Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

More information: Xinwei Su et al, Machine learning modeling assisted intelligent process analysis for high - performance virus filtration, Journal of Membrane Science (2025).

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...

Innovative AI techniques in cement formulation lead to eco-friendly mixes, significantly cutting emissions and improving ...

Brian Ongioni, chief product officer, uMotif, discusses how AI and machine learning can enhance patient-reported outcomes by ...

A new study reveals how children outlearn AI - using movement, senses, and social cues to master language faster than any ...

A Tribune reporter and data nerd went looking for a smarter way to evaluate and draft NBA players. From Cooper Flagg to a few ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...