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Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Weak artificial intelligence (weak AI) is artificial intelligence that implements a limited part of the mind, or, as Artificial Narrow Intelligence, [1] [2] [3] is focused on one narrow task. Weak AI is contrasted with strong AI , which can be interpreted in various ways:
AI and AI ethics researchers Timnit Gebru, Emily M. Bender, Margaret Mitchell, and Angelina McMillan-Major have argued that discussion of existential risk distracts from the immediate, ongoing harms from AI taking place today, such as data theft, worker exploitation, bias, and concentration of power. [139]
A customer service representative (AI technology is already used today for telephone-based interactive voice response systems) A nursemaid for the elderly (as was reported by Pamela McCorduck in her book The Fifth Generation) A soldier; A judge; A police officer; A therapist (as was proposed by Kenneth Colby in the 70s)
The Artificial Intelligence (AI) market in India is projected to reach $8 billion by 2025, growing at a compound annual growth rate (CAGR) of over 40% from 2020 to 2025. [1] This growth is part of the broader AI boom, a global period of rapid technological advancements starting in the late 2010s and gaining prominence in the early 2020s.
Artificial narrow intelligence – AI capable only of specific tasks; Artificial general intelligence – AI with ability in several areas, and able to autonomously solve problems they were never even designed for; Artificial superintelligence – AI capable of general tasks, including scientific creativity, social skills, and general wisdom. [2]
It suggested that there were severe limitations to what perceptrons could do and that Rosenblatt's predictions had been grossly exaggerated. The effect of the book was that virtually no research was funded in connectionism for 10 years. [120] The competition for government funding ended with the victory of symbolic AI approaches over neural ...
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.