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application of new techniques

  • 1 application

    ˌæplɪˈkeɪʃən сущ.
    1) просьба;
    заявление;
    форма заявления to file an application, make an application, put in an application, send in an application, submit an application ≈ подавать заявление, подавать прошение to reject application, turn down application ≈ отказать в прошении to withdraw an application ≈ забирать прошение membership application ≈ заявление с просьбой о членстве в какой-л. организации written application ≈ письменное прошение, письменное заявление application for financial aid ≈ просьба о финансовой помощи application for admission to a university ≈ заявление о приеме в университет He filed an application to be admitted to the intensive course. ≈ Он подал заявление о приеме на интенсивный курс. Syn: petition, request, formal request
    2) применение, использование, употребление;
    приложение;
    применимость application of new techniques ≈ применение новой техники the place of application of a force ≈ место приложения силы new applications for old remedies ≈ новые приложения старых средств Syn: use
    3) прикладывание, накладывание;
    нанесение
    4) мат. наложение
    5) компресс oily application for dry skin ≈ масляный компресс для сухой кожи
    6) аппликация, вышивка
    7) применение (лекарства) single application ≈ одноразовое применение лекарственного средства Rheumatic pains cured by the application of spirits of camphor. ≈ Ревматические боли снимаются применением камфарного спирта.
    8) прилежание, старание, усердие to succeed by application to one's studies ≈ добиваться успеха благодаря прилежанию в занятиях Syn: diligence I, attention
    1), assiduous effort
    9) компьют. прикладная задача
    заявление;
    заявка - written * письменное заявление - * form бланк заявки;
    бланк для заявления - * for the position заявление о зачислении на должность - to get books on * получить книги по заявке - to send in an * подать заявление просьба, обращение - * for help просьба о помощи - to refuse an * отказать в просьбе - * to smb. for smth. обращение к кому-либо за чем-либо (юридическое) заявление, письменное ходатайство суду или судье применение, приложение;
    использование - * of atomic energy for peaceful purposes применение атомной энергии в мирных целях - * of a theory in actual practice применение теории в практической деятельности - * of the law to the present case применение закона к данному случаю - such terms have no * with it такие термины неприменимы к этому применение, употребление - for external * only только для наружного употребления (о лекарстве) - * of force( физическое) приложение силы прикладывание, накладывание;
    нанесение (слоя вещества) - * of dressing to a wound наложение повязки на рану - * of ice to the forehead прикладывание льда ко лбу - * of forceps (медицина) наложение акушерских щипцов (математика) наложение (сельскохозяйственное) (профессионализм) внесение удобрений или ядохимикатов - heavy * обильное удобрение - supplemental * дополнительное удобрение, подкормка - liberal * повышенное удобрение - light * внесение малых доз( ядохимикатов) компресс, примочка - hot and cold *s горячие и холодные компрессы аппликация (вышивка) прилежание, рвение, внимание - to give * to work усердно работать - to lack * не проявлять особого рвения - my work demands close * моя работа требует пристального внимания (информатика) (прикладная) программа
    application жалоба ~ заявка ~ заявка на приобретение вновь выпускаемых ценных бумаг ~ заявление;
    прошение;
    to put in an application подать заявление ~ заявление ~ использование ~ обращение ~ обращение за кредитом ~ обращение за открытием счета ~ обращение за признанием в качестве банка ~ обращение за признанием в качестве брокера ~ отнесение платежа к определенному долгу ~ письменное ходатайство суду или судье ~ вчт. прикладная программа ~ прикладывание (горчичника, пластыря и т. п.) ~ прилежание, рвение, старание (тж. application to work) ~ прилежание ~ вчт. приложение ~ приложение ~ применение;
    применимость ~ применение (права, закона) ~ применение ~ просьба ~ прошение, заявление;
    применение (закона, правила, инструмента, прибора и т. п.) ~ рвение ~ употребление (лекарства) ~ употребление ~ ходатайство
    ~ by letter письменное заявление
    ~ for admission заявление о приеме
    ~ for admission to official listing заявка на допуск ценной бумаги к официальной торговле на фондовой бирже
    ~ for adoption сем. право заявление об усыновлении
    ~ for asylum просьба о предоставлении убежища
    ~ for cancellation просьба об аннулировании
    ~ for credit facilities заявка на выделение ссуды ~ for credit facilities заявка на получение кредитов
    ~ for documentary credit заявка на получение документарного аккредитива
    ~ for invalidation of an election заявление о признании выборов недействительными
    ~ for licence заявление с просьбой о предоставлении лицензии ~ for licence лицензионная заявка
    ~ for loan заявление с просьбой выдать заем ~ for loan просьба о предоставлении займа
    ~ for membership заявление о приеме в члены
    ~ for postponement недв. просьба об отсрочке
    ~ for probate заявление об утверждении завещания
    ~ for registration of limited company заявление о регистрации компании с ограниченной ответственностью
    ~ for registration of trade mark заявление о регистрации торговой марки
    ~ for shares заявка на приобретение вновь выпускаемых акций
    ~ form анкета поступающего на работу form: application ~ бланк заявки application ~ бланк заявки на приобретение акций application ~ бланк заявления application ~ бланк подписки на заем application ~ заявочный бланк
    ~ of law применение закона
    business ~ коммерческое применение
    computer ~ применение компьютера
    convention ~ пат. конвенционная заявка
    credit ~ заявка о предоставлении кредита
    declined loan ~ отклоненная заявка на получение ссуды
    dedicated ~ специализированное применение dedicated ~ специальное применение
    distributed ~ вчт. распределенная прикладная система
    ex parte ~ заявление одной стороны
    file an ~ подавать заявку file an ~ подавать заявление
    grant an ~ подавать заявку
    graphic ~ вчт. графическое приложение
    high-volume ~ вчт. крупномасштабная прикладная система
    job ~ заявление о приеме на работу
    loan ~ заявка на получение ссуды
    low-volume ~ вчт. прикладная малопроизводительная система
    make an ~ подавать заявление
    managerial ~ применение компьютера в управлении
    off-line ~ вчт. автономная прикладная система off-line ~ вчт. система в автономном режиме
    original ~ оригинал заявления
    originating ~ заявление, начинающее судебный процесс originating ~ письменная жалоба originating ~ повестка в суд
    parent ~ основная патентная заявка parent ~ первичная патентная заявка
    ~ заявление;
    прошение;
    to put in an application подать заявление
    real-time ~ вчт. прикладная система реального времени
    refuse an ~ отклонять заявление
    refused loan ~ отклоненная заявка на получение ссуды
    scientific ~ вчт. исследовательская прикладная система
    single-remote ~ вчт. автономная система
    submit an ~ подавать заявку
    time-sharing ~ вчт. прикладная система разделения времени
    written ~ письменное заявление

