Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for ...

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

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

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

Cadence has now launched the ChipStack AI Super Agent, the world’s first agentic workflow for automating chip design and verification. It provides up to 10X productivity improvements for coding ...

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

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Abstract: Cooperative path planning for multiple unmanned aerial vehicles (UAVs) is a challenging problem in the field of multi-agent reinforcement learning, characterized by high-dimensional state ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...