  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.
