AI in engineering: Engineering teams are adopting AI tools to speed up design iteration, detect system issues earlier, and scale internal expertise without replacing core CAD and simulation systems.

New integrations between Python and MATLAB’s Simulink platform are enabling engineers to coexecute Python models, automate VLSI workflows, and bridge AI-driven design with traditional simulation.

We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has introduced Nested Learning, a ...

Abstract: WSNs have demonstrated to play a key role in many applications ranging from environmental monitoring to military surveillance. The problem of efficient routing however is challenging due to ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

Cliff Asness, Wall Street’s standard bearer of traditional quant finance, was once skeptical that machine learning would ever make a big splash at AQR Capital Management. Yet seven years after the AQR ...