Deep reinforcement learning will transform manufacturing as we know it

If you walk down the street shouting out the names of every object you see — garbage truck! bicyclist! sycamore tree! — most people would not conclude you are smart. But if you go through an obstacle course, and you show them how to navigate a series of challenges to get to the end unscathed, they would.

Most machine learning algorithms are shouting names in the street. They perform perceptive tasks that a person can do in under a second. But another kind of AI — deep reinforcement learning — is strategic. It learns how to take a series of actions in order to reach a goal. That’s powerful and smart — and it’s going to change a lot of industries.

Two industries on the cusp of AI transformations are manufacturing and supply chain. The ways we make and ship stuff are heavily dependent on groups of machines working together, and the efficiency and resiliency of those machines are the foundation of our economy and society. Without them, we can’t buy the basics we need to live and work.

Startups like Covariant, Ocado’s Kindred and Bright Machines are using machine learning and reinforcement learning to change how machines are controlled in factories and warehouses, solving inordinately difficult challenges such as getting robots to detect and pick up objects of various sizes and shapes out of bins, among others. They are attacking enormous markets: The industrial control and automation market was worth $152 billion last year, while logistics automation was valued at more than $50 billion.

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