This article from KurzweilAI is about robots learning to use tools by watching videos on the internet.

This paper presents a system that learns manipulation
action plans by processing unconstrained videos from
the World Wide Web. Its goal is to robustly generate the sequence
of atomic actions of seen longer actions in video in
order to acquire knowledge for robots. The lower level of the
system consists of two convolutional neural network (CNN)
based recognition modules, one for classifying the hand grasp
type and the other for object recognition. The higher level
is a probabilistic manipulation action grammar based parsing
module that aims at generating visual sentences for robot
manipulation. Experiments conducted on a publicly available
unconstrained video dataset show that the system is able
to learn manipulation actions by “watching” unconstrained
videos with high accuracy

Robots, pay attention – I just Googled videos on “how to clean a bathroom” and got over 33 million results, so get to work!