Transparency and explainability are only way organizations can trust autonomous AI.

OpenAI today published a research paper that outlines a new way to improve the clarity and explainability of responses from generative artificial intelligence models. The approach is designed to ...

As the capabilities of artificial intelligence (AI) evolve, they push the boundaries of human understanding. Instead of transparent, explainable mechanisms, many AI applications are “black boxes,” ...

Model risk management is entering a period of rapid transformation as institutions integrate increasingly complex AI, ML, and GenAI models into their inventories. Traditional validation approaches are ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...

The financial services industry is undergoing an AI-driven transformation that extends well beyond the generative-AI headlines. Chatbots may capture attention, but a far quieter and more consequential ...

We developed precompiled lexicons and classification rules as features for the following ML classifiers: logistic regression, random forest, and support vector machines (SVMs). These features were ...