Open Source AI Infrastructure Ecosystem: A Leveling Force in a Globalized World

Bill Jia is a seasoned technologist with a distinguished career spanning nearly two decades at leading technology companies, including Google, Meta, and Microsoft. As Vice President of Engineering at Google, he currently leads teams responsible for the innovation, scalability, stability and performance of the company's Core ML/AI and AI infrastructure. This critical role positions him at the forefront of Google's AI initiatives, ensuring the seamless operation of systems that power a wide range of AI-driven products and services, including Gemini, Imagen and Veo.

Prior to joining Google, Bill held a pivotal role at Meta, overseeing company-wide critical areas including PyTorch, AI Training/Inference, AI Hardware, Data Infrastructure, Performance and Capacity Engineering, Hardware Engineering, and Supply Chain Management. Before his time at Meta and Google, Bill spent three years at Microsoft, where he focused on improving and optimizing various online services/products.

Across all of his roles, Bill has been instrumental in advancing AI capabilities. He played a leading role in the development and adoption of PyTorch (a widely used AI framework within Meta and the broader AI community), and JAX/XLA (the AI framework and compiler within Google and also across Gen AI community). Bill’s work has directly influenced the advancement of AI capabilities across a diverse range of applications, including Search, Ads, News Feed, Photos, and Videos, enhancing user experiences on a global scale.

Bill holds dual Bachelor degrees from Shanghai Jiao Tong University and received his MS degree from National University of Singapore. Bill obtained his PhD degree in operations research and algorithms design from the University of Southern California (USC) in 2007.

Yann LeCun is Chief AI Scientist at Meta and a Professor at NYU. He was the founding Director of Meta-FAIR and of the NYU Center for Data Science. After a PhD from Sorbonne Université and research positions at AT&T and NEC, he joined NYU in 2003 and Meta in 2013. He received the 2018 ACM Turing Award for his work on AI. He is a member of the US National Academies and the French Académie des Sciences.

http://yann.lecun.com

Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge where he leads the University’s flagship mission on AI, AI@Cam. He has been working on machine learning models for over 25 years. He returned to academia in 2019 after three years as Director of Machine Learning at Amazon. His main interest is the interaction of machine learning with the real world. This interest was triggered by deploying machine learning in the African context, where ‘end-to-end’ solutions are normally required. This has inspired new research directions at the interface of machine learning and systems research, this work is funded by a Senior AI Fellowship from the Alan Turing Institute. Neil is also visiting Professor at the University of Sheffield and the co-host of Talking Machines. He is the author of the forthcoming book The Atomic Human (release date 6th June 2024).