    Большой англо-русский и русско-английский словарь > application

  • 2 application

    [ˌæplɪ'keɪʃ(ə)n]
    сущ.
    1) просьба; заявление; форма заявления

    to file / make / put in / send in / submit an application — подавать заявление, подавать прошение

    to reject application / turn down application — отказать в прошении

    He filed an application to be admitted to the intensive course. — Он подал заявление о приёме на интенсивный курс.

    Syn:
    2) применение, использование, употребление; приложение; применимость
    Syn:
    3) прикладывание, накладывание; нанесение
    4) мат. наложение

    Rheumatic pains cured by the application of spirits of camphor. — Ревматические боли снимаются при помощи камфарного компресса.

    8) прилежание, старание, усердие
    Syn:
    9) информ. прикладная программа, пакет, приложение

    Англо-русский современный словарь > application

  • 3 Taylor, Frederick Winslow

    [br]
    b. 20 March 1856 Germantown, Pennsylvania, USA
    d. 21 March 1915 Philadelphia, Pennsylvania, USA
    [br]
    American mechanical engineer and pioneer of scientific management.
    [br]
    Frederick W.Taylor received his early education from his mother, followed by some years of schooling in France and Germany. Then in 1872 he entered Phillips Exeter Academy, New Hampshire, to prepare for Harvard Law School, as it was intended that he should follow his father's profession. However, in 1874 he had to abandon his studies because of poor eyesight, and he began an apprenticeship at a pump-manufacturing works in Philadelphia learning the trades of pattern-maker and machinist. On its completion in 1878 he joined the Midvale Steel Company, at first as a labourer but then as Shop Clerk and Foreman, finally becoming Chief Engineer in 1884. At the same time he was able to resume study in the evenings at the Stevens Institute of Technology, and in 1883 he obtained the degree of Mechanical Engineer (ME). He also found time to take part in amateur sport and in 1881 he won the tennis doubles championship of the United States.
    It was while with the Midvale Steel Company that Taylor began the systematic study of workshop management, and the application of his techniques produced significant increases in the company's output and productivity. In 1890 he became Manager of a company operating large paper mills in Maine and Wisconsin, until 1893 when he set up on his own account as a consulting engineer specializing in management organization. In 1898 he was retained exclusively by the Bethlehem Steel Company, and there continued his work on the metal-cutting process that he had started at Midvale. In collaboration with J.Maunsel White (1856–1912) he developed high-speed tool steels and their heat treatment which increased cutting capacity by up to 300 per cent. He resigned from the Bethlehem Steel Company in 1901 and devoted the remainder of his life to expounding the principles of scientific management which became known as "Taylorism". The Society to Promote the Science of Management was established in 1911, renamed the Taylor Society after his death. He was an active member of the American Society of Mechanical Engineers and was its President in 1906; his presidential address "On the Art of Cutting Metals" was reprinted in book form.
    [br]
    Principal Honours and Distinctions
    Paris Exposition Gold Medal 1900. Franklin Institute Elliott Cresson Gold Medal 1900. President, American Society of Mechanical Engineers 1906. Hon. ScD, University of Pennsylvania 1906. Hon. LLD, Hobart College 1912.
    Bibliography
    F.W.Taylor was the author of about 100 patents, several papers to the American Society of Mechanical Engineers, On the Art of Cutting Metals (1907, New York) and The Principles of Scientific Management (1911, New York) and, with S.E.Thompson, 1905 A Treatise on Concrete, New York, and Concrete Costs, 1912, New York.
    Further Reading
    The standard biography is Frank B.Copley, 1923, Frederick W.Taylor, Father of Scientific Management, New York (reprinted 1969, New York) and there have been numerous commentaries on his work: see, for example, Daniel Nelson, 1980, Frederick W.Taylor and the Rise of Scientific Management, Madison, Wis.
    RTS

