The expansion of artificial intelligence (AI) relies on trust. Users will reject machine learning (ML) systems they cannot trust. We will not trust decisions made by models that do not provide clear explanations. An AI system must provide clear … Read more
Denis Rothman graduated from Sorbonne University and Paris-Diderot University, writing one of the very first word2vector embedding solutions. He began his career authoring one of the first AI cognitive natural language processing (NLP) chatbots applied as a language teacher for Moët et Chandon and other companies. He has also authored an AI resource optimizer for IBM and apparel producers. He then authored an advanced planning and scheduling (APS) solution that is used worldwide. Denis is an expert in explainable AI (XAI), having added interpretable mandatory, acceptance-based explanation data and explanation interfaces to the solutions implemented for major corporate aerospace, apparel, and supply chain projects.