Search Results

The Computer Industry

Vernon W. Ruttan

in Is War Necessary for Economic Growth?: Military Procurement and Technology Development

The first all-purpose digital computer, completed in 1946, was developed by John W. Mauchly and J. Prosper Eckert, and associates at the University of Pennsylvania’s Moore School of Electrical ... More

The first all-purpose digital computer, completed in 1946, was developed by John W. Mauchly and J. Prosper Eckert, and associates at the University of Pennsylvania’s Moore School of Electrical Engineering, with funding from the U.S. Army Ballistic Research Laboratory. The first working transistor emerged from the solid state research program at Bell Laboratories led by William Schokley, John Bardeen, and Walter Brattain. The transition between initial development of the transistor and the subsequent development of military and commercial application in the 1950s were substantially funded by the Army Signal Corps. Intensification of the Cold War in the early 1950s provided the impetus for IBM to develop a fully transistorized computer for commercial use. Development of the integrated circuit at Texas Instruments in the late 1950s and of the microprocessor at Intel in the late 1960s set the stage for the development of both modern supercomputers and the personal computer.Less

Introduction

Ronald de Sousa

in Why Think?: Evolution and the Rational Mind

This introductory chapter begins with a discussion of the concept of rationality. It then discusses the difference between digital computers and analog computers, the origins and limits of ... More

This introductory chapter begins with a discussion of the concept of rationality. It then discusses the difference between digital computers and analog computers, the origins and limits of intelligence, and meeting Plantinga's challenge. An overview of the succeeding chapters is presented.Less

Digital Computers

Gualtiero Piccinini

in Physical Computation: A Mechanistic Account

This chapter explicates digital computers in mechanistic terms. It offers a systematic taxonomy of kinds of digital computer, including hard-wired vs. programmable and general-purpose vs. ... More

This chapter explicates digital computers in mechanistic terms. It offers a systematic taxonomy of kinds of digital computer, including hard-wired vs. programmable and general-purpose vs. special-purpose, giving explicit mechanistic criteria for each kind. The account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system’s mechanistic properties. Finally, the chapter briefly illustrates how the mechanistic account sheds light on some issues in the history and philosophy of computing as well as the philosophy of cognitive science. Formulations of computationalism are discussed. In particular, a robust notion of digital computers gives substance to theories according to which the brain is a digital computer.Less

Analog Computers

Gualtiero Piccinini

in Physical Computation: A Mechanistic Account

This chapter explicates analog computers in mechanistic terms. Problems with the analog-digital distinction are discussed, in particular with grounding the distinction solely in the ... More

This chapter explicates analog computers in mechanistic terms. Problems with the analog-digital distinction are discussed, in particular with grounding the distinction solely in the continuous-discrete dichotomy. Whereas the inputs and outputs of digital computers and their components are strings of digits, the inputs and outputs of analog computers and their components are continuous variables. Analog computers are mechanisms whose function is transforming an input real variable received during a certain time interval into an output real variable that stands in a specified functional relation to the input. The crucial components of analog computers are integrators. The reasons why both classes of devices are called ‘computers’, despite how little (pure) analog computers and digital computers have in common, are discussed.Less

What Lies Ahead: Virtuality, the Body, and the Computer Screen

Kate Mondloch

in Screens: Viewing Media Installation Art

This chapter examines the transformations in the spatial conditions of viewing media art accompanied by powerful yet unstructured networks associated with digital computer screens. It states that the ... More

This chapter examines the transformations in the spatial conditions of viewing media art accompanied by powerful yet unstructured networks associated with digital computer screens. It states that the concern of the case studies reviewed in this chapter with the spectator’s relationship to the space associated with viewing media screens is entirely consistent. It concludes by raising questions about new media installation art.Less

In the fMRI Laboratory

Morana Alač

in Handling Digital Brains: A Laboratory Study of Multimodal Semiotic Interaction in the Age of Computers

This chapter starts with the introduction of functional magnetic resonance imaging (fMRI) technology and its role in medicine and science, especially in cognitive neuroscience, and also explains the ... More

This chapter starts with the introduction of functional magnetic resonance imaging (fMRI) technology and its role in medicine and science, especially in cognitive neuroscience, and also explains the process of human brain mapping using fMRI and physical gestures. It further explores the development of technology, drawing attention to how researchers feel about digital computers and interface with them using their bodies. The author emphasizes different laboratory studies, works, and researches that are involved in the discussion of the scientific visuals concept. The final section of the chapter outlines the subsections and individual chapters discussed in this book.Less

Computing Hardware: Digital

James A. Anderson

in After Digital: Computation as Done by Brains and Machines

Digital computers are built from hardware of great simplicity. First, they are built from devices with two states: on or off, one or zero, high voltage or low voltage, or logical TRUE or FALSE. ... More

