Using its Xbox Kinect 3D sensor, a camera, a laptop and a laser pointer, Watch-Bot observed a week's worth of human activity in a kitchen and an office. During that time, it collected 458 videos -- about half of which included someone human deliberately "forgetting" to do something. The team then made Watch-Bot analyze the videos and use its unsupervised learning algorithm to determine which human actions were intentional and which ones -- like leaving the milk out on the counter -- were accidental. Using probabilistic learning models, Watch-Bot was able to independently figure out which actions the humans were forgetting. When Watch-Bot does notice the clumsy human in the room forgot to do something, it quietly highlights that item with the laser pointer until it is put away or dealt with.