New research reveals that the post-crisis drive to consolidate financial institutions inadvertently increased systemic risk by creating more interconnected and vulnerable networks.
A new approach leverages tensor networks to accurately forecast the long-term behavior of complex, chaotic dynamics.
A new approach leverages federated learning and explainable AI to identify financial risks across U.S. states without sharing sensitive data.
Researchers have developed a system that allows large language models to dynamically improve their defenses against evolving adversarial attacks.
A new deep learning system is now operational, using data from multiple satellites to identify and quantify methane point sources across the globe.
A new approach leverages natural language processing to anticipate social unrest and planned gatherings by analyzing news coverage.
A new framework for ensuring the reliability, transparency, and regulatory compliance of AI models used in critical reinsurance functions.
A detailed analysis of production incidents reveals critical vulnerabilities and practical strategies for building more reliable AI services.
A new system leveraging artificial intelligence achieves forecasting accuracy comparable to top human prediction experts.
As AI agents and connected devices multiply, existing infrastructure faces unprecedented strain, demanding a new approach to network design.