Financial crime is a constantly shifting threat. Fraudsters operate with unprecedented speed, scale, and technological capability. Their sole intent is to exploit any gap left unprotected, the most ...

UD professor's decades-long research helps organizations design transparent, accountable AI systems as new global regulations ...

At WIELS in Brussels, the artist’s brilliant, eccentric paintings unfold as surreal snapshots from a personal iconography that proves stubbornly inscrutable ...

An international research team developed CyberSentry, a software framework using advanced deep learning and optimization techniques to enhance cybersecurity in SCADA systems for power plants and ...

Franz Inc. expands graph, vector, and Neuro-Symbolic capabilities for enterprise-scale AI systems LAFAYETTE, CA, UNITED ...

In the study “Human-AI Synergy in Statistical Arbitrage: Enhancing Robustness Across Volatile Financial Markets,” published in the journal Risks, the researcher investigates how combining AI with ...

Explainability tools are commonly used in AI development to provide visibility into how models interpret data. In healthcare machine learning systems, explainability techniques may highlight factors ...

In a heated discussion with leading AI scholars Tuesday evening, Eric Schmidt, the American businessman who held the top post ...

Objectives Declining physical fitness, rising obesity and mental and behavioural diagnoses are growing public health issues in young adults. This study aimed to examine the associations between ...

While interpretability remains beyond reach and explainability, relying on approximations and simplification is still largely ...

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to ...

We present one of the first comprehensive evaluations of predictive information derived from retinal fundus photographs, illustrating the potential and limitations of readily accessible and low-cost ...