Alan Turing
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This document summarizes Alan Turing's seminal 1950 paper "Computing Machinery and Intelligence" which proposed what is now known as the Turing Test. The Turing Test involves an interrogator determining which of two entities, a human or computer, they are communicating with via teletyped responses. Turing argued that if a computer could successfully pass as human, it should be considered thinking. The document outlines Turing's description of the "Imitation Game" protocol and responses to philosophical counterarguments against the possibility of machine thought. It concludes by noting the impact of Turing's work on artificial intelligence and philosophy of computing.
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Alan Turing was a pioneering computer scientist who made fundamental contributions to artificial intelligence and the field of computer science. He defined the concept of an algorithm and developed the Turing machine, laying the foundations for the digital computer. During World War II, Turing worked at Britain's codebreaking center and cracked the German Enigma cipher, helping the Allies win the war. However, as a gay man in 1950s Britain, Turing was prosecuted for his homosexuality and chemically castrated, which led to his tragic death two years later at the young age of 41. Though he faced great adversity, Turing's revolutionary ideas transformed technology and shaped the modern world.
Turing
1. Alan Turing was a pioneering computer scientist who made fundamental contributions to artificial intelligence, cryptography and more.
2. During WWII, Turing worked at Bletchley Park where he helped crack German codes and is credited with shortening the war by at least two years.
3. Turing introduced the concept of a Turing machine, which formed the basis for modern computers and demonstrated that a single machine can simulate any other machine. He also proposed the Turing test for machine intelligence.
Alan turing - Life History & how he broke enigma code?
Alan Turing was a British mathematician who made pioneering contributions to computer science. During World War II, he worked at Bletchley Park cracking German codes transmitted by the Enigma machine. To help solve this problem faster than could be done by hand, Turing conceived of an electromechanical machine called the Bombe that could methodically search for potential code settings. Over 200 Bombes were built, allowing the Allies to decrypt thousands of messages per day and gain valuable intelligence. Turing's work is credited with shortening the war by as much as two years. He later did foundational work in computer science and artificial intelligence.
Alan Turing
This is an easy presentation i made for my english class about Alan Turing. I Hove this serve to anyone :D
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The Turing test, developed by Alan Turing in 1950, is a test to determine if a machine can exhibit intelligent behavior equivalent to a human. It involves a questioner interrogating both a human and computer respondent without seeing them. If the questioner cannot reliably tell which is human and which is computer, the computer is said to have passed the Turing test. Alan Turing, a mathematician, computer scientist and cryptanalyst, invented the test to explore whether a computer could convincingly converse like a human.
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Edited alan turing-presentation
Alan Turing was a pioneering computer scientist who made fundamental contributions to artificial intelligence and the field of computer science. He defined the concept of an algorithm and developed the Turing machine, laying the foundations for the digital computer. During World War II, Turing worked at Britain's codebreaking center and cracked the German Enigma cipher, helping the Allies win the war. However, as a gay man in 1950s Britain, Turing was prosecuted for his homosexuality and chemically castrated, which led to his tragic death two years later at the young age of 41. Though he faced great adversity, Turing's revolutionary ideas transformed technology and shaped the modern world.
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1. Alan Turing was a pioneering computer scientist who made fundamental contributions to artificial intelligence, cryptography and more.
2. During WWII, Turing worked at Bletchley Park where he helped crack German codes and is credited with shortening the war by at least two years.
3. Turing introduced the concept of a Turing machine, which formed the basis for modern computers and demonstrated that a single machine can simulate any other machine. He also proposed the Turing test for machine intelligence.
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Alan Turing was a British mathematician who made pioneering contributions to computer science. During World War II, he worked at Bletchley Park cracking German codes transmitted by the Enigma machine. To help solve this problem faster than could be done by hand, Turing conceived of an electromechanical machine called the Bombe that could methodically search for potential code settings. Over 200 Bombes were built, allowing the Allies to decrypt thousands of messages per day and gain valuable intelligence. Turing's work is credited with shortening the war by as much as two years. He later did foundational work in computer science and artificial intelligence.
