Explainable AI (XAI) is a subset of standard AI technology that allows us to understand the decision-making process of AI models. Researchers are using…
Browsing: Explainable AI
Understand the intricacies of Explainable AI through our extensive articles. Our content deciphers the transparency and interpretability aspects of AI systems, making complex concepts accessible to everyone.
Researchers from the University of Manitoba, Canada, are using explainable AI (XAI) to develop improved antibiotics. XAI is being used to train AI drug…
Researchers have introduced Temporal Reward Decomposition (TRD) to enhance explainability in reinforcement learning by predicting the next N expected rewards, revealing when and what…
Scientists from the University of Bristol have made significant strides in addressing AI ‘hallucinations’ and improving anomaly detection algorithms for Critical National Infrastructures. They…
The AI-RAN Alliance, led by industry expert Choi, aims to transform telecommunications through AI-RAN advancements, increased efficiency, and new economic opportunities. The alliance will…
The document verification market is expected to see significant growth in the next few years due to increasing regulatory frameworks and compliance standards, emphasis…
The article discusses the importance of explainable AI in understanding the decision-making process of deep neural networks. It highlights the need for engineers to…
A study compared the performance and explainability of non-expert humans, a traditional machine learning model, and a large language model in text classification. The…
Transformer Explainer is a new tool designed to bridge the gap between the complexity of Transformer models and the simplicity required for effective learning.…
This article discusses the development and evaluation of an explainable AI model for diagnosing melanoma, as well as a reader study with clinicians to…