Dr. Steve Chan
S&T Advisor
Brief biography:
Dr. Chan serves as a Science & Technology (S&T) Advisor for various organizations within government and industry. He is an inventor with 14 U.S. and international patents, and he is the author of 92 peer-reviewed book chapters, journal articles, and conference papers, which include 38 IEEE papers (for 65 of the refereed publications, he is first author, and 20 of these received Best Paper/Best Presentation awards). He has served as Chief Scientist/Principal Investigator for dozens of governmental/intergovernmental reports (e.g., U.S. Government, ASEAN Member States, United Nations), co-founded numerous research centers within industry (e.g., Fortune 500) as well as academia, and served as center advisor for National Science Foundation-funded consortiums of industry and government laboratories. He previously served as Vice President/Chief Innovation & Strategy Officer for IBM’s Safer Planet & Smarter Cities Division, Chief Technology Officer/Chief Architect roles at MIT, and Senior Fellow at Harvard. He is an alumnus of both MIT and Harvard. His presentations and lectures have been featured at the White House, National Research Council of the National Academies, and World Congress on Information Technology.
Talk Title:
The Prospective Paradox of Self-Monitoring at a Hyperscale Artificial Intelligence Data Center
Abstract:
This era of Artificial Intelligence (AI) has been marked by a dramatic increase in the number of hyperscale AI Data Centers (AIDC) being built. The computational density at these AIDC has surged, and the infrastructural and utilities requirements have also burgeoned. As AIDCs endeavor to leverage their own AI capabilities to self-monitor their extensive AIDC complexes, certain prospective paradoxes are unveiled. It turns out that, unless carefully managed, the AI-facilitated self-monitoring has the potential to dramatically increase the very infrastructural and utilities requirements that it was originally endeavoring to constrain.