Using machine learning and math, a BYU student improved a key tool firefighters rely on during wildfire season ...

Using machine learning and math, a Brigham Young University student improved a key tool firefighters rely on during wildfire ...

Brigham Young University graduate Jane Housley's research could help make a widely used wildfire modeling tool faster and ...

The new study, titled "The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity," comes from a team at Apple led by Parshin Shojaee ...

The end effector of a robot manipulator needs to be accurately positioned in the workspace when it is used for automated applications. Manipulators are driven using the torque inputs supplied to the ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

Neuromorphic computing, as a novel approach to processing information by mimicking biological neural networks, has gradually demonstrated significant ...

The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating ...

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the representation of the space immediately surrounding the body. This area, also ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...