26 Facts About AI


AI research has been defined as the field of study of intelligent agents, which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its goals.

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Various sub-fields of AI research are centered around particular goals and the use of particular tools.

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The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects.

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The first work that is generally recognized as AI was McCullouch and Pitts' 1943 formal design for Turing-complete "artificial neurons".

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Field of AI research was born at a workshop at Dartmouth College in 1956.

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However, beginning with the collapse of the Lisp Machine market in 1987, AI fell into disrepute, and a second, longer-lasting winter began.

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Robotics researchers, such as Rodney Brooks, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move, survive, and learn their environment.

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AI gradually restored its reputation in the late 1990s and early 21st century by finding specific solutions to specific problems.

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Much of current research involves statistical AI, which is overwhelmingly used to solve specific problems, even highly successful techniques such as deep learning.

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Symbolic AI used formal syntax to translate the deep structure of sentences into logic.

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Many problems in AI can be solved theoretically by intelligently searching through many possible solutions: Reasoning can be reduced to performing a search.

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AI researchers have devised a number of tools to solve these problems using methods from probability theory and economics.

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AI is used in search engines, targeting online advertisements, recommendation systems, driving internet traffic, targeted advertising, virtual assistants, autonomous vehicles, automatic language translation, facial recognition, image labeling and spam filtering.

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In 2019, WIPO reported that AI was the most prolific emerging technology in terms of number of patent applications and granted patents, the Internet of things was estimated to be the largest in terms of market size.

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Since AI emerged in the 1950s, 340,000 AI-related patent applications were filed by innovators and 1.

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Machine learning is the dominant AI technique disclosed in patents and is included in more than one-third of all identified inventions, with computer vision being the most popular functional application.

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AI-related patents not only disclose AI techniques and applications, they often refer to an application field or industry.

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AI devised the Turing test, which measures the ability of a machine to simulate human conversation.

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AI researchers are divided as to whether to pursue the goals of artificial general intelligence and superintelligence directly or to solve as many specific problems as possible in hopes these solutions will lead indirectly to the field's long-term goalsGeneral intelligence is difficult to define and difficult to measure, and modern AI has had more verifiable successes by focussing on specific problems with specific solutions.

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Machine-learning AI is able to design tens of thousands of toxic molecules in a matter of hours.

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AI concludes that AI poses a risk to mankind, however humble or "friendly" its stated goals might be.

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Friendly AI are machines that have been designed from the beginning to minimize risks and to make choices that benefit humans.

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The regulatory and policy landscape for AI is an emerging issue in jurisdictions globally.

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The Global Partnership on Artificial Intelligence was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology.

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Similarly, Russia can use AI to help analyze battlefield data from surveillance footage taken by drones.

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In radiology imaging, AI uses deep learning algorithms to identify potentially cancerous lesions which is an important process assisting in early diagnosis.

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