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AnswerTuring TestCoined by computing pioneer Alan Turing in .pdf
Answer:
Turing Test:
Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a
rudimentary way of determining whether or not a computer counts as \"intelligent\".
The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a
computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the
other side. Most of those interlocutors will be humans; one will be a chatbot, created for the sole
purpose of tricking the judge into thinking that it is the real human.
Turing Test Objections:
1.The Theological Objection:
Substance dualists believe that thinking is a function of a non-material, separately existing,
substance that somehow “combines” with the body to make a person. So the argument might go
making a body can never be sufficient to guarantee the presence of thought: in themselves,
digital computers are no different from any other merely material bodies in being utterly unable
to think. Moreover to introduce the “theological” element it might be further added that, where a
“soul” is suitably combined with a body, this is always the work of the divine creator of the
universe: it is entirely up to God whether or not a particular kind of body is imbued with a
thinking soul.
2.The ‘Heads in the Sand’ Objection:
If there were thinking machines, then various consequences would follow. First, we would lose
the best reasons that we have for thinking that we are superior to everything else in the universe
(since our cherished “reason” would no longer be something that we alone possess). Second, the
possibility that we might be “supplanted” by machines would become a genuine worry: if there
were thinking machines, then very likely there would be machines that could think much better
than we can. Third, the possibility that we might be “dominated” by machines would also
become a genuine worry: if there were thinking machines, who\'s to say that they would not take
over the universe, and either enslave or exterminate us.
3.Arguments from Various Disabilities:
Turing considers a list of things that some people have claimed machines will never be able to
do:
(1) be kind.
(2) be resourceful.
(3) be beautiful.
(4) be friendly.
(5) have initiative.
(6) have a sense of humor.
(7) tell right from wrong.
(8) make mistakes.
(9) fall in love.
(10) enjoy strawberries and cream.
(11) make someone fall in love with one.
(12) learn from experience.
(13) use words properly.
(14) be the subject of one\'s own thoughts.
(15) have as much diversity of behavior as a man; (16) do something really new.
4.Argument from Continuity of the Nervous System:
The human brain and nervous system is not much like a digital computer. In particular, there are
reasons for being skeptical of the claim that the brain is a discrete-state machine. Turing observes
that a small error in the information about the size of a nervous impulse impinging on a neuron
may make a large difference to the size of the o.
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This document provides a survey of the history and philosophical foundations of artificial intelligence (AI). It discusses early ideas that anticipated AI, including the work of Aristotle, Hobbes, and Descartes. It outlines Alan Turing's seminal 1950 paper which proposed the Turing Test but stopped short of claiming machines could truly think. The document analyzes the overly ambitious goals set out in the 1955 Dartmouth proposal to simulate all aspects of intelligence with machines. It discusses subsequent progress in areas like natural language processing but notes the field's identity crisis due to its elusive goal of artificial general intelligence.
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Quantum computers use principles of quantum mechanics rather than classical binary logic. They have qubits that can represent superpositions of 0 and 1, allowing massive parallelism. Key effects like superposition, entanglement, and tunneling give them advantages over classical computers for problems like factoring and searching. Early quantum computers have been built with up to a few hundred qubits, and algorithms like Shor's show promise for cryptography applications. However, challenges remain around error correction and controlling quantum states as quantum computers scale up. D-Wave has produced commercial quantum annealing systems with over 1000 qubits, but debate continues on whether these demonstrate quantum advantage. Overall, quantum computing could transform fields like AI, simulation, and optimization if challenges around building reliable large-scale quantum
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2. It describes John Searle's Chinese room argument against the idea that running a computer program is sufficient for a machine to have a mind or understanding.
3. There is debate around whether strong AI, which claims computers could match or exceed human intelligence through algorithms, is possible or if intelligence requires aspects like consciousness that computers may lack.
