# 主题
Reduce AI's Carbon Footprint
# 主讲人
Dr. Guosheng Hu, the Head of Research at Oosto
# 报告摘要
AI-driven data centres, operating continuously and predominantly powered by fossil fuels, contribute significantly to global greenhouse gas emissions (2.5-3.7%). The widespread use of large foundation models such as ChatGPT exacerbates this environmental impact. This talk explores strategies for mitigating AI's carbon footprint through model acceleration aiming to significantly reduce computations while maintaining the accurate of Al models. This session will spotlight various model acceleration techniques, including Neural Architecture Search, Knowledge Distillation, and others. Beyond academic advancements, the talk will also delve into successful industrial applications. Last, it will outline potential future research directions in the field of model acceleration.
# 嘉宾简介
Dr. Guosheng Hu serves as the Head of Research at Oosto (a Unicorrof AI). Additionally, he holds the title of Honorary Professor of Practice atQueen's University Belfast. Prior to his role at Oosto, he was a ResearchFellow in the THOTH team at INRIA Grenoble Rhone-Alpes, France. DrHu earned his PhD under the supervision of Prof. Josef Kittler at the University of Surrey, UK. His expertise lies in the intersection of computer vision and deep learning. With a robust academic background, he has published numerous research papers at major conferences and journals.