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Thermodynamic computer mimics AI image generation using a fraction of the energy

Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for generating images from pure noise by using the physics of heat and motion ...

'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.
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.
IEEE

Gradient Harmony Optimization-Driven Hybrid Physics-Informed Neural Network for Solving Neutron Diffusion Problems

Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving neutron diffusion equations, yet their accuracy and stability are often hindered by limited spatial ...
IEEE

Interdisciplinary Methodology for Resource Allocation Problems Using Artificial Neural Networks and Software Robots

Abstract: This study presents an interdisciplinary methodology for the Resource Allocation Problem (RAP) in a textile manufacturing environment, aligned with the principles of Industry 5.0, which ...

This Cadence AI Super Agent Is World’s First To Automate Chip Design

The semiconductor industry has been applying AI to accelerate chip design for over three years, achieving 10X productivity gains and focusing primarily on tasks that now seem relatively easy, such as ...

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 ...