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This document discusses the Turing Test, which aims to determine if a machine can exhibit intelligent behavior that is indistinguishable from a human. It explores the outcomes of passing or failing the test, and whether those outcomes are justified. While the Turing Test has its limitations and does not encompass all types of intelligence, it has still inspired significant research in artificial intelligence and assessing machine behavior. The document concludes that the Turing Test, though not perfect, still provides a useful framework for categorizing machines and furthering the field of AI.
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Quantum computing uses quantum mechanics phenomena like superposition, entanglement, and interference to perform computation. Quantum computers are improving at an exponential rate according to Neven's Law, doubling their processing power exponentially faster than classical computers. The basic unit of quantum information is the qubit, which can exist in superposition and represent a '1' and '0' simultaneously. This allows quantum computers to explore all computational paths at once, greatly increasing their processing speed over classical computers for certain problems.
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This document provides an overview of quantum computing, including its history, basic concepts, applications, advantages, difficulties, and future directions. It discusses how quantum computing originated in the 1980s with the goal of building a computer that is millions of times faster than classical computers and theoretically uses no energy. The basic concepts covered include quantum mechanics, superpositioning, qubits, quantum gates, and how quantum computers could perform calculations that are intractable on classical computers, such as factoring large numbers. The document also outlines some of the challenges facing quantum computing as well as potential future advances in the field.
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AI research is highly technical and specialised, and is deeply divided into subfields that often fail to communicate with each other.[5] Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications.
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Cognitive computing refers to the development of computer system modeled after the human brain.
This technology was introduced by IBM as 5 in 5.
In next five years IBM is planning to develop kind of Applications which will have capabilities of the right side of the human brain.
New technologies makes it possible for machines to mimic and augment the senses.
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This document discusses cognitive computing. It begins with an introduction that defines cognition and cognitive computing. Cognitive computing aims to develop systems that can think and react like the human mind through a combination of neuroscience, supercomputing, and nanotechnology. The need for cognitive computing is that today's information is challenging to manage and current search engines are limited. An example provided is IBM's Watson, the first cognitive computer, which was able to answer questions in natural language and defeat human champions on Jeopardy. The document concludes by stating that cognitive systems will help make sense of complex information and create new industries through collaboration with human reasoning.
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AnswerTuring TestCoined by computing pioneer Alan Turing in .pdf
Answer:
Turing Test:
Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a
rudimentary way of determining whether or not a computer counts as \"intelligent\".
The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a
computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the
other side. Most of those interlocutors will be humans; one will be a chatbot, created for the sole
purpose of tricking the judge into thinking that it is the real human.
Turing Test Objections:
1.The Theological Objection:
Substance dualists believe that thinking is a function of a non-material, separately existing,
substance that somehow “combines” with the body to make a person. So the argument might go
making a body can never be sufficient to guarantee the presence of thought: in themselves,
digital computers are no different from any other merely material bodies in being utterly unable
to think. Moreover to introduce the “theological” element it might be further added that, where a
“soul” is suitably combined with a body, this is always the work of the divine creator of the
universe: it is entirely up to God whether or not a particular kind of body is imbued with a
thinking soul.
2.The ‘Heads in the Sand’ Objection:
If there were thinking machines, then various consequences would follow. First, we would lose
the best reasons that we have for thinking that we are superior to everything else in the universe
(since our cherished “reason” would no longer be something that we alone possess). Second, the
possibility that we might be “supplanted” by machines would become a genuine worry: if there
were thinking machines, then very likely there would be machines that could think much better
than we can. Third, the possibility that we might be “dominated” by machines would also
become a genuine worry: if there were thinking machines, who\'s to say that they would not take
over the universe, and either enslave or exterminate us.
3.Arguments from Various Disabilities:
Turing considers a list of things that some people have claimed machines will never be able to
do:
(1) be kind.
(2) be resourceful.
(3) be beautiful.
