Science

A new framework offers a lifecycle-based approach to managing AI risks and ensuring alignment with evolving global regulations.

Researchers have unveiled a comprehensive evaluation framework designed to rigorously assess the safety and compliance of large language models when applied to complex financial tasks.

A new approach leverages graph neural networks to dramatically accelerate the simulation of blood flow within intracranial aneurysms, paving the way for faster, more accurate risk assessment.

A recent community strike on Stack Exchange highlights the growing tensions between platform policies, AI integration, and the rights of volunteer contributors.

A new analysis reveals how large language models are reflecting-and potentially shaping-research trends in understanding and addressing healthcare inequities.

Researchers are leveraging real-world crash data to create realistic and controllable scenarios for rigorously testing the safety of autonomous vehicles.

Training increasingly complex AI models requires careful management of GPU resources, and accurately forecasting memory usage is now critical for efficient development.

Researchers have developed a novel artificial intelligence framework that combines geometric and stochastic modeling of physiological data to improve prediction of life-threatening events like SUDEP and stroke.

Researchers are leveraging the power of large language models to generate realistic, data-driven stress tests for financial portfolios.

A new methodology leverages high-performance computing to comprehensively assess power grid vulnerability to cascading failures and identify critical infrastructure.