Researchers have developed a new AI framework that leverages natural language understanding to improve the accuracy and interpretability of traffic forecasting, especially during unexpected events.
A new framework efficiently integrates personal and market data to deliver more relevant and personalized financial asset recommendations using large language models.
New research demonstrates how explainable AI is unlocking the ‘black box’ of wildfire prediction models to build greater trust in forecasts and improve disaster preparedness.
A new multi-agent system leverages large language models to forecast hazards and enhance safety protocols in complex operational settings.
A new approach to combining weather model predictions significantly boosts the accuracy of forecasting high-impact events, offering crucial improvements for disaster preparedness.
A new approach leverages artificial intelligence and localized data to create adaptable regional boundaries that better address specific disaster risks and enable more targeted interventions.
New research reveals that the impact of data quality on credit risk models isn’t always what you’d expect.
A new analysis reveals that surprisingly few manipulated data points can compromise the accuracy and reliability of artificial intelligence systems used in medical diagnosis and treatment.
A new multi-agent system leverages AI to reconstruct the moments leading up to a crash with unprecedented accuracy, promising to reshape traffic collision analysis.
A new machine learning approach leverages the interconnectedness of power grids to forecast how long outages will last after major storms.