Science

A new approach uses AI to automate the complex process of predicting power grid stability, accelerating analysis and optimizing system design.

As large language models become increasingly integrated into critical applications, understanding how – and why – they fail is paramount.

A new framework leverages advanced attention networks and dynamic risk assessment to dramatically improve forward collision warning systems in challenging traffic conditions.

A new report details the evolving landscape of technical and institutional safeguards designed to manage the risks of increasingly powerful artificial intelligence.

New research demonstrates how advanced image recognition systems are improving the speed and accuracy of early wildfire detection.

Researchers are boosting prediction accuracy by introducing a method that separates coarse-grained trends from fine-grained details in time-series data.

As AI systems become increasingly complex and permeate safety-critical applications, researchers are exploring innovative ways to ensure their reliability and prevent potentially catastrophic failures.

A novel approach to long-term financial modeling incorporates realistic volatility and drift uncertainty for improved forecasting accuracy.

New research reveals that commonly used AI models for predicting patient diagnoses can disproportionately fail vulnerable groups when faced with the messy reality of imperfect clinical data.

A new approach leverages the power of qudits to build interpretable quantum neural networks for improved credit risk assessment.