This insight, that digital computers can simulate any process of formal reasoning, is known as the Church–Turing thesis.
Along with concurrent discoveries in neurobiology, information theory and cybernetics, this led researchers to consider the possibility of building an electronic brain.
The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields.
The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it".
Turing proposed that "if a human could not distinguish between responses from a machine and a human, the machine could be considered "intelligent".
AI's founders were optimistic about the future: Herbert Simon predicted, "machines will be capable, within twenty years, of doing any work a man can do".
By 1985, the market for AI had reached over a billion dollars.
At the same time, Japan's fifth generation computer project inspired the U.
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.