Tenacious robot ashamed of creator's performance, shows mankind how it's done (video)
![](https://s.yimg.com/ny/api/res/1.2/jeapEywMFgirJ_z2xRwsNw--/YXBwaWQ9aGlnaGxhbmRlcjt3PTk2MDtoPTUzMw--/https://s.yimg.com/uu/api/res/1.2/NMcZpWXaxdui7a.pSWduzw--~B/aD0zMzM7dz02MDA7YXBwaWQ9eXRhY2h5b24-/https://www.blogcdn.com/www.engadget.com/media/2011/05/robot-learning-from-failed-demonstrations-1305830196.jpg)
Looks like researchers have made another step towards taking Skynet live: giving robots the groundwork for gloating. A Swiss team of misguided geniuses have developed learning algorithms that allow robot-kind to learn from human mistakes. Earthlings guide the robot through a flawed attempt at completing a task, such as catapulting a ball into a paper basket; the machine then extrapolates its goal, what went wrong in the human-guided example, and how to succeed, via trial and error. Rather than presuming human demonstrations represent a job well done, this new algorithm assumes all human examples are failures, ultimately using their bad examples to help the 'bot one-up its creators. Thankfully, the new algorithm is only being used with a single hyper-learning appendage; heaven forbid it should ever learn how to use the robot-internet.