The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

From space exploration to artificial intelligence, modern scientific breakthroughs depend on moving large amounts of data ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Researchers at College of Food, Agricultural and Natural Resource Sciences are using AI to detect patterns across landscapes, atmospheres and ecosystems at scales that were previously impossible.

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

AI users and developers can now measure the amount of electricity various AI models consume to complete tasks with an ...

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...

Understanding the connection between behavior and brain cell activity is a major goal of neuroscience. To make progress, neuroscientists often choose simple, transparent lab animals because it's ...