Science

Despite remarkable advances in language processing, artificial intelligence consistently struggles to accurately interpret user intent, opening the door to manipulation and unexpected behavior.

Researchers are leveraging the power of differential equations to more accurately and efficiently forecast the movements of multiple celestial bodies.

New research reveals a universal indicator-critical slowing down-that can predict impending failure in a wide range of systems, from engineered infrastructure to natural ecosystems.

This research introduces an architecture that uses blockchain technology to enhance the security, transparency, and accountability of artificial intelligence systems operating in real-world environments.

A novel system aims to establish a clear record of AI application activity, fostering accountability and mitigating risks in increasingly complex AI ecosystems.

A new approach combines machine learning and physics-based modeling to assess wildfire risk at the individual building level, factoring in both environmental conditions and structural vulnerabilities.

A new framework combines qualitative analysis of investor-founder conversations with machine learning to offer a more nuanced and accurate view of startup viability.

Researchers have developed a novel framework that blends the power of artificial intelligence with formal verification to ensure the safe and reliable operation of next-generation 5G networks.

Researchers have developed a refined forecasting model that leverages economic indicators and regime switching to better anticipate equity premium movements.

A new deep learning model is demonstrating impressive accuracy in identifying online harassment within Spanish-language text.