1972-1979+xx

SUBJECT AREA: Electricity

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After graduating from Keble College, Oxford, Rawcliffe joined the Metropolitan Vickers Electrical Company in 1932 as a college apprentice, and later became a design engineer. This was followed by a period as a lecturer at Liverpool University, where he was able to extend his knowledge of the principles underlying the design and operation of electrical machines. In 1941 he became Head of the Electrical Engineering Department at the Robert Gordon Technical College, Aberdeen, and Lecturer in charge of Electrical Engineering at Aberdeen University. In 1944 Rawcliffe was appointed to the Chair of Electrical Engineering at the University of Bristol, where he remained until his retirement in 1975. The reputation of his department was enhanced by the colleagues he recruited.

After 1954 he began research into polyphase windings, the basis of alternating-current machinery, and published papers concerned with the dual problems of frequency changing and pole changing. The result of this research was the discovery in 1957 of a technique for making squirrel-cage induction motors run at more than one speed. By reversing current in one part of the winding, the pole distribution and number were changed, and with it the speed of rotation.

Rawcliffe's name became synonymous with pole amplitude modulation, or PAM, the name given to this technique. Described by Rawcliffe as a new philosophy of windings, the technique led to a series of research papers, patents and licensing agreements in addition to consultancies to advise on application problems. Commercial exploitation of the new idea throughout Western Europe, the United Kingdom and the United States followed. In total he contributed twentyfive papers to the Proceedings of the Institution of Electrical Engineers and some sixty British patent applications were filed.

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SUBJECT AREA: Electronics and information technology, Horology, Land transport

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The son of G.W.C.Sinclair, a machine tool engineer, the young Sinclair's education was disrupted by the failure of his father's business. Aged 12 he left Boxgrove preparatory school and went through twelve more schools before leaving St George's School, Weybridge, at the age of 17. His first job was as an editorial assistant on a hobbyist's magazine, Practical Wireless, and his next as an editor at Bernard Books, writing a series of technical manuals. In 1961 he registered Sinclair Radionics and in the following year announced its first product, a micro-amplifier. This was the first of a series of miniaturized radio products that he put on the market while retaining his editorial job. In 1972 he launched the Sinclair Executive calculator, selling originally at £79.95 but later at £24.95. In 1976, the Black Watch, an electronic watch with digital light-emitting diode (LED) display, was marketed, to be followed by the TV1A, a miniature television with a 2 in. (5 cm) monochrome screen. During the latter part of this period, Sinclair Radionics was supported by investment from the UK National Enterprise Board, who appointed an outside managing director; after making a considerable loss, they closed the company in 1979. However, Sinclair Electronics had already been set up and started to market the UK's first cheap computer kit, the MK 14, which was followed by the ZX 80 and later the ZX 81. Price was kept at a minimum by the extensive use of existing components, though this was a restriction on performance. The small memory was enhanced from one kilobyte to seventeen kilobytes with the addition of a separate memory unit. In January 1985 Sinclair produced the Sinclair C5, a small three-wheeled vehicle driven by a washing-machine engine, intended as a revolutionary new form of personal transport; perceived as unsafe and impractical, it did not prove popular, and the failure of this venture resulted in a contraction of Sinclair's business activities. Later in 1985, a rival electronics company, Amstrad, paid £35,000,000 for all rights to existing Sinclair computer products.

In March 1992, the irrepressible Sinclair launched his latest brainchild, the Zike electric bicycle; a price of £499 was forecast. This machine, powered by an electric motor but with pedal assistance, had a top speed of 19 km/h (12 mph) and, on full power, would run for up to one hour. Its lightweight nickel-cadmium battery could be recharged either by a generator or by free-wheeling. Although more practical than the C5, it did not bring Sinclair success on the scale of his earlier micro-electronic products.

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Канарський, Анатолій Станіславович (1936, с. Руднє-Грабовка Житомирської обл. - 1984) - укр. філософ. Закінчив філософський ф-т КНУ ім. Т. Шевченка (1966). Докт. філософських наук (1983), проф. У1966 - 1984 рр. -асист., ст. викл., доц., проф. кафедри етики й естетики філософського ф-ту КНУ ім. Т. Шевченка Ф. ілософський здобуток К. охоплює ґрунтовний аналіз природи й форм естетичної чуттєвості, генези естетичної культури, взаємозв'язку історичної життєдіяльності та естетичної свідомості індивіда, нового понятійно-категоріального апарату естетичної науки.

