Webinar

CASS-Wide Webinar XXIII: Are Hardware and System Design The Missing Piece for AGI?: Hardware and Systems Considerations for Next Generation AI

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Abstract

Are Hardware and System Design The Missing Piece for AGI?: Hardware and Systems Considerations for Next Generation AI

Today’s AI solutions face a trifecta of challenges: The Great AGI Leap, The Energy Wall and The Alignment Problem. Recent AI solutions have been quite energy inefficient. They consume unprecedented amounts of energy during training and unsustainable peak power during run-time. Making things worse, the amount of compute used for training doubles every 3.5 months. Current approach to AI lacks system design; even though system-level characteristics play a critical role in the human brain; from the way it processes information to how it makes decisions. For the AGI Leap, the required integration and balanced operation of multiple functional subsystems is impossible to achieve without system-design. Lastly, for the alignment problem, AI lacks the capacity to employ multiple subsystems (such as System 1 and 2, model-free and model-based learning) in a balanced way for moral decisioning. In this talk, we investigate the importance of system design for next generation AI solutions and argue that system-design is the missing piece without which the three grand challenges may never be solved.

Description

This talk will take place on 25 September 2024 at 9:00 AM EDT (-4:00 UTC) and features a talk by Dr. Eren Kurshan,  titled "Are Hardware and System Design The Missing Piece for AGI?: Hardware and Systems Considerations for Next Generation AI". Registration for this series is entirely free and will be limited to the first 1,000 registrants per event. 

Biography

Dr. Eren Kurshan is an AI researcher and technology executive focused on building AI systems for large-scale industrial use cases. Kurshan received her Ph.D. in Computer Science from the University of California, Los Angeles, as well as a Master’s in Computer Science and a Bachelor’s in Electrical Engineering. She serves as an Executive-in-Residence at Princeton University and the Head of Research and Methodology. Prior to these roles, she led a number of AI/ML and emerging technology programs at Columbia University, J.P. Morgan and IBM T.J. Watson Research Labs. She was a Visiting Fellow at Princeton’s Center for Information Technology Policy (2015-2016) and served as an Adjunct Professor at Columbia University since 2014. Dr. Kurshan published over 80 peer reviewed technical publications and ~260 patents, with approximately 100 granted. She has served as an associate editor of several IEEE and ACM journals and transactions including the IEEE Transactions on Emerging Technologies in Computing, IEEE Transactions on Computers, ACM Journal of Emerging Technologies in Computing, ACM Transactions on Design Automation of Electronic Systems and the Journal of Low Power Electronics. She was the recipient of 2 Best Technical Paper Awards from IEEE and ACM conferences, as well as top inventor and licensing awards from Bank of America and IBM. She received 2 Outstanding Research and Corporate Accomplishment Awards from IBM for her work on system design and optimization and emerging technology development respectively.