    Biographical history of technology > Taylor, Frederick Winslow

  • 4 Millington, John

    [br]
    b. 1779
    d. 1868
    [br]
    English engineer and educator.
    [br]
    John Millington was Professor of Mechanics at the Royal Institution, London, from 1817 to 1829. He gave numerous courses on natural philosophy and mechanics and supported the introduction of coal gas for lighting. In 1823 he testified to a Select Committee of the House of Commons that the spread of gas lighting would greatly benefit the preservation of law and order, and with the same utilitarian and penal inclination he devised a treadmill for use in the Bedfordshire House of Correction. Millington was appointed the first Professor of Engineering and the Application of Mechanical Philosophy to the Arts at the newly founded University of London in 1828, but he speedily resigned from the post, preferring to go to Mexico in 1829. Like Trevithick and Robert Stephenson before him, he was attracted to the New World by the possibility of using new techniques to reopen old mines, and he became an engineer to some Mexican mining projects. In 1837 he went to Williamsburg in the United States, being appointed Professor of Chemistry, and it was there that he died in 1868. Millington wrote extensively on scientific subjects.
    [br]
    Further Reading
    Dictionary of National Biography.
    M.Berman, The Royal Institution, pp. 46, 98–9.
    AB

    Biographical history of technology > Millington, John

  • 5 внедрение

    ср.
    1) introduction;
    inculcation;
    implantation внедрение достижений науки в производство ≈ application of the achievements of science to production
    2) геол. intrusion
    с.
    1. inculcation, adoption;
    ~ передового опыта introduction of advanced know-how;
    ~ новой техники inculcation of new techniques;
    ~ в производство достижений науки adoption of scientific achievements in industry;

    2. геол. intrusion.

    Большой англо-русский и русско-английский словарь > внедрение

  • 6 Kennelly, Arthur Edwin

    [br]
    b. 17 December 1871 Colaba, Bombay, India
    d. 18 June 1939 Boston, Massachusetts, USA
    [br]
    Anglo-American electrical engineer who predicted the ionosphere and developed mathematical analysis for electronic circuits.
    [br]
    As a young man, Kennelly worked as office boy for a London engineering society, as an electrician and on a cable-laying ship. In 1887 he went to work for Thomas Edison at West Orange, New Jersey, USA, becoming his chief assistant. In 1894, with Edwin J.Houston, he formed the Philadelphia company of Houston and Kennelly, but eight years later he took up the Chair of Electrical Engineering at Harvard, a post he held until his retirement in 1930. In 1902 he noticed that the radio signals received by Marconi in Nova Scotia from the transmitter in England were stronger than predicted and postulated a reflecting ionized layer in the upper atmosphere. Almost simultaneously the same prediction was made in England by Heaviside, so the layer became known as the Kennelly-Heaviside layer. Throughout most of his working life Kennelly was concerned with the application of mathematical techniques, particularly the use of complex theory, to the analysis of electrical circuits. With others he also contributed to an understanding of the high-frequency skin-effect in conductors.
    [br]
    Principal Honours and Distinctions
    President, American Institute of Electrical Engineers 1898–1900. President, Institution of Electrical Engineers 1916. Institute of Electrical and Electronics Engineers Medal of Honour 1932; Edison Medal 1933.
    Bibliography
    1915, with F.A.Laws \& P.H.Pierce "Experimental research on the skin effect in conductors", Transactions of the American Institute of Electrical Engineers 34:1,953.
    1924, Hyperbolic Functions as Applied to Electrical Engineering.
    1924, Check Atlas of Complex Hyperbolic \& Circular Functions (both on mathematics for circuit analysis).
    Further Reading
    K.Davies, 1990, Ionospheric Radio, London: Peter Peregrinus. See also Appleton, Sir Edward Victor.
    KF

