CEO Dillon Erb of Paperspace cloud-native machine learning platform examines the challenges developers face in getting real value from ML programs
1. Tell us how you came to be the co-founder and CEO at Paperspace. How did developing cloud native machine learning platform become your career path?
I’m the co-founder and CEO of Paperspace, where we are building a cloud-based MLOps platform for machine learning teams. Prior to co-founding Paperspace, I worked in architecture and engineering, most notably looking at structural performance within large building structures. I’ve spent a significant amount of time developing genetic and evolutionary algorithms for tensile structures. My expertise is in low-level optimization problems and designing the ways we can more easily manage and interact with them. These days I spend most of my time applying that background in optimization techniques to cloud GPU pipelines and the exciting and emerging deep learning space.