Digital computers are built from hardware of great simplicity. First, they are built from devices with two states: on or off, one or zero, high voltage or low voltage, or logical TRUE or FALSE. Second, the devices are connected with extremely fine connections, currently on the order of size of a large virus. Their utility, value, and perceived extreme complexity lie in the software controlling them. Different devices have been used to build computers: relays, vacuum tubes, transistors, and integrated circuits. Theoretically, all can run the same software, only slower or faster. More exotic technologies have not proved commercially viable. Digital computer hardware has increased in power by roughly a factor of 2 every 2 years for five decades, an observation called Moore’s Law. Engineering problems with very small devices, such as quantum effects, heat, and difficulty of fabrication, are increasing and may soon end Moore’s Law.Less

Programmability

Wendy Hui Kyong Chun

in Software Studies: A Lexicon

This chapter briefly discusses the different conceptions of program and programmability in the digital computer field; the discussion continues with two different grammatical definitions of the term ... More

This chapter briefly discusses the different conceptions of program and programmability in the digital computer field; the discussion continues with two different grammatical definitions of the term “program,” verb and noun. It also focuses on ENIAC, the first working electronic digital computer. The chapter describes the requirements and the process of programming the analog and digital computer machines along with the works and arguments of various computer scientists. It furthermore states that programming an analog computer is descriptive while programming a digital one is prescriptive. The conclusion explains how the programmability concept affected the world of computers, from quantum computers to biology computing fields like DNA and RNA computing.Less

The Red Queen’s Race

Arlindo Oliveira

in The Digital Mind: How Science is Redefining Humanity

This chapter introduces the idea that technology, invented millennia ago, is developing at an even increasing pace, creating the need for all systems to develop to avoid becoming obsolete. This is ... More

This chapter introduces the idea that technology, invented millennia ago, is developing at an even increasing pace, creating the need for all systems to develop to avoid becoming obsolete. This is called the Red Queen effect. The current generation has seen the appearance and rapid development of many new technologies, from digital computers and cellular phones, to DNA sequencing and genetic engineering. However, the next decades will witness an even faster technological development, leading to the appearance of economic and social realities that we cannot even dream of. Computer technology and biotechnology will come together to create changes in society that will make the last decades look like slow-paced, in what respects technology development.Less

Creating Insight: Gestalt Theory and the Early Computer

David Bates

in Genesis Redux: Essays in the History and Philosophy of Artificial Life

This chapter questions the underlying assumptions of both classic Artificial Intelligence, founded in the analogy between the brain and the digital computer, and the newer tradition that construes ... More

This chapter questions the underlying assumptions of both classic Artificial Intelligence, founded in the analogy between the brain and the digital computer, and the newer tradition that construes the mind as an emergent property of interacting, distributed, parallel processes. It specifically explores Gestalt psychology and its brief engagement with cybernetics to suggest that was perhaps a missed opportunitt, and additionally examines John von Neumann's influential automata theory. The structure of insight helped explain the complex, nonmechanical behavior of living, acting organisms. For von Neumann, the creative plasticity of the nervous system served only to highlight the rather simplistic, and inferior, mechanical structure of the early computers, something he was of course well positioned to notice. His terse conclusion was that the logical structures involved in nervous system activity must “differ considerably” from the ones that are familiar in logic and mathematics.Less

Computers and the Politics of Systematics

Christine Hine

in Systematics as Cyberscience: Computers, Change, and Continuity in Science

This chapter can be regarded as the continuation of the preceding chapter; in this section, the author extends his views in the field of systematics in a detailed way. The chapter explores the role ... More

This chapter can be regarded as the continuation of the preceding chapter; in this section, the author extends his views in the field of systematics in a detailed way. The chapter explores the role of ICTs in systematics as a case study through the analysis of high-profile and public commentary. Politicization issues, the relationship between material and virtual cultures, and the historical specificity of systematics are briefly covered in the next parts of the chapter. The chapter also investigates the role of new and existing digital computer technologies and the Select Committee Report in the field of systematics. The data for this case study, drawn from the 2002 policy report, was produced by the United Kingdom's House of Lords Select Committee on Science and Technology. The conclusion of the chapter explains that further exploration is needed on the study results.Less

Synthesis

Edmund T. Rolls

in Cerebral Cortex: Principles of Operation

Principles of cortical computation, and not a whole theory of cortical computation, are described. However, Chapter 18 on the evolution of the cortex and Section 26.5.18 come close to presenting ... More

Principles of cortical computation, and not a whole theory of cortical computation, are described. However, Chapter 18 on the evolution of the cortex and Section 26.5.18 come close to presenting hypotheses about how cortical microcircuitry operates; and as examples of how the principles combine to provide a theory of how cortical systems operate, I outline a theory of the operation of the hippocampal system for episodic memory in Chapter 24, and a theory of the operation of the ventral visual system for transform invariant object recognition in Chapter 25. The mind-brain problem is considered in the light of different levels of explanation, which offer a solution. A comparison of cortical computation and computation in a digital computer highlights many fundamentally different principles of brain computation, and computation in a digital computer. Reasons why understanding cortical computation is making rapid progress are described. The advances in understanding the emotional, rational, and decision-making systems in the brain have implications for understanding in a wide range of areas, including aesthetics, art, ethics, economics, and social interactions, as considered elsewhere (Rolls, 2012, 2016). Section 26.5 draws together some of the principles of operation of the cerebral cortex, to help the reader understand the progression that has been made in the course of this book. Pointers are provided to the chapters where the principles are described, and new thoughts are added on how some of the principles relate to each other to provide foundations for cortical operation. New thoughts are also added on cortical lamination and the types of computation performed in different layers, and in different types of cortex, including neocortex, pyriform cortex, and hippocampal cortex. New ideas and concepts are also added that may help to provide a foundation for further understanding and investigations of how the cerebral cortex operates in health and disease.Less

