Phys.org

Spin as an input parameter: Machine learning predicts magnetic properties of materials

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends and to the robotics systems powering automation. They're also inside more ...
Frontiers

Physics-Grounded Machine Learning Force Fields for Biomolecular Modelling: Variational, Renormalization and Effective Field Theory Approaches

Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...
Yahoo Finance

WiMi Explores the Application of Neural Networks in Parameter Optimization for Dual-Field Quantum Key Distribution

BEIJING, June 29, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, announced that they ...
The Tech Edvocate

How Moonshot AI’s Kimi K3 Is Disrupting the AI Landscape with Its 2.8-Trillion Parameter Model

Spread the love“`html On July 16, 2026, Moonshot AI made waves in the artificial intelligence (AI) domain by officially ...
Eos

Comparing Machine Learning Models of Raindrop Formation

Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
TMCnet

Hanbat National University Study Advances Machine Learning Calibration of Biosensors for Microcystin Toxin Monitoring in Freshwater

A machine learning model adjusts toxin readings for water-quality variability, enabling faster, lower-cost on-site testing without repeated recalibration CHUNGCHEONG PROVINCE, South Korea, July 10, ...