While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

As enterprises shift from AI experimentation to scaled implementation, one principle will separate hype from impact: explainability. This evolution requires implementing 'responsible AI' frameworks ...

One of the most important aspects of data science is building trust. This is especially true when you're working with machine learning and AI technologies, which are new and unfamiliar to many people.

TruEra, provider of a suite of AI quality solutions, is releasing TruLens, an open source explainability software tool for machine learning models that are based on neural networks. TruLens is a ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Explainability is not a technology issue — ...

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset available to the institution. Moving AI decisioning closer to this data ...

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 ...