New £50 Celebrates Turing’s Achievements

ITNOW ◽  
2019 ◽  
Vol 61 (4) ◽  
pp. 32-33
Author(s):  
Johanna Hamilton

Abstract Johanna Hamilton interviews Sarah John, Chief Cashier of the Bank of England, about the decision to feature Alan Turing, the father of computer science, on the new £50 note.

Author(s):  
Arlindo Oliveira

This chapter covers the development of computing, from its origins, with the analytical engine, to modern computer science. Babbage and Ada Lovelace’s contributions to the science of computing led, in time, to the idea of universal computers, proposed by Alan Turing. These universal computers, proposed by Turing, are conceptual devices that can compute anything that can possibly be computed. The basic concepts created by Turing and Church were further developed to create the edifice of modern computer science and, in particular, the concepts of algorithms, computability, and complexity, covered in this chapter. The chapter ends describing the Church-Turing thesis, which states that anything that can be computed can be computed by a Turing machine.


Author(s):  
Iolanda Pisotta ◽  
Silvio Ionta

We experience and interact with the world through our body. The founding father of computer science, Alan Turing, correctly realized that one of the most important features of the human being is the interaction between mind and body. Since the original demonstration that electrical activity of the cortical neurons can be employed to directly control a robotic device, the research on the so-called Brain-Machine Interfaces (BMIs) has impressively grown. For example, current BMIs dedicated to both experimental and clinical studies can translate raw neuronal signals into computational commands to reproduce reaching or grasping in artificial actuators. These developments hold promise for the restoration of limb mobility in paralyzed individuals. However, as the authors review in this chapter, before this goal can be achieved, several hurdles have to be overcome, including developments in real-time computational algorithms and in designing fully implantable and biocompatible devices. Future investigations will have to address the best solutions for restoring sensation to the prosthetic limb, which still remains a major challenge to full integration of the limb into the user's self-image.


Author(s):  
Stephen Wolfram

I never met Alan Turing; he died five years before I was born. But somehow I feel I know him well, not least because many of my own intellectual interests have had an almost eerie parallel with his. And by a strange coincidence, the ‘birthday’ of Wolfram Mathematica, 23 June 1988, is aligned with Turing’s own. I think I first heard of Alan Turing when I was about 11 years old, right around the time I saw my first computer. Through a friend of my parents, I had got to know a rather eccentric old classics professor, who, knowing my interest in science, mentioned to me this ‘bright young chap named Turing’ whom he had known during the Second World War. One of this professor’s eccentricities was that, whenever the word ‘ultra’ came up in a Latin text, he would repeat it over and over again and make comments about remembering it. At the time, I didn’t think much of it, although I did remember it. Only years later did I realize that ‘Ultra’ was the codename for the British cryptanalysis effort at Bletchley Park during the war. In a very British way, the classics professor wanted to tell me something about it, without breaking any secrets—and presumably it was at Bletchley Park that he had met Alan Turing. A few years later I heard scattered mentions of Alan Turing in various British academic circles. I heard that he had done mysterious but important work in breaking German codes during the war, and I heard it claimed that after the war he had been killed by British Intelligence. At that time some of the British wartime cryptography effort was still secret, including Turing’s role in it. I wondered why. So I asked around, and started hearing that perhaps Turing had invented codes that were still being used. In reality, though, the continued secrecy seems to have been intended to prevent its being known that certain codes had been broken, so that other countries would continue to use them. I am not sure where I next encountered Alan Turing. Probably it was when I decided to learn all I could about computer science, and saw all sorts of mentions of ‘Turing machines’. But I have a distinct memory from around 1979 of going to the library and finding a little book about Alan Turing written by his mother, Sara Turing.


Author(s):  
Robin Whitty

In 1936 Turing invented a mathematical model of computation, known today as the Turing machine. He intended it as a representation of human computation and in particular as a vehicle for refuting a central part of David Hilbert’s early 20th-century programme to mechanize mathematics. By a nice irony it came to define what is achievable by non-human computers and has become deeply embedded in modern computer science. A simple example is enough to convey the essentials of a Turing machine. We then describe the background to Hilbert’s programme and Turing’s challenge—and explain how Turing’s response to Hilbert resolves a host of related problems in mathematics and logic. If I had to portray, in less than 30 seconds, what Alan Turing achieved in 1936 it seems to me that drawing the picture shown in Fig. 37.1 would be a reasonable thing to do. That this might be so is a testament to the quite extraordinary merging of the concrete and the abstract in Turing’s 1936 paper on computability. It is regarded by, I suppose, a large majority of mathematical scientists as his greatest work. The details of our picture are not especially important. As it happens, it is a machine for deciding which whole numbers, written in binary form, are multiples of 3. It works thus: suppose the number is 105, whose binary representation is 1101001, because (1 × 26) + (1 × 25) + (0 × 24) + (1 × 23) + (0 × 22) + (0 × 21) + (1 × 20) = 64 + 32 + 8 + 1 = 105. We start at the node labelled A and use the binary digits to drive us from node to node. The first couple of 1s take us to node B and back to A again. The third digit, 0, loops us around at A. Now a 1 and a 0 take us across to node C; and the final 0 and 1 take us back via B to A once more.


Author(s):  
Jack Copeland ◽  
Jonathan Bowen ◽  
Mark Sprevak ◽  
Robin Wilson

Alan Turing has long proved a subject of fascination, but following the centenary of his birth in 2012, the code-breaker, computer pioneer, mathematician (and much more) has become even more celebrated with much media coverage, and several meetings, conferences and books raising public awareness of Turing's life and work. This volume will bring together contributions from some of the leading experts on Alan Turing to create a comprehensive guide to Turing that will serve as a useful resource for researchers in the area as well as the increasingly interested general reader. The book will cover aspects of Turing's life and the wide range of his intellectual activities, including mathematics, code-breaking, computer science, logic, artificial intelligence and mathematical biology, as well as his subsequent influence.


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