For years, the artificial intelligence industry has followed a simple, brutal rule: bigger is better. We trained models on ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

A study in Nature Communications by Michele Ceriotti’s group at EPFL has introduced a new dataset and model that greatly improve the efficiency of machine-learning interatomic potentials (MLIPs) and ...

AI tool GyroSwin simulates fusion plasma in seconds, cutting costs and speeding the design of future fusion power plants.

Test vendors use AI and machine learning to handle massive data volumes from complex electronics and detect hard-to-find ...

AI-driven adaptive safety stock planning is revolutionizing inventory management in fluctuating supply chains.

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...

Explore the strategic technology trends that will shape 2026, from AI supercomputing platforms to AI-native development, and ...

As organizations modernize industrial systems, high-integrity functional safety strategies are now critical for reducing risk and ensuring compliance. This report delivers actionable insight into the ...

A new study published in Engineering by Xin Wang, Jian Yao, Jin Zhang and their colleagues proposes a machine-learning-guided strategy that combines ...