(4) be friendly.
(5) have initiative.
(6) have a sense of humor.
(7) tell right from wrong.
(8) make mistakes.
(9) fall in love.
(10) enjoy strawberries and cream.
(11) make someone fall in love with one.
(12) learn from experience.
(13) use words properly.
(14) be the subject of one\'s own thoughts.
(15) have as much diversity of behavior as a man; (16) do something really new.
4.Argument from Continuity of the Nervous System:
The human brain and nervous system is not much like a digital computer. In particular, there are
reasons for being skeptical of the claim that the brain is a discrete-state machine. Turing observes
that a small error in the information about the size of a nervous impulse impinging on a neuron
may make a large difference to the size of the o.
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This document provides a survey of the history and philosophical foundations of artificial intelligence (AI). It discusses early ideas that anticipated AI, including the work of Aristotle, Hobbes, and Descartes. It outlines Alan Turing's seminal 1950 paper which proposed the Turing Test but stopped short of claiming machines could truly think. The document analyzes the overly ambitious goals set out in the 1955 Dartmouth proposal to simulate all aspects of intelligence with machines. It discusses subsequent progress in areas like natural language processing but notes the field's identity crisis due to its elusive goal of artificial general intelligence.
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Mary Shelley, Frankenstein, or The Modern Prometheus, 1818
Boris Karloff in Frankenstein in 1931 directed by James Whale
Mary Shelley first published Frankenstein, or the Modern Prometheus 1818. the novel allegorizes the Romantic obsession with discovering the power or principle of life. Ideas about a life power were consistent with the scientific understanding of the day. Darwin himself spoke of an organizing “spirit of animation” in his Zoonomia; or, The Laws of Organic Life, in which he stated “the world itself might have been generated, rather than created.”
Dr. Frankenstein picked all the parts for his monster based on their beauty, but when it comes to life, the monster is unbearably ugly. “I had worked hard for nearly two years, for the sole purpose of infusing life into an inanimate body…the beauty of the dream vanished, and breathless horror and disgust filled my heart. Unable to endure the aspect of the being I had created, I rushed out of the room”.
4
Two definitions of AI:
“The use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular.
--Margaret Boden
“The science of making machines do things that would require intelligence if done by humans.”
-Marvin Minsky
BOTH OF THESE STATEMENTS ORIGINATE IN ALAN TURING’S FIRST COMPUTER SCIENCE ARTICLE
Working assumption: all cognition is computable
Question:
Is what’s not yet known to be computable actually computable?
if so, then what?
if not, why not, and what does that tell us about cognition?
7
Who was Alan Turing?
B. 1912 London, attended King’s College, Cambridge and Princeton University. He studied mathematics and logic (he hadn’t invented computer science yet)
At 23, he invented the “Turing machine” and published “On Computable Numbers in 1936, the first and most important paper in comp. sci.
During WWII, solved the German Enigma code by use of electromechanical devices—a precursor to the computer
Laid the foundation for major subfields of comp sci: theory of computation, design of hardware and software, and the study of artificial intelligence
“The Imitation Game,”
aka
“The Turing Test”
In 1950, Turing posited a way to test machine intelligence: a person in a room before a screen. S/he would correspond with two agents and based on their responses, decide which was a machine and which was human. If the machine can pass fo.
Artificial Intelligence
The document discusses perspectives on artificial intelligence (AI), defined as the intelligence exhibited by machines or software. It outlines different approaches to creating AI, including cybernetics, brain simulation, traditional symbolic AI, sub-symbolic AI, and statistical AI. The document also discusses evaluating AI systems using Turing's test and potential applications of AI in fields like medicine, finance, robotics, law, science, games and toys.
Unit 1 ppt.pptx
- Sensors that allow the system to perceive its environment
- Actuators that allow the system to act on or change its environment
- An ability to reason and make rational decisions or plans of action based on its perceptions
The document discusses sensors and actuators in the context of intelligent agents - for humans, examples of sensors are eyes and ears, while actuators are hands, legs, and mouth. For robots, examples of sensors would be cameras and other input devices, while actuators would allow the robot to move or manipulate objects.