Computation

Nico Orlandi

in The Innocent Eye: Why Vision Is Not a Cognitive Process

The final chapter concludes the case in favor of the embedded view by showing that the view is compatible with computational theories of mental activity. This is true for two reasons. First, there ... More

The final chapter concludes the case in favor of the embedded view by showing that the view is compatible with computational theories of mental activity. This is true for two reasons. First, there are perfectly legitimate models of computation that do not describe them as regimented operations on representations. Second, denying that the visual system performs computations in a narrow, classical sense does not amount to rejecting the classical computational theory of mind in its entirety. We can concede that classicism is true of other mental processes while recognizing that we have little reason to suppose that it is true of perception. The chapter discusses the systematicity and productivity that we find in vision and argues that these two features do not require appeal to classical computations.Less

Quantum

Lance Fortnow

in The Golden Ticket: P, NP, and the Search for the Impossible

This chapter examines the power of quantum computing, as well as the related concepts of quantum cryptography and teleportation. In 1982, the Nobel prize-winning physicist Richard Feynman noticed ... More

This chapter examines the power of quantum computing, as well as the related concepts of quantum cryptography and teleportation. In 1982, the Nobel prize-winning physicist Richard Feynman noticed there was no simple way of simulating quantum physical systems using digital computers. He turned this problem into an opportunity—perhaps a computational device based on quantum mechanics could solve problems more efficiently than more traditional computers. In the decades that followed, computer scientists and physicists, often working together, showed in theory that quantum computers can solve certain problems, such as factoring numbers, much faster. Whether one can actually build large or even medium-scale working quantum computers and determine exactly what these computers can or cannot do still remain significant challenges.Less

Chips with Everything

David Segal

in Materials for the 21st Century

Chapter 3 highlights the critical role materials have in the development of digital computers. It traces developments from the cat’s whisker to valves through to relays and transistors. Accounts are ... More

Chapter 3 highlights the critical role materials have in the development of digital computers. It traces developments from the cat’s whisker to valves through to relays and transistors. Accounts are given for transistors and the manufacture of integrated circuits (silicon chips) by use of photolithography. Future potential computing techniques, namely quantum computing and the DNA computer, are covered. The history of computability and Moore’s Law are discussed.Less

Introduction

in Science in the Age of Computer Simulation

This introduction discusses the theme of this book, which is about computer simulation and the philosophy of science. The book examines what philosophers of science should learn in the age of ... More

This introduction discusses the theme of this book, which is about computer simulation and the philosophy of science. The book examines what philosophers of science should learn in the age of simulation and what philosophy can contribute to our understanding of how the digital computer is transforming science. It investigates the relationship between computer simulation and experiment, the conditions under which computer simulation can be reliable, and the role of deliberately false assumptions in the construction of simulation models.Less

What Did Alan Turing Mean by “Machine”?

Andrew Hodges

in The Mechanical Mind in History

This chapter focuses on the title of Alan Turing’s unpublished 1948 report “Intelligent Machinery” to explore what Turing intended by an “intelligent machine.” Turing saw central roles for new ... More

This chapter focuses on the title of Alan Turing’s unpublished 1948 report “Intelligent Machinery” to explore what Turing intended by an “intelligent machine.” Turing saw central roles for new digital computers in the development of machine intelligence and in the exploration of brain mechanisms through simulations, both of which came to pass. It is argued that although the central thrust of Turing’s thought was that the action of brains, like that of any machine, could be captured by classical computation, he was aware that there were potential problems in connecting computability with physical reality.Less

Giant Brains

James Lawrence Powell

in Four Revolutions in the Earth Sciences: From Heresy to Truth

This chapter looks at the use of digital computers by scientists to solve the complex equations needed for numerical weather prediction. The first attempts used the ENIAC (Electronic Numerical ... More

This chapter looks at the use of digital computers by scientists to solve the complex equations needed for numerical weather prediction. The first attempts used the ENIAC (Electronic Numerical Integrator and Computer), built by scientists at the University of Pennsylvania between 1943 and 1945. ENIAC, dubbed the “Giant Brain,” had at most ten words of read/write memory, yet its 18,000 vacuum tubes, 6,000 switches, and the like filled an entire room. Scientists then turned to climate modeling using a general circulation model (GCM). The first GCM was developed by Norman Phillips, whose equations divided the atmosphere into an upper and a lower layer. He changed the amount of heat in the lower layer and ran the model through ENIAC to see the effect. By the late 1950s, the U.S. Weather Bureau had emerged as the key climate-modeling agency. This chapter also considers the work of James Hansen on climate change induced by anthropogenic release of carbon dioxide, as well as his dire predictions of the consequences of global warming.Less