The wetland puzzle that stumped hydrology for decades—how physics and AI joined forces to predict unmeasured regions

For years, the Prairie Pothole Region has bothered me in a very specific way. On a map, it looks like a normal landscape: ...
Tech.eu

Venture Kick backs Fainite to advance physics-based simulations

Fainite is developing a physics-aware AI platform to accelerate simulation workflows, reduce engineering complexity and ...
Science Daily

Improving hurricane modeling with physics-informed machine learning

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...
Frontiers

Hybrid Mechanistic–AI Modeling with Physics-Trained Neural Networks for Patient Digital Twins

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.
The Conversation

Nobel Prize in physics spotlights key breakthroughs in AI revolution − making machines that learn

Ambuj Tewari receives funding from the NSF. If your jaw dropped as you watched the latest AI-generated video, your bank balance was saved from criminals by a fraud detection system, or your day was ...
Devdiscourse

Big Data and AI propel geoscience into new digital era

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...
EurekAlert!

KIDL: A knowledge-informed deep learning paradigm for generalizable and stability-optimized car-following models

The knowledge-informed deep learning (KIDL) paradigm, with the blue section representing the LLM workflow (teacher demonstration), the orange section representing the distillation pipeline of KIDL ...