Turing Test
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The document discusses Alan Turing and the Turing Test. It provides details on: - Alan Turing created the Turing Test in the 1950s to determine if a computer can exhibit intelligent behavior equivalent to a human. - The Turing Test involves an interrogator asking questions to both a human and computer to determine which is which based on their responses. - In 2014, a computer program passed the Turing Test by convincing 33% of judges that it was a human during conversations, marking the first successful passing of the test.
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Turing test
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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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.
Turing Test in Artificial Intelligence.pptx
In this Powerpoint Presentation, I gave presentation on Turing Test, Alan Turing and Immitation Test.
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.
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Machine learning helps predict behavior and recognize patterns that humans cannot by learning from data without relying on programmed rules. It is an algorithmic approach that differs from statistical modeling which formalizes relationships through mathematical equations. Machine learning is a part of the broader field of artificial intelligence which aims to develop systems that can act and respond intelligently like humans. The machine learning workflow involves collecting and preprocessing data, selecting algorithms, training models, and evaluating performance. Common machine learning algorithms include supervised learning, unsupervised learning, reinforcement learning, and deep learning. Popular tools for machine learning include Python, R, TensorFlow, and Spark.
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The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills.
Those who complete the course will be able to:
1. Master the concepts of supervised and unsupervised learning
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3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
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Turing test
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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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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In this Powerpoint Presentation, I gave presentation on Turing Test, Alan Turing and Immitation Test.
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.
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Machine learning helps predict behavior and recognize patterns that humans cannot by learning from data without relying on programmed rules. It is an algorithmic approach that differs from statistical modeling which formalizes relationships through mathematical equations. Machine learning is a part of the broader field of artificial intelligence which aims to develop systems that can act and respond intelligently like humans. The machine learning workflow involves collecting and preprocessing data, selecting algorithms, training models, and evaluating performance. Common machine learning algorithms include supervised learning, unsupervised learning, reinforcement learning, and deep learning. Popular tools for machine learning include Python, R, TensorFlow, and Spark.
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1. What is Artificial intelligence?
2. Types of Artificial intelligence
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Those who complete the course will be able to:
1. Master the concepts of supervised and unsupervised learning
2. Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, Naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
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Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
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Decision Making
Solve Problems
Feelings(Love,Happy,Angry)
Understand
Apply logic
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making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
Robots are autonomous or semi-autonomous machines meaning that they can act independently of external commands. Artificial intelligence is software that learns and self-improves.
Why Artificial Intelligence?
• Computers can do computations, by fixed programmed rules
• A.I machines perform tedious tasks efficiently & reliably.
• computers can’t understanding & adapting to new situations.
• A.I aims to improve machine to do such complex tasks.
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Error Reduction
Difficult Exploration(mining & exploration processes)
Daily Application(Siri, Cortana)
Digital Assistants(interact with users)
Medical Applications(Radiosurgery)
Repetitive Jobs(monotonous)
No Breaks
Some disadvantages of A.I:
High Cost
Unemployment
Weaponization
No Replicating Humans
No Original Creativity
No Improvement with Experience
Safety/Privacy Issues
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Introduction to Big Data
What is Text Mining?
What is NLP?
Introduction to Stemming
Introduction to Lemmatization
Applications of Stemming & Lemmatization
Difference between stemming & Lemmatization
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
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Human intelligence is the intellectual powers of humans, Learning
Decision Making
Solve Problems
Feelings(Love,Happy,Angry)
Understand
Apply logic
Experience
making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
Robots are autonomous or semi-autonomous machines meaning that they can act independently of external commands. Artificial intelligence is software that learns and self-improves.
Why Artificial Intelligence?
• Computers can do computations, by fixed programmed rules
• A.I machines perform tedious tasks efficiently & reliably.
• computers can’t understanding & adapting to new situations.
• A.I aims to improve machine to do such complex tasks.
Advantages of A.I:
Error Reduction
Difficult Exploration(mining & exploration processes)
Daily Application(Siri, Cortana)
Digital Assistants(interact with users)
Medical Applications(Radiosurgery)
Repetitive Jobs(monotonous)
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High Cost
Unemployment
Weaponization
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Safety/Privacy Issues
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What is artificial intelligence?
