Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate predictions by analyzing large amounts of data. These networks are structured in layers, each of which transforms input data into 'features' that guide the analysis of the next layer.| phys.org
Neutrinos are tiny and neutrally charged particles accounted for by the Standard Model of particle physics. While they are estimated to be some of the most abundant particles in the universe, observing them has so far proved to be highly challenging, as the probability that they will interact with other matter is low.| phys.org
New theoretical research by Michael Wondrak, Walter van Suijlekom and Heino Falcke of Radboud University has shown that Stephen Hawking was right about black holes, although not completely. Due to Hawking radiation, black holes will eventually evaporate, but the event horizon is not as crucial as had been believed. Gravity and the curvature of spacetime cause this radiation too. This means that all large objects in the universe, like the remnants of stars, will eventually evaporate.| phys.org
The brain's ability to process information is known to be supported by intricate connections between different neuron populations. A key objective of neuroscience research has been to delineate the processes via which these connections influence information processing.| phys.org
To produce light, lasers typically rely on optical cavities, pairs of mirrors facing each other that amplify light by bouncing it back and forth. Recently, some physicists have been investigating the generation of "laser light" in open air without the use of optical cavities, a phenomenon known as cavity-free lasing in atmospheric air.| phys.org