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Intelligence amplification (IA) (also referred to as cognitive augmentation, machine augmented intelligence and enhanced intelligence) is the use of information technology in augmenting human intelligence. The idea was first proposed in the 1950s and 1960s by cybernetics and early computer pioneers.
They define five levels of AGI: emerging, competent, expert, virtuoso, and superhuman. For example, a competent AGI is defined as an AI that outperforms 50% of skilled adults in a wide range of non-physical tasks, and a superhuman AGI (i.e. an artificial superintelligence) is similarly defined but with a threshold of 100%.
Artificial Intelligence Markup Language (AIML) [11] is an XML dialect [12] for use with Artificial Linguistic Internet Computer Entity (A.L.I.C.E.)-type chatterbots. Planner is a hybrid between procedural and logical languages. It gives a procedural interpretation to logical sentences where implications are interpreted with pattern-directed ...
Artificial intelligence (AI) refers to the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making.
The word intelligence derives from the Latin nouns intelligentia or intellēctus, which in turn stem from the verb intelligere, to comprehend or perceive.In the Middle Ages, the word intellectus became the scholarly technical term for understanding and a translation for the Greek philosophical term nous.
Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion.
John Searle contests the possibility of strong AI (by which he means conscious AI). He further believes that the Turing test (created by Alan Turing and originally called the "imitation game", used to assess whether a machine can converse indistinguishably from a human) is not accurate or appropriate for testing whether an AI is "strong".
Yudkowsky, E. (2008). Artificial Intelligence as a Positive and Negative Factor in Global Risk. In Global Catastrophic Risks, Oxford University Press. Discusses Artificial Intelligence from the perspective of Existential risk. In particular, Sections 1-4 give background to the definition of Friendly AI in Section 5.