Science

A new approach to agentic AI leverages internal adversarial testing to dramatically improve accuracy and reliability in commercial insurance underwriting.

A new framework clarifies why 5G radio access networks might fail, enabling proactive maintenance and improved reliability.

New research reveals that advanced artificial intelligence systems demonstrate surprisingly nuanced strategic thinking when simulating high-stakes nuclear confrontations.

This review introduces a powerful framework for modeling complex financial instruments by treating them as systems for allocating stochastic cash flows.

A new analysis details the escalating risks posed by increasingly powerful artificial intelligence systems and outlines potential pathways to ensure their safe development and deployment.

As large language models infiltrate financial analysis, a critical examination of potential biases is essential for reliable results.

Current AI safety evaluations often fail to account for the unique vulnerabilities and contextual risks present in African nations, demanding a more localized approach.

A new theoretical framework provides a robust method for understanding and managing uncertainty when inferring causal relationships from distributed time-series data.

A novel algorithm accurately pinpoints key spreaders within a population during an ongoing epidemic, offering a faster and more efficient method for targeted intervention.

A new method leverages neural networks to dramatically accelerate Markov Chain Monte Carlo simulations, offering a powerful tool for analyzing complex systems and estimating transition probabilities.