Old industries, sexy data: How machine learning is reshaping the world's backbone industries

Over the past decade, machine learning has become intertwined with newer, Internet-born businesses. This despite the fact that the vast majority of global GDP turns on larger, less visible industries like energy and construction. David Beyer explores the ways these backbone industries are adopting machine-intelligent applications and the trends underlying this shift.

Machine-learning techniques and products are quietly powering a small renaissance in intelligent automation and applications for enterprises that constitute the vast, but often less visible, economy all around us. From drones that automate construction equipment in real time to sensors that can optimize harvests, the industries that in aggregate constitute the lion’s share of global GDP are waking up to the promise of intelligent automation and context. This transformation is driven by a constellation of interrelated trends, from foundational improvements in computing to the accelerating proliferation of sensor nodes and mobile devices. And while the underlying silicon may be the same, the adoption of machine learning as a practice varies by industry in interesting ways. David Beyer introduces some of the key trends of significance to the adoption of machine learning at the enterprise level, as well as the unique paths taken by some of the world’s largest industries (e.g., healthcare, agriculture, and energy) as they incorporate these new techniques to optimize current practices and explore previously impossible ones.