Unlike conventional black-box AI models that flag anomalies without explanation, IFAT produces decision trees that map the ...

His work reflects how AI-native platforms address singular challenges in financial data handling, fraud detection, and risk ...

While the public focuses on model size or benchmark wins, the layer where actual decisions happen gets far less attention.

As customer expectations evolve, businesses are seeking more advanced AI solutions that can bridge the gap between automated ...

Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), today announced ...

It is important that organizations understand who trains their AI systems, what data was used and, just as importantly, what went into their algorithms’ recommendations. A high-quality explainable AI ...

The patient knowledge gap is considered to be a critical shortcoming for the medical community, particularly at a time when ...

LOS ALTOS, Calif., Aug. 7, 2025 /PRNewswire/ -- Kubit, the leading customer journey analytics platform, today announced the launch of Ask Kubit, a conversational AI interface that allows teams to ask ...

Many past machine learning approaches to microplastic detection have been criticised for relying on idealised datasets ...

Explainable AI (XAI) is a field of AI that focusses on developing techniques to make AI models more understandable to humans.

A novel image-based deep learning approach achieves high accuracy and interpretability, offering potential for clinical ...