ALAN TURING MACHINE.pptx
Alan Turing proposed the Turing Test in 1950 to test a machine's ability to exhibit intelligent behavior indistinguishable from a human. The Turing Test involves an interrogator asking questions to both a human and a computer without seeing them. If the interrogator cannot discern which is human and which is computer, the computer is said to have passed the test. Several chatbots like ELIZA, Parry, and Eugene Goostman have attempted the Turing Test, with Eugene Goostman convincing 29% of judges it was human. However, philosophers like John Searle argue that passing the Turing Test does not prove a machine has human understanding through his Chinese Room Argument.
Lecture 1
This document provides an overview of an introduction to artificial intelligence course, including:
- Course details such as the textbook, grading breakdown, and schedule
- Definitions and types of artificial intelligence including rational agents, the Turing test, and different branches of AI
- A brief history of ideas influencing AI such as philosophy, mathematics, psychology, and agents
- Examples of AI applications and challenges including ethics
AI.doc
The document discusses the history and challenges of developing artificial general intelligence (AGI). It argues that while no AGI currently exists, continued advances in computer technology and approaches like functionalism make AGI an eventual possibility rather than just fiction. Key challenges discussed include the limitations of symbol systems and rule-based approaches for developing broad, flexible intelligence.
Artificial intelligence
This document provides an overview of the history and use of artificial intelligence on computer systems. It discusses:
1) The origins of AI research beginning in the 1940s and 1950s with pioneers like Alan Turing and the first conference on AI at Dartmouth College in 1956.
2) The development of AI through boom periods in the 1960s with significant government funding, and bust periods in the 1970s and 1980s due to limitations and funding cuts.
3) Recent advances in AI from the 1990s to present using techniques like deep learning, access to large datasets, and increasing computational power which have led to applications in areas like logistics, data mining, and medical diagnosis.
The Mind as the Software of the Brain by Ned Block httpww.docx
"The Mind as the Software of the Brain" by Ned Block http://www.nyu.edu/gsas/dept/philo/faculty/block/papers/msb.html
1 of 34 20/04/2004 16.04
The Mind as the Software of the Brain
Ned Block
New York University
1. Machine Intelligence
2. Intelligence and Intentionality
3. Functionalism and the Language of Thought
4. Searle's Chinese Room Argument
Cognitive scientists often say that the mind is the software of the brain. This chapter is about what this
claim means.
1. Machine Intelligence
In this section, we will start with an influential attempt to define `intelligence', and then we will move to a
consideration of how human intelligence is to be investigated on the machine model. The last part of the
section will discuss the relation between the mental and the biological.
1.1 The Turing Test
One approach to the mind has been to avoid its mysteries by simply defining the mental in terms of the
behavioral. This approach has been popular among thinkers who fear that acknowledging mental states
that do not reduce to behavior would make psychology unscientific, because unreduced mental states are
not intersubjectively accessible in the manner of the entities of the hard sciences. "Behaviorism", as the
attempt to reduce the mental to the behavioral is called, has often been regarded as refuted, but it
periodically reappears in new forms.
Behaviorists don't define the mental in terms of just plain behavior, since after all something can be
intelligent even if it has never had the chance to exhibit its intelligence. Behaviorists define the mental not
in terms of behavior, but rather behavioral dispositions, the tendency to emit certain behaviors given
certain stimuli. It is important that the stimuli and the behavior be specified non-mentalistically. Thus,
intelligence could not be defined in terms of the disposition to give sensible responses to questions, since
that would be to define a mental notion in terms of another mental notion (indeed, a closely related one).
To see the difficulty of behavioristic analyses, one has to appreciate how mentalistic our ordinary
behavioral descriptions are. Consider, for example, throwing. A series of motions that constitute throwing
if produced by one mental cause might be a dance to get the ants off if produced by another.
