Getting AI to work in a fleshy, messy world is harder than you think

At the warehouses of British online grocery company Ocado Technology, robots, guided by AI, whizz around on rails at speeds of up to four metres per second, picking a 50-item order in minutes. The journeys then taken by Ocado's delivery trucks are optimised by a neural network that makes more than 14 million last-mile routing calculations per second, and adjusts delivery routes each time a customer places a new order or adds extra items to their shopping lists. But Ocado's most ambitious automation efforts involve packing robots. At the time of writing the company has five robotic picking arms powered by computer vision, and other machine-learning systems that can identify the products that need to be packed and use suction power to grab them. Further advances, undertaken in conjunction with two European academic-led projects, are in the pipeline. "From a human's perspective, it is a fairly simple task to pick and pack, and it doesn't require an awful lot of training," says Alex Harvey, chief of advanced technology at Ocado Technology. "For a computer and for a robot, the dexterous manipulation involved is far beyond the state of the art today to be able to pick and pack the full range of items that we do."