 Artificial intelligence AI sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science AI research is defined as the study of intelligent agents any device that perceives its environment and takes actions that maximise its chance of successfully achieving its goals. If alone queally, the term artificial intelligence is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem-solving. The scope of AI is disputed, as machines become increasingly capable, tasks considered as requiring intelligence are often removed from the definition, of phenomenon known as the AI effect, leading to the quit, AI is whatever hasn't been done yet. For instance, optical character recognition is frequently excluded from artificial intelligence having become a routine technology. Modern machine capabilities generally classify this AI include successfully understanding human speech, competing at the highest level in strategic game systems such as chess and go autonomously operating cars, and intelligent routing in content delivery networks and military simulations. Artificial intelligence was funded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding known as an AI winter followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These subfields are based on technical considerations, such as particular goals e.g. robotics or machine learning the use of particular tools logic or artificial neural networks for deep philosophical differences. Subfields have also been based on social factors particular institutions or the work of particular researchers. The traditional problems or goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligences among the field's long term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy and many others. The field was founded on the claim that human intelligence can be so precisely described that machine can be made to simulate it. This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Twenty others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment. In the 21st century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding, and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.