Science

Researchers are drawing inspiration from the intricate wiring of the mouse visual cortex to build more efficient and robust deep learning models for facial emotion recognition.

A new study reveals that hands-on experience training small language models dramatically improves understanding of how artificial intelligence works, moving beyond simplistic analogies.

Researchers have created a benchmark demonstrating that AI agents can independently develop effective control policies for physical robots, often exceeding human-level performance.

A new study reveals that automatically generated code changes, while often accepted, can quietly introduce complexity and potential vulnerabilities into software projects.

A new evaluation of decentralized multi-robot SLAM systems reveals the critical trade-offs for autonomous mapping in challenging planetary analogue terrains.

A new machine learning framework accelerates the discovery of promising metal hydrides for efficient and scalable hydrogen storage.

As artificial intelligence reshapes work, a new study examines how productivity gains can subtly erode human skills and dignity.

A new library demonstrates the potential-and challenges-of combining traditional agent programming with the power of modern large language models.

A new study examines the impact of AI coding assistants on the quality and characteristics of pull requests, comparing them directly to human-authored contributions.

Researchers have developed a method that combines data-driven learning with inherent physical symmetries to accurately identify the governing equations of complex dynamical systems.