AI Strategy Seminar Series | Where is it Cost-effective to Deploy AI?

Abstract: The economic and environmental impacts of deep learning are increasing rapidly and could make some prospective AI applications unattractive to companies. In this talk, I will discuss my work with the Lab to understand which applications will make the most business sense.

Bio: Dr. Neil Thomspon is an Innovation Scholar at MIT’s Computer Science and Artificial Intelligence Lab and the Initiative on the Digital Economy. He is also an Associate Member of the Broad Institute. Previously, he was an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he co-directed the Experimental Innovation Lab (X-Lab), and a Visiting Professor at the Laboratory for Innovation Science at Harvard. He has advised businesses and government on the future of Moore’s Law and has been on National Academies panels on transformational technologies and scientific reliability.

He did his PhD in Business and Public Policy at Berkeley, where he also did Masters degrees in Computer Science and Statistics. He has a masters in Economics from the London School of Economics, and undergraduate degrees in Physics and International Development. Prior to academia, he worked at organizations such as Lawrence Livermore National Laboratories, Bain and Company, The United Nations, the World Bank, and the Canadian Parliament.

Event Information: The AI Strategy Seminar Series is a quarterly offering for the MIT-IBM Watson AI Lab’s corporate membership program hosted by thought leaders in business applications of AI. While our monthly technical series is designed to educate our members’ employees on latest advancements in the field of AI, this quarterly seminar series will discuss higher level AI strategy and trends across industries. The seminar is open to any employee of our member companies, technical or non-technical alike.

For any questions regarding this event, please reach out to Kate Soule (kate.soule@ibm.com).