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1912-2012 : “100 years of Genius”
Salient Points of the Presentation
 A Brief History of Turing’s Life
 Turing’s Contributions to Computer Science
 Turing Machine
 Turing Test
 Turing Completeness(Programming Language)
 ACE (Automated Computing Engine)
 AI (Artificial Intelligence)
 Artificial Life
 Halting Problem
After the War he     On his return       He met his
                     During WWII, he                                                demise on:
    Alan Mathias       worked at The
                                             reformulated     from the U.S,he
  Turing: Born 23 Government Code          Hilbert’s decision     joined the          7 June
 June 1912,Maida & Cipher School at       problem and gave         National        1954 (aged 4
   Vale, London, Bletchley Park as a      his own hypothesis       Physical              1)
  England, United      Cryptanalyst.      which is now know Laboratory, in          Wilmslow
Kingdom. But was Where he invented           as the Halting                         Cheshire,
                                                                 Manchester,
    conceived in       the bombe to                                                  England,
                                                Problem            where he           United
Chatrapur Odisha, crack the German
 his father worked codes. He was             There after,he    developed the        Kingdom,
for the Indian Civil placed in Hut – 8,      worked under        Automated
                                                                                      Cause of
     Sevices.He         the division       Alonso Church at      Computing             death
      attended        responsible for     Princeton and gave Engine(ACE),wh         according to
 Sherbone School Intercepting and         the Church-Turing         ich is a       the reports is
          in
 Dorset,thereafter
                        breaking the       hypothesis which primitive type            cyanide
                          German             gives a formal     of Computer.         poisoning.
 enrolled in Kings codes.According to                          Thereafter, he
College and where some estimates his          definition of                          This marks
                                           “Turing Machine”        became          the end of an
 he passed with a work reduced the
First Class honours war time in the                            interested in a      era and the
  in Mathematics Atlantic by at least                           subject called      beginning of
                                                               “Artificial Life”   a revolution.
                         two years.
   A wartime hero in all respects, as he was instrumental in the defeat of the Germans in the
    Atlantic.
   Popularly known as Father of Computer Science, indeed true in all respects.
   His turing machine formed the basis of the Modern Computer.
   His reformulation of the Halting Problem,which was first introduced by Hilbert as the
    “Entscheidungsproblem", later led to a set of problems known as NP complete.
   The Turing Test served as the benchmark for recognizing an intelligent machine, this was
    published in his 1936 paper, where he rigorously debated on the topic-”Can Machines
    think”.
   This paper set the ball rolling for the development of Artificial Intelligence and Machine
    Learning.
   Turing Complete- A term associated with programming languages provides the measure of
    computing power of any given language.
   He himself envisioned Computers one day beating Grandmasters at Chess.(which is today a
    reality).
   His contributions to Speech Cryptography is lesser known albeit he developed “Delilah” at
    Bell Labs.
   In his last years he was deeply interested in mathematical biology, especially finding patterns
    in Chemical Morphogenesis.
   Hence to sum it all up, his contribution to the development of Computer Science was akin to
    that of the fire and wheel in the progress and survival of the human race.
 The Turing Machine which I call the “simple wonder”,
consists of a tape with symbols etched on them, and a head
which is restricted to move only forward and backward,
reading the symbols and performing necessary actions
according to a table of rules.
 The most simple Turing machine can be approximated to
a DFA(Deterministic Finite Automata).The following example
will illustrate the same.                                    1/0
                           0
                                           1




              Start State                                Final State
 A turing machine consists of a tape which is divided into cells,each cell has
an alphabet etched on it or it might be left blank, the alphabet can belong to
any “Formal Language” or a Regular Expression.”
 A head which is capable of movement in the left and right directions and it
reads the symbols which are written on the tape.
 A State Register which stores the state of the of the machine.
 Then there is an action table, which stores the actions to be performed on
encountering a specific symbol or state.
 Thus a complete turing machine can be thought of as a tuple of the
following:

