Amazon’s one-million-square-foot distribution center in Baltimore is a massive fulfillment machine. Stand at one end of the warehouse, and its titanium-white scaffolding and seemingly endless conveyor belts disappear at a vanishing point that is, somehow, within the building. The machine is a dazzling combination of chutes, ladders, rollers and 11 miles’ worth of conveyor belts. Customers’ orders move from shelving into bins and from bins into boxes as they travel via the machine straight into delivery vans, passing by stationary workers at various points along the way. Humans are rarely required to move around here. It’s much faster, and cheaper, to have stuff brought to them.
Amazon’s robots signal a sea change in how the things we buy will be aggregated, stored and delivered. The company requires one minute of human labor to get a package onto a truck, but that number is headed to zero. Autonomous warehouses will merge with autonomous manufacturing and delivery to form a fully automated supply chain.
We are in the early days of what might be called the “physical cloud,” an e-commerce ecosystem that functions like the internet itself. Netflix caches the movies you stream at a data center physically close to you; Amazon is building warehouse after warehouse to store goods closer to consumers. And the storage systems at those warehouses are looking more like the data-storage systems in the cloud. Instead of storing similar items in the same place—a helpful practice when humans were fetching the goods—Amazon’s warehouses store multiples of the same item at random locations, known only to the robots. Trying to find an Instapot at one of Amazon’s warehouses would be like trying to find where in the cloud one of your emails is stored. Of course, you don’t have to. You just tap your screen and the email appears. No humans are involved.
The same will someday be true of the things we buy.
Thanks to retail’s low margins and the high cost of robots, warehousing has been slow to embrace automation, lagging behind industries like farming and car manufacturing. That changed when Kiva Systems, founded in 2003 in Reading, Mass., developed robots that could bring items to workers. At one point, Kiva’s clients included Gap, Saks Fifth Avenue and Staples. Then in 2012, Amazon bought Kiva for $775 million, took Kiva’s robots off the market and made them the backbone of its distribution centers. According to Deutsche Bank, acquiring Kiva reduced Amazon’s fulfillment costs by 20%, and it blew an enormous hole in the plans of its competitors. Because of patents and the difficulty of recreating Kiva’s deep well of expertise, new robotics companies weren’t able to offer comparable systems until the past couple of years.
Christopher Atkeson, a robotics professor at Carnegie Mellon, says a robotic arm capable of replacing Amazon’s warehouse workers will be available within five years.
Amazon is coy about its long-term plans. Tye Brady, the chief technologist for Amazon Robotics, says only that the company is always seeking to make its employees more efficient. Other retailers are more blunt. Richard Liu, the CEO and chairman of JD.com, a leading e-commerce company in China that relies heavily on automation, has said his goal is a 100% robot workforce.
A fully automated warehouse is just the beginning. Amazon and Walmart have patented blimplike warehouses that will float 1,000 feet in the air, armed with drones ready to deliver toothpaste and toilet paper to your doorstep as if they were files. Welcome to the physical cloud.
Beneath the grid are the groceries, stacked in bins 18 layers deep. After a customer places an order for, say, a gallon of milk, an Ocado robot comes to the appropriate square and reaches its arms downward to grab a bin containing milk. Then the robot sucks the bin into its belly and carries it to a conveyor belt, which conveys the milk to workers, who have the dexterity to grab the individual carton and pack it into a bag. Although neither Amazon nor Ocado has robots that can pack items efficiently, Ocado’s robots can autonomously move items from storage onto conveyor belts.
More impressive than the robots is the software behind them. Ocado’s system requires an AI of unholy complexity. The AI is trying to optimize every aspect of Ocado’s fulfillment: where to store its tens of thousands of items, which of those should be packed first and into which bags, which items should go on which trucks, which delivery route to take so that ice cream doesn’t melt on the way. The optimal solutions for different factors don’t always agree with one another: The fastest way to load a truck may not be the most efficient use of its space. As a result, adding just one more variable to the system increases the difficulty exponentially. And Ocado is optimizing for millions of variables.