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Осн. тв.: "Практика і естетична свідомість" (1972); "Суб'єкт і об'єкт як філософська проблема", у співавт. (1978); "Діалектика естетичного як теорія чуттєвого пізнання" (1979); "Діалектика естетичного процесу: генеза чуттєвої культури" (1982) та ін.

Маркузе, Герберт (1898, Берлін - 1979) - нім.-амер. філософ, соціолог. Захистив докт. дисертацію в галузі літератури (1922); од 1934 р. - у США. Початковий період філософської творчості М. був позначений впливом ідей Гайдеггера, особливо щодо "закинутості" індивіда у світ об'єктів та, відповідно, його уподібнення об'єктові (пізніше ця ідея частково оприявнилася у соціологізованому вигляді в концепції "одновимірної людини"). Проте домінантним для цього періоду був вплив Маркса. Аргументація стосовно вкоріненості індивіда в соціально-економічній структурі суспільства, а також характерний для філософії Франкфуртської школи (див. Адорно, Горкгаймер), до якої М. приєднався у 1933 р., дали підстави для тлумачення філософії М. як "не-радянського" марксизму. Синтезувавши частково психологічні ідеї фройдизму (у повоєнні роки), соціальна філософія М. стала підмурівком для активного продукування ідей про соціальне лідерство у суспільстві у період його вірогідних докорінних трансформацій З. гідно з М., такі прошарки, як студентство, гуманітарна інтелігенція, соціальні аутсайдери (люмпени, безробітні, гноблені національні меншини) мають замінити пролетаріат, який остаточно адаптувався до капіталістичної системи В. ивільнення інстинктів, пригнічених за капіталізму, відкриває перспективу нового життя - на основі розкутої чуттєвості, злагоди й краси. Одна із засадничих ідей естетичної теорії М. полягала у тому, що чуттєве виявлення краси у творах мистецтва сприяє запобіганню гнітові репресивних сил сьогодення, нагадуючи про можливий вільний спосіб життя.

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Осн. тв.: "Одновимірна людина" (1964); "Нариси про свободу" (1969); "Контрреволюція і бунт" (1972).

РИМСЬКИЙ КЛУБ - міжнародне неурядове науково-дослідницьке об'єднання інтелектуальної еліти Заходу, відомих вчених-глобалістів, громадських діячів та політиків (значна частина яких були лауреатами Нобелівської премії), засноване у Римі (1968) за ініціативою італ. економіста і менеджера Печчеї (засновник і перший президент клубу). Науково-дослідницькі напрями роботи Р. к. охоплювали наступне коло проблем: - критичний аналіз стратегій розвитку західної і загалом світової цивілізації в цілому; - обґрунтування неефективності й небезпечності неоколоніальної системи; - пошук можливих альтернатив розвитку людства та ефективних засобів гуманізації соціуму в сучасних умовах; - аргументація безперспективності й абсурдності гонки озброєнь; - об'єднання зусиль світової громадськості задля збереження довкілля й досягнення соціальної справедливості в глобальному масштабі. Значний резонанс світової громадськості викликали роботи, виконані в жанрі "Доповіді Римського клубу": "Межі росту" - 1972 (Деніс Л. Медоуз, Донела Медоуз та ін.); "Людство на роздоріжжі" - 1974 (Месарович, Пестель); "Перегляд міжнародного порядку" - 1976 (Тинберген); "За межами віку марнотратства" - 1976 (Коломбі, Габор); "Цілі для людства" - 1977 (Ласло); "Енергія: зворотний рахунок" - 1978 (Монбріаль); "Нема меж освіті: подолання розриву в рівні освіти людей" - 1979 (Маліца, Боткін, Ельманджрі); "Третій світ: три четверті світу" - 1980 (Гарньє); "Діалоги про багатство і добробут" - 1980 (Джоріні); "Дороговкази в майбутнє" - 1981 (Гаврилишин); "За межами росту" - 1987 (Пестель)та ін. Крім того, відомими й авторитетними у всьому світі стали роботи членів клубу Форрестера "Світова динаміка" (1971), Кінга "Новий поріг" (1973), Зиблера та Кайя "Доповідь із Токіо" (1974) та ін. Оприлюднення як першої, так і наступної "Доповідей" викликало бурхливу дискусію в усьому світі, яка продовжується й зараз, та суттєво активізувало обговорення порушених проблем. У "Доповідях" була створена глобальна математична модель дослідження "світового порядку", значно розширений діапазон досліджень, зокрема задіяні головні чинники соціогуманітарного характеру. Останнім часом особлива увага приділяється етнічним, економічним та культурним аспектам розвитку. Гаврилишин, зокрема, пропонує враховувати специфіку релігійних вірувань та "наснагу до праці" Д. ля визначення перспектив формування "нового світового порядку" залучається якісний аналіз стану освіти в тому чи іншому регіоні, всебічно досліджується науково-технічний потенціал планети і можливість його ефективного використання для розв'язання енергетичних, сировинних, продовольчих, демографічних та екологічних проблем. Головною стратегемою досліджень членів Р. к. стає пошук шляхів та засобів задоволення елементарних потреб населення Землі, забезпечення "гідного життя і помірного добробуту для усіх громадян світу" (Тінберген).