An especially influential behaviorist definition of intelligence was put forward by A. M. Turing (1950).
Turing, one of the mathematicians who cracked the German code during World War II, formulated the
idea of the universal Turing machine, which contains, in mathematical form, the essence of the
"The Mind as the Software of the Brain" by Ned Block http://www.nyu.edu/gsas/dept/philo/faculty/block/papers/msb.html
2 of 34 20/04/2004 16.04
programmable digital computer. Turing wanted to define intelligence in a way that applied to both men
and machines, and indeed, to anything that is intelligent. His version of behaviorism formulates the issue
of wh.
Artificial Intelligence can machine think
Technology, innovation, and artificial intelligence have advanced drastically in the past few decades. According to one philosopher, Lady Lovelace, she argued that, A computer cannot "originate anything" but only "can do whatever we know how to order it to perform". But Allan Turing proved that his "universal computing machine" would be capable of performing any conceivable mathematical computation if it were representable as an algorithm. I will argue that an action made by an artefact does not only depend on the order made by its human designer rather an artefact is capable of learning.
SOME INSIGHTS FROM ALAN TURING’S ARTIFICIAL COGNITION RESEARCH
- Alan Turing is known for his work on computability and cryptography during WWII. In later years, he became interested in artificial intelligence and modeling biological processes.
- In 1948, he wrote an unpublished article called "Intelligent Machinery" where he outlined challenges for machine intelligence and proposed a new type of Turing machine (TM48) that could learn from experience and sensory input.
- He regularly met with British cyberneticists through the Ratio Club to discuss topics like self-organization. This influenced his work toward understanding cognition through biological and organic forms rather than just functional abstraction.
- His 1952 article on morphogenesis used mathematical models to explain how complex biological patterns and forms can emerge from simple local interactions,
Introduction to AI
This document provides an overview of approaches to artificial intelligence including acting humanly through the Turing test, thinking humanly through cognitive modeling, thinking rationally through Aristotelian logic and syllogisms, and acting rationally as autonomous agents. It defines AI as "the science and engineering of making intelligent machines" and notes key characteristics include natural language processing, knowledge representation, automated reasoning, machine learning, computer vision, and robotics.
The IOT Academy Training for Artificial Intelligence ( AI)
This document provides an overview of artificial intelligence (AI). It begins with definitions of AI as modeling human thinking and acting rationally. The history of AI is then summarized, including early developments in neural networks in the 1940s and the 1956 Dartmouth conference that coined the term "artificial intelligence." Real-world applications of AI are mentioned such as autonomous vehicles and IBM's Watson. The document concludes by outlining the objectives of an introductory AI course.
SOME INSIGHTS FROM ALAN TURING’S ARTIFICIAL COGNITION RESEARCH
- Alan Turing's early work focused on mathematical logic and computability, while his later work examined the chemical basis of morphogenesis. This article argues that Turing's desire to develop "artificial cognition" and his involvement with the cybernetics-focused Ratio Club connected his two periods of research.
- After WWII, Turing worked to develop machines capable of human-like reasoning. His 1948 article "Intelligent Machinery" introduced concepts like organized vs. unorganized machinery and open vs. closed problems to address limitations of early computing machines.
- Turing's interactions with the Ratio Club exposed him to biological conceptions of self-organization and pattern formation, shifting his focus to understanding natural cognition through modeling
Artificial Intelligence (short introduction)
Artificial intelligence (AI) is the intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. It is defined as the ability of machines to understand, think, and learn. The document traces the history of AI from Alan Turing's 1950 Turing Test to evaluate machine intelligence to John McCarthy coining the term "artificial intelligence" in 1955. It also categorizes AI into artificial narrow intelligence focused on specific problems, artificial general intelligence aimed at general problem-solving like humans, and artificial super intelligence exceeding human level abilities.
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