Just less than before, according to the ORCA test exclusive Current-day LLMs are prediction engines and, as such, they can ...

Using machine learning and math, a Brigham Young University student improved a key tool firefighters rely on during wildfire season As Utah enters the heart of wildfire season, wind might be the most ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

The formula, developed by a URV research team, accurately describes the movement patterns of people. The results have been published in the journal Nature Communications How many people will travel ...

Jane Housley, a BYU mathematics graduate and wildfire modeling researcher, developed a faster, smarter way to predict how wind moves through fire-prone terrain. Her work could help firefighters ...