This raised philosophical arguments about the mind and the ethical consequences of creating artificial beings endowed with human-like intelligence these issues have previously been explored by myth, fiction and philosophy since antiquity. The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it". AI also draws upon computer science, psychology, linguistics, philosophy, and many other fields. To solve these problems, AI researchers have adapted and integrated a wide range of problem-solving techniques – including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability and economics. General intelligence (the ability to solve an arbitrary problem) is among the field's long-term goals. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects. The various sub-fields of AI research are centered around particular goals and the use of particular tools. In the first decades of the 21st century, highly mathematical-statistical machine learning has dominated the field, and this technique has proved highly successful, helping to solve many challenging problems throughout industry and academia. AI research has tried and discarded many different approaches since its founding, including simulating the brain, modeling human problem solving, formal logic, large databases of knowledge and imitating animal behavior. Īrtificial intelligence was founded 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 instance, optical character recognition is frequently excluded from things considered to be AI, having become a routine technology. Īs machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs.ĪI applications include advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). Artificial intelligence ( AI) is intelligence-perceiving, synthesizing, and inferring information-demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans.
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