Author: Magda

31 Mar These algorithms help make the system adaptable

Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn't take jobs

Meanwhile, Kiva itself is hiring. Orange balloons-the same color as the robots-hover over multiple cubicles in its sprawling office, signaling that the occupants arrived https://besthookupwebsites.org/gaydar-review/ within the last month. Most of these new employees are software engineers: while the robots are the company's poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots' movements and determine where in the warehouse products are stored. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.

Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks-for example, packaging various items together. Many of the traditional problems in robotics-such as how to teach a machine to recognize an object as, say, a chair-remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.

Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain.