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 ...

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

As we head into the New Year, experts across the tech landscape weigh in to share what they think will happen in 2026 ...

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

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 ...

Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework ...

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.

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

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