Researchers are moving beyond traditional curve-fitting methods by integrating large language models and agent-based modeling to create more accurate and interpretable epidemic forecasts.
New research reveals how advanced artificial intelligence can sift through social media to pinpoint the immediate impacts of crises and identify affected areas.
As AI systems gain more autonomy, ensuring their safety and security is paramount, and this article presents a comprehensive framework for proactive risk management.
A new framework standardizes the identification and quantification of risks facing artificial intelligence systems, connecting technical vulnerabilities to business impact.
Researchers have developed a novel agentic AI framework to dramatically improve the speed and accuracy of cloudburst prediction and enable coordinated responses to mitigate potential disasters.
A new framework proposes proactively simulating catastrophic AI scenarios to improve risk evaluation and prepare for previously unimaginable threats.
Researchers have developed a deep learning model that more accurately gauges how easy a document is to understand, going beyond simple word counts and sentence length.
As multi-agent systems powered by large language models become more complex, understanding how quickly they recover from reasoning failures is crucial for dependable operation.
A new approach leverages statistical guarantees to provide pilots with real-time risk assessments and preemptive warnings during flight testing.
A new deep learning pipeline leverages advanced image analysis to improve the detection of 16 different types of oral lesions from clinical images.