Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

Researchers developed an AI model that stabilizes molecular simulations under extreme conditions, enabling long, accurate ...

The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, necessitates innovative approaches to resource management. Biomass, a versatile ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale.

Using six gut- and diet-derived metabolites, a machine learning model had 79% accuracy in classifying adults as having ...

A UC Berkeley team used Apache Spark ML to predict airline delays at scale, training models on millions of flight records and ...

Web3 is looking at a similar trajectory. The industry is pivoting from theoretical musings to measurable utility in 2026, ...