Imagine opening your eyes and being awake for only half an hour at a time. This is the life that robots traditionally live. This is due to a number of factors, such as battery life and wear on prototype joints. Roboticists have typically muddled though this challenge by crafting handmade perception and planning models of the world, or by using machine learning with synthetic and real-world data, but cloud-based robotics aims to marry large distributed systems with machine learning techniques to understand how to build robots that interpret the world in a richer way. This movement aims to build large-scale machine learning algorithms that use experiences from large groups of people, whether sourced from a large number of tabletop robots or a large number of experiences with virtual agents. Large-scale robotics aims to change embodied AI as it changed non-embodied AI.