Microsoft is launching a research project to estimate the influence of specific training examples on the text, images, and other types of media that generative AI models create. That’s per a job ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...