Science

A new approach to observability leverages intelligent agents to dramatically accelerate issue resolution in complex e-commerce systems.

A new approach combines the efficiency of smaller AI models with the power of large language models to overcome data limitations and improve threat detection.

Generative AI adoption in the U.S. banking sector initially lowers productivity but ultimately amplifies systemic risk through interconnected algorithms and network effects.

A new framework explicitly models how disruptions like accidents impact traffic flow, leading to significantly improved predictions.

A new framework analyzes international financial risk not through traditional deficit metrics, but by mapping the network of balance of payments and assessing its inherent stability.

New research shows artificial intelligence is surprisingly adept at forecasting the success of startup ventures, challenging traditional methods of strategic foresight.

A new approach aligns graph neural networks with financial tasks, boosting performance in dynamic stock market forecasting.

As artificial intelligence moves beyond conventional deep learning, current regulatory frameworks struggle to address the unique challenges posed by brain-inspired computing architectures.

A new framework reveals how the spectral properties of key network operators govern both the robustness and interpretability of deep learning models.

This research details a new science gateway that streamlines post-disaster analysis by combining photogrammetry and machine learning techniques.