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Clothes folding robot takes us to a point where housework can be done by artificial intelligence. Can the robot take over everything? Not many of us like doing housework. Who will refuse assistance with household chores? So, it might be interesting to know that the clothes folding robot have already been created. The most famous version is the Japanese folding clothes machine, Laundroid. Another one has recently been discovered as well, with software designed by the University of California, Berkeley, and hardware by Rethink Robotics. However, don't be too excited. Robots do have an amazing level of concentration for doing tasks, but their performance is very slow. Laundroid takes four minutes to fold one outfit. What about The Rethink Robotics? Fifteen minutes. Robots might come, but not anytime soon. Meanwhile, if you need the best parts for your robots or machines, we recommend you to check out excellent parts for high torque movements.

However, the existence of this technology is an achievement. And developing a robot that can help at home doesn't mean just helping with laundry: it allows researchers to understand the core problems of artificial intelligence in general.

If they can understand the clothes-folding robot, they can apply the lesson to something more important, for example, emergency response, disaster recovery or care. This is because developing an autonomous assistant to help with domestic tasks is actually more complicated than it seems.

This is paradoxical, says Mariana Pestana, co-curator of the exhibition Future Begins Here at the London Victoria & Albert Museum, where the robot is displayed.

"The robot came out of the results of deep learning from one of the leading universities for the development of AI - but takes several minutes for things that we can do easily in seconds. All housework is constantly changing. A servant robot must be very versatile, adaptable to environmental changes, and easy to work with," said Siddharth Srivastava, a staff scientist at Berkeley who helped develop the robot.

One of the challenges facing Srivastava and his team is to make the robot understand the high-level tasks desired by its human employer. "Everyone who has worked in a team understands that an assistant is not very helpful if they need instructions for every aspect of the problem," Srivastava said.