Overcoming Obstacles to AI Execution: Trust, Scale, and Reasoning


Corporate survey data indicate consensus on the importance of AI for competitive advantage, but only a small fraction of companies are actually executing on AI in their core businesses. This is partially due to fundamental limitations of the technology on key business requirements. Can we trust AI models? Can we scale them? Can we use them flexibly for higher order problem solving? These challenges motivate AI scientists at the MIT-IBM Watson AI Lab, who work with member companies to convert fundamental research to real-world impact. In this presentation, MIT-IBM Strategy & Operations Lead and business program leader Mark Weber will review the latest advancements in AI robustness, scalability, and fluid intelligence as they relate to opportunities in business applications.


Mark Weber is an applied researcher and Strategy & Operations Lead at the MIT-IBM Watson AI Lab, a $250 million partnership funding over 200 scientists making fundamental breakthroughs in AI. Through the lab’s corporate membership program, which he runs, Mark works closely with global leaders across multiple sectors on the creative challenge of bridging fundamental science to real-world impact. Mark’s current applied research includes neuro-symbolic generative modeling for construction monitoring, graph deep learning for anti-money laundering, and supply chain demand forecasting. Mark also oversees strategic engagements with IDEO, the International Monetary Fund, and the Internal Revenue Service. Prior to IBM Research, Mark was a graduate researcher at the MIT Media Lab and a fellow at the MIT Legatum Center for Development & Entrepreneurship while he earned his M.B.A in finance from MIT Sloan. There he led the development of an open-source protocol called b_verify for verifiable records in supply chain finance. Before his foray into technology, Mark spent the first chapters of his career focused on political economy and development. He produced three documentary films on these subjects, most notably the critically acclaimed film Poverty, Inc