November 24-26, 2025
Auditorium between Building 4 & 5, Level 0, Room 0215
Overview
The KAUST Workshop on Distributed Training in the Era of Large Models is a three-day, in-person event dedicated to one of the most pressing challenges in artificial intelligence today: how to efficiently scale learning algorithms to meet the massive computational and data demands of modern AI models.
Over the past few years, models have grown from millions to hundreds of billions of parameters, delivering remarkable improvements in capability, but also creating unprecedented challenges for training. Scaling this next generation of AI systems requires advances across distributed optimization, communication-efficient algorithms, model-parallel architectures, and hardware-software co-design.
This workshop will bring together an exceptional group of international researchers, industry practitioners, and KAUST faculty to share state-of-the-art solutions and explore what comes next for distributed and large-scale training. Through invited talks and informal interactions, participants will have the opportunity to engage deeply with emerging ideas, discover new research directions, and build collaborations that will shape the future of scalable machine learning.
For full details about the program, speakers, and schedule, please visit the workshop website.