Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex ...

Topological defects govern how many advanced materials behave, but predicting them has traditionally required slow, resource-intensive simulations. Researchers at Chungnam National University have ...

Order doesn’t always form perfectly—and those imperfections can be surprisingly powerful. In materials like liquid crystals, ...

Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...

Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving intellectual tasks. These models are not replicas of human intelligence. Their ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

A new artificial intelligence approach combines deep learning with physical modeling to extract detailed aerosol properties from complex satellite observations. By learning how light intensity and ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...

Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry transitions into an ordered ...