EurekAlert!

Compression using automatically differentiable tensor networks: Fewer parameters with equal or better performance

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
TechSpot

AMD's neural texture compression could reduce storage and VRAM requirements

Something to look forward to: High-resolution textures are a primary factor behind the growing install sizes and VRAM usage in modern blockbuster games. Nvidia proposed a neural-network-based method ...
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 ...
MIT Technology Review

A new way to build neural networks could make AI more understandable

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.
Geeky Gadgets

What is an AI neural network and how do they work?

AI neural networks, inspired by the human brain are a foundational technology in the field of artificial intelligence. They are designed to recognize patterns and make decisions with a level of ...