Supercharging Molecular Dynamics with Machine Learning

A new interface allows researchers to seamlessly integrate neural network potentials into GROMACS, accelerating and improving the accuracy of biomolecular simulations.

A new interface allows researchers to seamlessly integrate neural network potentials into GROMACS, accelerating and improving the accuracy of biomolecular simulations.

New research explores how internal collaboration can move AI governance requirements from abstract regulation to concrete implementation within software development teams.
A new study reveals the key psychological factors influencing whether university students will openly admit to using artificial intelligence in their coursework.
![The model organizes complex inter-object transformations into a structured scalar axis representing relative displacement, achieved through a group homomorphism and visualized with Principal Component Analysis, where outward motions are indicated by larger positive scalar values [latex]s[/latex] (red) and inward motions by smaller negative values (blue).](https://arxiv.org/html/2604.20925v1/img/exp2.png)
Researchers have developed a novel unsupervised learning framework that allows AI agents to autonomously discover and represent the relationships between objects in visual scenes.

Researchers have created a large-scale resource designed to help AI systems generate more effective and informative diagrams for scientific publications.
A new exploration considers the possibility of detecting advanced extraterrestrial intelligence leveraging the unique physics surrounding supermassive black holes.

A new architecture leverages artificial intelligence to automate the complex process of military course of action development, accelerating decision-making and enhancing strategic options.

Researchers have developed a navigation system that empowers robots to explore and interact with environments using both visual perception and natural language instructions.
New research reveals that many AI governance prompts lack the structural detail needed to ensure effective implementation and oversight.

New research demonstrates how synthetic data can overcome limitations in creating realistic and controllable videos of human movement.