    Biographical history of technology > Kennelly, Arthur Edwin

  • 7 kaizen

    Gen Mgt, Ops
    the Japanese term for the continuous improvement of current processes. Kaizen is derived from the words “kai,” meaning “change,” and “zen,” meaning “good” or “for the better.” It is a philosophy that can be applied to any area of life, but its application has been most famously developed at the Toyota Motor Company, and it underlies the philosophy of total quality management. Under kaizen, continuous improvement can mean waste elimination, innovation, or working to new standards. The kaizen process makes use of a range of techniques, including small-group problem solving, statistical techniques, brainstorming, and work study. Although kaizen forms only part of a strategy of continuous improvement, for many employees it is the element that most closely affects them and is therefore synonymous with continuous improvement.

    The ultimate business dictionary > kaizen

  • 8 Senefelder, Alois

    SUBJECT AREA: Paper and printing
    [br]
    b. 6 November 1771 Prague, Bohemia (now Czech Republic)
    d. 26 February 1834 Munich, Germany
    [br]
    German inventor of lithography.
    [br]
    Soon after his birth, Senefelder's family moved to Mannheim, where his father, an actor, had obtained a position in the state theatre. He was educated there, until he gained a scholarship to the university of Ingolstadt. The young Senefelder wanted to follow his father on to the stage, but the latter insisted that he study law. He nevertheless found time to write short pieces for the theatre. One of these, when he was 18 years old, was an encouraging success. When his father died in 1791, he gave up his studies and took to a new life as poet and actor. However, the wandering life of a repertory actor palled after two years and he settled for the more comfortable pursuit of playwriting. He had some of his work printed, which acquainted him with the art of printing, but he fell out with his bookseller. He therefore resolved to carry out his own printing, but he could not afford the equipment of a conventional letterpress printer. He began to explore other ways of printing and so set out on the path that was to lead to an entirely new method.
    He tried writing in reverse on a copper plate with some acid-resisting material and etching the plate, to leave a relief image that could then be inked and printed. He knew that oily substances would resist acid, but it required many experiments to arrive at a composition of wax, soap and charcoal dust dissolved in rainwater. The plates wore down with repeated polishing, so he substituted stone plates. He continued to etch them and managed to make good prints with them, but he went on to make the surprising discovery that etching was unnecessary. If the image to be printed was made with the oily composition and the stone moistened, he found that only the oily image received the ink while the moistened part rejected it. The printing surface was neither raised (as in letterpress printing) nor incised (as in intaglio printing): Senefelder had discovered the third method of printing.
    He arrived at a workable process over the years 1796 to 1799, and in 1800 he was granted an English patent. In the same year, lithography (or "writing on stone") was introduced into France and Senefelder himself took it to England, but it was some time before it became widespread; it was taken up by artists especially for high-quality printing of art works. Meanwhile, Senefelder improved his techniques, finding that other materials, even paper, could be used in place of stone. In fact, zinc plates were widely used from the 1820s, but the name "lithography" stuck. Although he won world renown and was honoured by most of the crowned heads of Europe, he never became rich because he dissipated his profits through restless experimenting.
    With the later application of the offset principle, initiated by Barclay, lithography has become the most widely used method of printing.
    [br]
    Bibliography
    1911, Alois Senefelder, Inventor of Lithography, trans. J.W.Muller, New York: Fuchs \& Line (Senefelder's autobiography).
    Further Reading
    W.Weber, 1981, Alois Senefelder, Erfinder der Lithographie, Frankfurt-am-Main: Polygraph Verlag.
    M.Tyman, 1970, Lithography 1800–1950, London: Oxford University Press (describes the invention and its development; with biographical details).
    LRD

    Biographical history of technology > Senefelder, Alois

  • 9 Artificial Intelligence

       In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)
       Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)
       Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....
       When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)
       4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually
       Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)
       Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)
       What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)
       [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)
       The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)
       9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form
       The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)
       There are many different kinds of reasoning one might imagine:
        Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."
        Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)
       Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)
       Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)
       The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)
        14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation
       It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)
       We might distinguish among four kinds of AI.
       Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.
       Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.
    ... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)
       Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)
        16) Determination of Relevance of Rules in Particular Contexts
       Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)
       Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)
        18) The Assumption That the Mind Is a Formal System
       Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)
        19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence
       The primary goal of Artificial Intelligence is to make machines smarter.
       The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)
       The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....
       AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)
        21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions
       In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)
       Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)
       Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)
       The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

    Historical dictionary of quotations in cognitive science > Artificial Intelligence

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