AI/ML has become an integral part of today's technology landscape, but what often goes unnoticed is the underlying Machine Learning Infrastructure.
This 25-minute talk will peel back the curtain on this critical yet overlooked component and elucidate the evolution of Machine Learning Infrastructure considering the new GenAI wave.
We'll start by highlighting the 'hidden' efforts and technical debt involved in transitioning machine learning models from prototype to production, referencing the rise of Machine learning Infrastructure from frontier tech companies.
Then, we'll introduce the evolving concept of 'Gen AI', the next frontier of AI, emphasizing the increasing role of Foundation Models, landscape value proposition, and focus on the challenges of domain-specific fine tuners.
After a comparative lens between traditional machine learning and emerging Generative AI technologies, we'll explore the early thoughts on Generative AI infrastructure and how it's setting the stage for the future of AI.
Take the chance to understand the infrastructure that makes AI possible.
Suqiang Song
As engineering director, Suqiang leads multiple teams of ML infrastructure engineers, driving machine learning platforms and infrastructure solutions for all product and engineering teams in Airbnb.
As a senior AI leader, he works closely with senior partners in product and engineering to shape Airbnb’s vision in AI and ML, streamline innovations, and ensure Airbnb has a complete set of AI infrastructure that meets long-term needs.
Previously, Suqiang served as Vice President, Data Platforms and Engineering Services at Mastercard, as one of the Data / AI commit board members to identify strategies and directions for Data Enablement, Data and ML platforms across multiple product lines and multiple deployment infrastructures. He has led worldwide engineering teams of data engineers, Machine Learning engineers, and data analysts to build unified data and ML platforms both on-premise and on-cloud for Mastercard