Abstract: The rise in deep neural networks (DNNs) has led to increased interest in explaining their predictions. While many methods for this exist, there is currently no consensus on how to evaluate ...

Why 90% of enterprise AI projects fail to scale, and how Turinton is compressing adoption cycles by aligning AI with business ...

The eligible studies included technology-based research involving wearable devices, sensors, or mobile phones focused on explainability, machine learning, or deep learning and that used quantified ...

Abstract: This review paper addresses the research question of the significance of explainability in AI and the role of integrating KG and RL to enhance Explainable Recommender Systems (XRS). It ...

Unlike traditional applications, agentic systems must monitor themselves in production, adapt to dynamic data and user ...