Crowd computing utilizes both crowdsourcing and human computation to solve problems. Crowdsourcing enables more efficient and scalable data collection and processing by outsourcing tasks to a large, undefined group of people. Human computation allows software developers to incorporate human intelligence and judgment into applications to provide capabilities beyond current artificial intelligence. Examples discussed include Amazon Mechanical Turk, various crowd-powered applications, and how crowdsourcing has helped label large datasets to train machine learning models.