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The Slide talks in details about turing's life and his achievements

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  1. 1. 1912-2012 : “100 years of Genius”
  2. 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. 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 WilmslowKingdom. But was Where he invented as the Halting Cheshire, Manchester, conceived in the bombe to England, Problem where he UnitedChatrapur 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, heCollege and where some estimates his definition of This marks “Turing Machine” became the end of an he passed with a work reduced theFirst 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. 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. 5.  The Turing Machine which I call the “simple wonder”,consists of a tape with symbols etched on them, and a headwhich is restricted to move only forward and backward,reading the symbols and performing necessary actionsaccording to a table of rules. The most simple Turing machine can be approximated toa DFA(Deterministic Finite Automata).The following examplewill illustrate the same. 1/0 0 1 Start State Final State
  6. 6.  A turing machine consists of a tape which is divided into cells,each cell hasan alphabet etched on it or it might be left blank, the alphabet can belong toany “Formal Language” or a Regular Expression.” A head which is capable of movement in the left and right directions and itreads 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 onencountering a specific symbol or state. Thus a complete turing machine can be thought of as a tuple of thefollowing: { Q , ∑ , δ , q0 , F }Where:Q : Finite Set of States∑ : Finite Set of Input Symbolsδ : Transition State a function of f(Q,sigma)q0 : The initial state or the start stateF : Final State or the Accept State.
  7. 7. The Universal Turing Machine: Aturing Machine which can mimicany other turing machine isknown as the Universal TuringMachine. In simple words it cansolve any problem which is posedto it.The Turing Oracle: It is a turingMachine, which has an infiniteamount of tape length. Its is usedto solve decision problems,though it fails in the haltingproblem.
  8. 8. 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 anddefinitions of various terms in the question . He instead decided to reframe thequestion as “Can machines Imitate humans”. This was the most pertinent question which early researchers in the field ofArtificial Intelligence have asked and in this field Turing was the torch-bearer. Hispaper countered all the objections raised against a machine thinking as intelligentlyas humans. This was when he presented the Turing Test which has now become the Litmustest of Machine Intelligence. It was based on the ‘Imitation Game’ , infact there areseveral versions of this the most important among them are ‘Imitation Game’ andthe ‘Standard Turing Test’. Several machines have passed the turing test till date,first among them areJoseph 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 hasNatural Language Processing capabilities.It has beaten the all-time champions ofpopular show Jeopardy,and is on it’s way to commercialization.
  9. 9. The Imitation Game: This is also known asthe party game,where there are two peopleon man and a woman and a third personwho is the interrogator. The Interrogator canonly interact with the two people throughtext , that is letters. The man tries to trickthe interrogator into believing that he is awoman and the woman tries to befool theinterrogator that she is a man. Theinterrogator must recognize the truthbehind the messages. In turing’s version ofthe game either the man or the woman isreplaced by a digital computer.The Standard Turing Test: In this testthe differences between the sexes isdissolved , there is a computer and aperson, and an interrogator. TheComputer tricks theInterrogator into believing that it is ahuman . If it passes then it is Intelligent.
  10. 10.  Reverse Turing Test: This is where a computer decides for itself where it interacts with ahuman or not. CAPTCHA’s are examples of this.Though breaking the CAPTCHA code is quite easywith artificial Neural Networks. The Loebner Prize : Its is an annual competition held at Center for Behavioral Studies inCambridge , Massachusetts (U.S). This is where various intelligent machines try to deceive thejudges and since its inception in the year 1991 it has received , overwhelming participation fromvarious corners of the world. Though there is enough scepticism regarding the rules and theprocedure of testing , most consider this prestigious award as the recognition of their machine’sintelligence. Drawbacks: The most significant one raised by John Searle which states that the Turing Testdoesnot 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 arequintessential human emotions like greed & avarice, rancour & jealously. Tenacity, and mostimportantly Imagination the brainchild of human survival and the harbinger of innovation whichmachines lack.
  11. 11. 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.
  12. 12. Automated Computing Engine
  13. 13. 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.
  14. 14. 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.
  15. 15. 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 theComputational fields under its ambit. Popular applications of AI include : “Data Mining”, “SearchOptimization”, “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 asits cornerstone. Examples of AI based systems include: IBM’s chess playing Deep Blue, IBM’s Watson, DARPA Grand Challenge. HOAP 2
  16. 16. Artificial Life…
  17. 17. Turing’s Contribution… Turing worked from 1952 until his death in 1954on mathematical biology, specifically morphogenesis. Hepublished one paper on the subject called The Chemical Basisof Morphogenesis in 1952, putting forth the Turinghypothesis of pattern formation. His central interest in thefield was understanding Fibonacci phyllotaxis the existence ofFibonacci numbers in plant structures. He used reaction–diffusion equations which are central to the field of patternformation. Later papers went unpublished until 1992 whenCollected Works of A.M. Turing was published. Hiscontribution is considered a seminal piece of work in thisfield.
  18. 18. The Problem Statement is : Can there ever be a program whichcan 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….????
  19. 19. 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 whenfed 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