                  { Q , ∑ , δ , q0 , F }
Where:
Q : Finite Set of States
∑ : Finite Set of Input Symbols
δ : Transition State a function of f(Q,sigma)
q0 : The initial state or the start state
F : Final State or the Accept State.
The Universal Turing Machine: A
turing Machine which can mimic
any other turing machine is
known as the Universal Turing
Machine. In simple words it can
solve any problem which is posed
to it.
The Turing Oracle: It is a turing
Machine, which has an infinite
amount of tape length. Its is used
to solve decision problems,
though it fails in the halting
problem.
Can Machines Think???....
 That was the same question that Turing asked in his 1950 paper titled
“Computing Machinery and Intelligence”. Rather than going into the details and
definitions of various terms in the question . He instead decided to reframe the
question as “Can machines Imitate humans”.
 This was the most pertinent question which early researchers in the field of
Artificial Intelligence have asked and in this field Turing was the torch-bearer. His
paper countered all the objections raised against a machine thinking as intelligently
as humans.
 This was when he presented the Turing Test which has now become the Litmus
test of Machine Intelligence. It was based on the ‘Imitation Game’ , infact there are
several versions of this the most important among them are ‘Imitation Game’ and
the ‘Standard Turing Test’.
 Several machines have passed the turing test till date,first among them are
Joseph Weizenbaum’s “ELIZA” and Kenneth Colby’s “PARRY”.
 Most recently there are several chatterbots existing.
 IBM’s Watson is the most powerful and intelligent machine, till date which has
Natural Language Processing capabilities.It has beaten the all-time champions of
popular show Jeopardy,and is on it’s way to commercialization.
The Imitation Game: This is also known as
the party game,where there are two people
on man and a woman and a third person
who is the interrogator. The Interrogator can
only interact with the two people through
text , that is letters. The man tries to trick
the interrogator into believing that he is a
woman and the woman tries to befool the
interrogator that she is a man. The
interrogator must recognize the truth
behind the messages. In turing’s version of
the game either the man or the woman is
replaced by a digital computer.

The Standard Turing Test: In this test
the differences between the sexes is
dissolved , there is a computer and a
person, and an interrogator. The
Computer tricks the
Interrogator into believing that it is a
human . If it passes then it is Intelligent.
 Reverse Turing Test: This is where a computer decides for itself where it interacts with a
human or not. CAPTCHA’s are examples of this.Though breaking the CAPTCHA code is quite easy
with artificial Neural Networks.
 The Loebner Prize : Its is an annual competition held at Center for Behavioral Studies in
Cambridge , Massachusetts (U.S). This is where various intelligent machines try to deceive the
judges and since its inception in the year 1991 it has received , overwhelming participation from
various corners of the world. Though there is enough scepticism regarding the rules and the
procedure of testing , most consider this prestigious award as the recognition of their machine’s
intelligence.
 Drawbacks: The most significant one raised by John Searle which states that the Turing Test
doesnot take into account the Mental State and the previous knowledge of the interrogator
,that is whether the interrogator knows he is testing a Computer or not. Then there are
quintessential human emotions like greed & avarice, rancour & jealously. Tenacity, and most
importantly Imagination the brainchild of human survival and the harbinger of innovation which
machines lack.
1. In Computability theory a system of data-manupulation rules
    which can simulate any single taped turing machine is known as
    Turing Complete.
2. In practice, Turing completeness means that rules followed in
   sequence on arbitrary data can produce the result of any
   calculation. In imperative languages, this can be satisfied by
   having, at a minimum, conditional branching (e.g., an "if" and
   "goto" statement) and the ability to change
   arbitrary memory locations (e.g., having variables). To show that
   something is Turing complete, it is enough to show that it can be
   used to simulate the most primitive computer, since even the
   simplest computer can be used to simulate the most complicated
   one.
3. Thus , Turing Completeness is a measure of the computational
   power of any given programming language.
Automated Computing Engine
1. The Automatic Computing Engine (ACE) was an
   early electronic stored-program computer design produced
   by Alan Turing at the invitation of John R. Womersley,
   superintendent of the Mathematics Division of the National
   Physical Laboratory (NPL). It was based on turing’s work at
   Bletchley Park , where he designed the Colossus Computers for
   breaking the German Codes.

2. Turing’s draft on the construction of the Engine stated that “It
   should use stored program in its memory”, he had laid out the
   detailed logic diagrams and the circuits for construction of the
   Computer.

