Machine learning's own Industrial Revolution
This addresses the problem of scaling ML for enterprise demands and broad industries, but it is incremental as it builds on existing discussions about ML industrialization.
The paper argues that machine learning must undergo its own Industrial Revolution to address challenges in standardization and automation, aiming to enable rapid translation from innovation to mass production and utilization.
Machine learning is expected to enable the next Industrial Revolution. However, lacking standardized and automated assembly networks, ML faces significant challenges to meet ever-growing enterprise demands and empower broad industries. In the Perspective, we argue that ML needs to first complete its own Industrial Revolution, elaborate on how to best achieve its goals, and discuss new opportunities to enable rapid translation from ML's innovation frontier to mass production and utilization.