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 is learning without crossing ethical lines.

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

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

See how Langraph powers a multi-agent stock sim with configurable rounds and models, helping you compare trade plans without ...

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

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

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

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

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

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

Lux and Discovery are engineered for scientific workloads that now pair high-fidelity simulation with large AI models, ...