3. The Pilot Model of the ACE was developed and soon after John
   Von Nuemann proposed his design for the EDVAC which was
   based on turing work and this is the same architecture that is
   used in the Modern Computers.
Navigating through the Intelligence…
I.   Artificial intelligence (AI) is the intelligence of machines and the
     branch of computer science that aims to create it. AI textbooks
     define the field as "the study and design of intelligent
     agents" where an intelligent agent is a system that perceives its
     environment and takes actions that maximize its chances of
     success. John McCarthy, who coined the term in 1955, defines it as
     "the science and engineering of making intelligent machines.“

II. The field of AI research was founded at a conference on the
    campus of Dartmouth College in the summer of 1956.The
    attendees, including John McCarthy, Marvin Minsky, Allen
    Newell and Herbert Simon, became the leaders of AI research for
    many decades. They and their students wrote programs that were,
    to most people, simply astonishing.
Continued…
 The  field of AI has seen its ups and downs, it has seen the oft termed
“AI winter” in the 70’s and the early 90’s.
 But today it is soaring high and has brought almost all the
Computational fields under its ambit.
 Popular applications of AI include : “Data Mining”, “Search
Optimization”, “Social Intelligence”, “Neural Networks”, “Logic”.
 Google’s Search Engine uses AI to optimize your search queries.
 Robotics which is soon going to a significant game-changer has AI as
its cornerstone.

 Examples of AI based systems include:

 IBM’s chess playing Deep Blue, IBM’s Watson,
 DARPA Grand Challenge.
 HOAP 2
Artificial Life…
Turing’s Contribution…
           Turing worked from 1952 until his death in 1954
on mathematical biology, specifically morphogenesis. He
published one paper on the subject called The Chemical Basis
of Morphogenesis in 1952, putting forth the Turing
hypothesis of pattern formation. His central interest in the
field was understanding Fibonacci phyllotaxis the existence of
Fibonacci numbers in plant structures. He used reaction–
diffusion equations which are central to the field of pattern
formation. Later papers went unpublished until 1992 when
Collected Works of A.M. Turing was published. His
contribution is considered a seminal piece of work in this
field.
The Problem Statement is : Can there ever be a program which
can predict whether another program will halt on a specific input.

DOES-HALT(program,input) // halts if the program goes into an infinte
                            loop else does-not halt.


SELF-HALT(program) {
      if (DOES-HALT(program,program)) {
               infinite loop
      } else {
               halt
      }
}
Now we give the input to the function self-halt as follows:
SELF-HALT(SELF-HALT)
What happens….????
A                               A                             A
          Given above is a buffer gate which consists of two NOT gates .
As is evident since it undergoes a double inversion we get the output same as
  the input. A turing Machine can be roughly compared to a NOT gate for the
    sake of simplicity and understanding and not for any real implications. In
 reality the turing machine is a DFA(Deterministic Finite Automata), that is its
  states are fixed and predetermined and can transition to only one state on a
   single input. Here we are trying to create a parallelism between the Buffer
  gate and the Halting Problem for a better and much easier understanding of
 the latter. Similar to the Buffer Gate the Output of one turing machine when
fed as the Input of another equivalent turing machine should yield the original
 input but in reality it doesnot.This is the paradox and using this we can prove
   that such a machine cannot exist which can predict whether a program will
                                    stop or not
Turing
Turing

