SSCS March Technical Webinar: Scaling AI Sustainably by Carole-Jean Wu

Date

2024-03-13

Time

12 PM ET

Location

Webinar - Online

Contact

Aeisha VanBuskirk – a.vanbuskirk@ieee.org

Web site

https://ieee.webex.com/weblink/register/r3e666b5dea4602ee39b1ba767f5c347b

Sponsorship

Sponsor

Presenter

Carol-Jean Wu

Description

The past 50 years has seen a dramatic increase in the amount of compute per person, in particular, those enabled by AI. Despite the positive societal benefits, AI technologies come with significant environmental implications. I will talk about the carbon footprint of AI computing by examining the model development cycle, spanning data, algorithms, and system hardware. At the same time, we will consider the life cycle of system hardware from the perspective of hardware architectures and manufacturing technologies. The talk will capture the operational and manufacturing carbon emissions of AI computing. Based on the industry experience and lessons learned, I will share key challenges, on what and how at-scale optimization can help reduce the overall carbon footprint of AI and computing. This talk will conclude with important development and research directions to advance the field of computing in an environmentally-responsible and sustainable manner. 

Carole-Jean Wu is a Director of AI Research at Meta. She is a founding member and a Vice President of MLCommons – a non-profit organization that aims to accelerate machine learning for the benefits of all. Dr. Wu also serves on the MLCommons Board as a Director, chaired the MLPerf Recommendation Benchmark Advisory Board, and co-chaired for MLPerf Inference. Prior to Meta/Facebook, She was a professor at ASU.

Dr. Wu is passionate about pathfinding and tackling system challenges to enable efficient, responsible AI execution. Her expertise sits at the intersection of computer architecture and machine learning. Dr. Wu's work has been recognized with several awards, including IEEE Micro Top Picks and ACM/IEEE Best Paper Awards. She received her M.A. and Ph.D. from Princeton and B.Sc. from Cornell.