AI captures particle accelerator behavior to optimize machine performance

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 ...

RRAM hasn't delivered yet, but stacked memory is being pitched to run neural networks in place

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

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

Cadence has now launched the ChipStack AI Super Agent, the world’s first agentic workflow for automating chip design and ...
2UrbanGirls on MSN

Making AI more accessible: Miria Feng champions AI technology for everyone

Artificial intelligence is advancing rapidly, changing how people work, communicate, and solve problems across almost ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification BEIJING, Feb.06, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
IEEE

Graph Neural Network - Variable Neighborhood Search for Solving Symmetric Traveling ...

Abstract: The goal in optimization is to discover the nearest optimum that satisfies particular constraints. The traveling salesman problem (TSP) is a well-known challenge in combinatorial ...
IEEE

Causality-Informed Neural Networks for Regularized Learning in Regression Problems

Abstract: Neural networks that overlook the underlying causal relationships among observed variables pose significant risks in high-stakes decision-making contexts due to concerns about the robustness ...