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Turing

  • 1. 1912-2012 : “100 years of Genius”
  • 2. Salient Points of the Presentation  A Brief History of Turing’s Life  Turing’s Contributions to Computer Science  Turing Machine  Turing Test  Turing Completeness(Programming Language)  ACE (Automated Computing Engine)  AI (Artificial Intelligence)  Artificial Life  Halting Problem
  • 3. After the War he On his return He met his During WWII, he demise on: Alan Mathias worked at The reformulated from the U.S,he Turing: Born 23 Government Code Hilbert’s decision joined the 7 June June 1912,Maida & Cipher School at problem and gave National 1954 (aged 4 Vale, London, Bletchley Park as a his own hypothesis Physical 1) England, United Cryptanalyst. which is now know Laboratory, in Wilmslow Kingdom. But was Where he invented as the Halting Cheshire, Manchester, conceived in the bombe to England, Problem where he United Chatrapur Odisha, crack the German his father worked codes. He was There after,he developed the Kingdom, for the Indian Civil placed in Hut – 8, worked under Automated Cause of Sevices.He the division Alonso Church at Computing death attended responsible for Princeton and gave Engine(ACE),wh according to Sherbone School Intercepting and the Church-Turing ich is a the reports is in Dorset,thereafter breaking the hypothesis which primitive type cyanide German gives a formal of Computer. poisoning. enrolled in Kings codes.According to Thereafter, he College and where some estimates his definition of This marks “Turing Machine” became the end of an he passed with a work reduced the First Class honours war time in the interested in a era and the in Mathematics Atlantic by at least subject called beginning of “Artificial Life” a revolution. two years.
  • 4. A wartime hero in all respects, as he was instrumental in the defeat of the Germans in the Atlantic.  Popularly known as Father of Computer Science, indeed true in all respects.  His turing machine formed the basis of the Modern Computer.  His reformulation of the Halting Problem,which was first introduced by Hilbert as the “Entscheidungsproblem", later led to a set of problems known as NP complete.  The Turing Test served as the benchmark for recognizing an intelligent machine, this was published in his 1936 paper, where he rigorously debated on the topic-”Can Machines think”.  This paper set the ball rolling for the development of Artificial Intelligence and Machine Learning.  Turing Complete- A term associated with programming languages provides the measure of computing power of any given language.  He himself envisioned Computers one day beating Grandmasters at Chess.(which is today a reality).  His contributions to Speech Cryptography is lesser known albeit he developed “Delilah” at Bell Labs.  In his last years he was deeply interested in mathematical biology, especially finding patterns in Chemical Morphogenesis.  Hence to sum it all up, his contribution to the development of Computer Science was akin to that of the fire and wheel in the progress and survival of the human race.
  • 5.
  • 6.  The Turing Machine which I call the “simple wonder”, consists of a tape with symbols etched on them, and a head which is restricted to move only forward and backward, reading the symbols and performing necessary actions according to a table of rules.  The most simple Turing machine can be approximated to a DFA(Deterministic Finite Automata).The following example will illustrate the same. 1/0 0 1 Start State Final State
  • 7.  A turing machine consists of a tape which is divided into cells,each cell has an alphabet etched on it or it might be left blank, the alphabet can belong to any “Formal Language” or a Regular Expression.”  A head which is capable of movement in the left and right directions and it reads the symbols which are written on the tape.  A State Register which stores the state of the of the machine.  Then there is an action table, which stores the actions to be performed on encountering a specific symbol or state.  Thus a complete turing machine can be thought of as a tuple of the following: { Q , ∑ , δ , q0 , F } Where: Q : Finite Set of States ∑ : Finite Set of Input Symbols δ : Transition State a function of f(Q,sigma) q0 : The initial state or the start state F : Final State or the Accept State.
  • 8. The Universal Turing Machine: A turing Machine which can mimic any other turing machine is known as the Universal Turing Machine. In simple words it can solve any problem which is posed to it. The Turing Oracle: It is a turing Machine, which has an infinite amount of tape length. Its is used to solve decision problems, though it fails in the halting problem.
  • 9. Can Machines Think???....  That was the same question that Turing asked in his 1950 paper titled “Computing Machinery and Intelligence”. Rather than going into the details and definitions of various terms in the question . He instead decided to reframe the question as “Can machines Imitate humans”.  This was the most pertinent question which early researchers in the field of Artificial Intelligence have asked and in this field Turing was the torch-bearer. His paper countered all the objections raised against a machine thinking as intelligently as humans.  This was when he presented the Turing Test which has now become the Litmus test of Machine Intelligence. It was based on the ‘Imitation Game’ , infact there are several versions of this the most important among them are ‘Imitation Game’ and the ‘Standard Turing Test’.  Several machines have passed the turing test till date,first among them are Joseph Weizenbaum’s “ELIZA” and Kenneth Colby’s “PARRY”.  Most recently there are several chatterbots existing.  IBM’s Watson is the most powerful and intelligent machine, till date which has Natural Language Processing capabilities.It has beaten the all-time champions of popular show Jeopardy,and is on it’s way to commercialization.