What are its uses?
advantages?
disadvantages?
Charasteristics?
examples?
functions
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Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans
2.17Mb ppt
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AI Artificial Intelligence1Reading responsePeter .docx
AI: Artificial Intelligence
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Reading response
Peter Dormer, “Craft and the Turing Test for Practical Thinking,” in The Challenge of Technology.
What is personal know-how? What is distributed knowledge?
How do they relate to the Turing test?
Give one example of your own how these concepts matter today to artists and makers, or better yet, in your own experience?
Journal homework
Keep a record (text and drawings) of events in daily life where human and machine intersect and interact. Fill at least two pages with your observations.
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?
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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.
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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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Ai
Artificial intelligence is a branch of computer science that aims to build machines that can think and act intelligently like humans. The document traces the history of AI from its origins in classical philosophy to modern applications in areas like games, speech recognition, music, healthcare, the military, finance, customer service, and transportation. It also discusses key differences between artificial and natural intelligence and considers both the advantages and disadvantages of AI as well as its potential future impacts.
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Artificial intelligence (AI) refers to machines that can mimic human intelligence and behavior. There are two main tests for AI - the Turing test, which evaluates if a machine can have an intelligent conversation indistinguishable from a human, and the imitation game, which compares a machine's abilities to a human's. Examples of current AI include conversational agents, autonomous vehicles, drones, and IBM's Watson. While AI is advancing, it also faces challenges like potentially replacing human jobs, increasing laziness, and cost issues. As AI becomes more prevalent, it is important to understand how it works and how it may impact daily life.
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Alan Turing was a pioneering British mathematician and logician in the early 20th century. He made fundamental contributions to mathematics, cryptanalysis, logic, philosophy, and computer science. He invented the concept of a universal machine and laid the foundations for modern computing by conceptualizing programmable, general-purpose computers. During World War II, Turing worked at Bletchley Park where he played a pivotal role in cracking the German Enigma codes, which accelerated the Allied victory. Despite his achievements, Turing was prosecuted for homosexuality and died in 1954 at the age of 41. He is now widely considered one of the most influential scientists in history.
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
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and machines, and indeed, to anything that is intelligent. His version of behaviorism formulates the issue
of wh.
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Turing Test
- 1. By: Maisha, Kris, Rogerio, Engo
- 2. Alan Turing Created the Turing Test in the 1950’s; British mathematician; Predicted by year 2000 the average interrogator would not be able to distinguish between machine or human after five mins of questioning.
- 3. Turing test Turing test artificial intelligence Determines whether a computer can “think.” Turing proposed the imitation game so it does not reject machine intelligence.
- 4. How does the Turing test work Remote human interrogator Must distinguish between a computer and a human Based on their replies to various questions Success at “thinking” can be measured by its probability of being misidentified as the human subject.
- 5. How to pass the test The 65-year-old Turing Test is successfully passed if a computer is mistaken for a human more than 30% of the time during a series of five-minute keyboard conversations.
- 6. University of reading competition In 2014 a computer program simulating a 13-years-old Ukrainian boy, passed the Turing Test. The Computer program convinced 33% of the judges that is was a human. The program was created by Vladimir Veselov from Russia and Eugene Demchenko from Ukraine.
- 7. http://www.theguardian.com/technology/2014/jun/09/what-is-the-alan- turing-test http://www.bbc.co.uk/news/technology-27762088 http://www.bbc.com/future/story/20150724-the-problem-with-the-turing-test http://www.turing.org.uk/publications/testbook.html https://www.cl.cam.ac.uk/projects/raspberrypi/tutorials/turing- machine/one.html http://www.britannica.com/technology/Turing-test 2014 University of Reading competition: Prof Noel Sharkey (2012) BBC Technology [online]. Bbc.co.uk, Available from: http://www.bbc.co.uk/news/technology-18475646, accessed on: 03/03/2016 References