  • 10. The Imitation Game: This is also known as the party game,where there are two people on man and a woman and a third person who is the interrogator. The Interrogator can only interact with the two people through text , that is letters. The man tries to trick the interrogator into believing that he is a woman and the woman tries to befool the interrogator that she is a man. The interrogator must recognize the truth behind the messages. In turing’s version of the game either the man or the woman is replaced by a digital computer. The Standard Turing Test: In this test the differences between the sexes is dissolved , there is a computer and a person, and an interrogator. The Computer tricks the Interrogator into believing that it is a human . If it passes then it is Intelligent.
  • 11.  Reverse Turing Test: This is where a computer decides for itself where it interacts with a human or not. CAPTCHA’s are examples of this.Though breaking the CAPTCHA code is quite easy with artificial Neural Networks.  The Loebner Prize : Its is an annual competition held at Center for Behavioral Studies in Cambridge , Massachusetts (U.S). This is where various intelligent machines try to deceive the judges and since its inception in the year 1991 it has received , overwhelming participation from various corners of the world. Though there is enough scepticism regarding the rules and the procedure of testing , most consider this prestigious award as the recognition of their machine’s intelligence.  Drawbacks: The most significant one raised by John Searle which states that the Turing Test doesnot take into account the Mental State and the previous knowledge of the interrogator ,that is whether the interrogator knows he is testing a Computer or not. Then there are quintessential human emotions like greed & avarice, rancour & jealously. Tenacity, and most importantly Imagination the brainchild of human survival and the harbinger of innovation which machines lack.
  • 12.
  • 13. 1. In Computability theory a system of data-manupulation rules which can simulate any single taped turing machine is known as Turing Complete. 2. In practice, Turing completeness means that rules followed in sequence on arbitrary data can produce the result of any calculation. In imperative languages, this can be satisfied by having, at a minimum, conditional branching (e.g., an "if" and "goto" statement) and the ability to change arbitrary memory locations (e.g., having variables). To show that something is Turing complete, it is enough to show that it can be used to simulate the most primitive computer, since even the simplest computer can be used to simulate the most complicated one. 3. Thus , Turing Completeness is a measure of the computational power of any given programming language.
  • 15. 1. The Automatic Computing Engine (ACE) was an early electronic stored-program computer design produced by Alan Turing at the invitation of John R. Womersley, superintendent of the Mathematics Division of the National Physical Laboratory (NPL). It was based on turing’s work at Bletchley Park , where he designed the Colossus Computers for breaking the German Codes. 2. Turing’s draft on the construction of the Engine stated that “It should use stored program in its memory”, he had laid out the detailed logic diagrams and the circuits for construction of the Computer. 3. The Pilot Model of the ACE was developed and soon after John Von Nuemann proposed his design for the EDVAC which was based on turing work and this is the same architecture that is used in the Modern Computers.
  • 16.
  • 17. Navigating through the Intelligence… I. Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines.“ II. The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades. They and their students wrote programs that were, to most people, simply astonishing.
  • 18. Continued…  The field of AI has seen its ups and downs, it has seen the oft termed “AI winter” in the 70’s and the early 90’s.  But today it is soaring high and has brought almost all the Computational fields under its ambit.  Popular applications of AI include : “Data Mining”, “Search Optimization”, “Social Intelligence”, “Neural Networks”, “Logic”.  Google’s Search Engine uses AI to optimize your search queries.  Robotics which is soon going to a significant game-changer has AI as its cornerstone.  Examples of AI based systems include:  IBM’s chess playing Deep Blue, IBM’s Watson,  DARPA Grand Challenge.  HOAP 2
  • 20. Turing’s Contribution… Turing worked from 1952 until his death in 1954 on mathematical biology, specifically morphogenesis. He published one paper on the subject called The Chemical Basis of Morphogenesis in 1952, putting forth the Turing hypothesis of pattern formation. His central interest in the field was understanding Fibonacci phyllotaxis the existence of Fibonacci numbers in plant structures. He used reaction– diffusion equations which are central to the field of pattern formation. Later papers went unpublished until 1992 when Collected Works of A.M. Turing was published. His contribution is considered a seminal piece of work in this field.
  • 21.
  • 22. The Problem Statement is : Can there ever be a program which can predict whether another program will halt on a specific input. DOES-HALT(program,input) // halts if the program goes into an infinte loop else does-not halt. SELF-HALT(program) { if (DOES-HALT(program,program)) { infinite loop } else { halt } } Now we give the input to the function self-halt as follows: SELF-HALT(SELF-HALT) What happens….????
  • 23. A A A Given above is a buffer gate which consists of two NOT gates . As is evident since it undergoes a double inversion we get the output same as the input. A turing Machine can be roughly compared to a NOT gate for the sake of simplicity and understanding and not for any real implications. In reality the turing machine is a DFA(Deterministic Finite Automata), that is its states are fixed and predetermined and can transition to only one state on a single input. Here we are trying to create a parallelism between the Buffer gate and the Halting Problem for a better and much easier understanding of the latter. Similar to the Buffer Gate the Output of one turing machine when fed as the Input of another equivalent turing machine should yield the original input but in reality it doesnot.This is the paradox and using this we can prove that such a machine cannot exist which can predict whether a program will stop or not