   1) The Basic Idea of Cognitive Science

   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.... [P]eople and intelligent computers turn out to be merely different manifestations of the same underlying phenomenon. (Haugeland, 1981b, p. 31)

   2) Experimental Psychology, Theoretical Linguistics, and Computational Simulation of Cognitive Processes Are All Components of Cognitive Science

   I went away from the Symposium with a strong conviction, more intuitive than rational, that human experimental psychology, theoretical linguistics, and computer simulation of cognitive processes were all pieces of a larger whole, and that the future would see progressive elaboration and coordination of their shared concerns.... I have been working toward a cognitive science for about twenty years beginning before I knew what to call it. (G. A. Miller, 1979, p. 9)

   3) The Nature of Cognitive Science

    Cognitive Science studies the nature of cognition in human beings, other animals, and inanimate machines (if such a thing is possible). While computers are helpful within cognitive science, they are not essential to its being. A science of cognition could still be pursued even without these machines.

    Computer Science studies various kinds of problems and the use of computers to solve them, without concern for the means by which we humans might otherwise resolve them. There could be no computer science if there were no machines of this kind, because they are indispensable to its being. Artificial Intelligence is a special branch of computer science that investigates the extent to which the mental powers of human beings can be captured by means of machines.

   There could be cognitive science without artificial intelligence but there could be no artificial intelligence without cognitive science. One final caveat: In the case of an emerging new discipline such as cognitive science there is an almost irresistible temptation to identify the discipline itself (as a field of inquiry) with one of the theories that inspired it (such as the computational conception...). This, however, is a mistake. The field of inquiry (or "domain") stands to specific theories as questions stand to possible answers. The computational conception should properly be viewed as a research program in cognitive science, where "research programs" are answers that continue to attract followers. (Fetzer, 1996, pp. xvi-xvii)

   4) The Nature of Cognitive Science

   What is the nature of knowledge and how is this knowledge used? These questions lie at the core of both psychology and artificial intelligence.

   The psychologist who studies "knowledge systems" wants to know how concepts are structured in the human mind, how such concepts develop, and how they are used in understanding and behavior. The artificial intelligence researcher wants to know how to program a computer so that it can understand and interact with the outside world. The two orientations intersect when the psychologist and the computer scientist agree that the best way to approach the problem of building an intelligent machine is to emulate the human conceptual mechanisms that deal with language.... The name "cognitive science" has been used to refer to this convergence of interests in psychology and artificial intelligence....

   This working partnership in "cognitive science" does not mean that psychologists and computer scientists are developing a single comprehensive theory in which people are no different from machines. Psychology and artificial intelligence have many points of difference in methods and goals.... We simply want to work on an important area of overlapping interest, namely a theory of knowledge systems. As it turns out, this overlap is substantial. For both people and machines, each in their own way, there is a serious problem in common of making sense out of what they hear, see, or are told about the world. The conceptual apparatus necessary to perform even a partial feat of understanding is formidable and fascinating. (Schank & Abelson, 1977, pp. 1-2)

   5) The New Field of Cognitive Science

   Within the last dozen years a general change in scientific outlook has occurred, consonant with the point of view represented here. One can date the change roughly from 1956: in psychology, by the appearance of Bruner, Goodnow, and Austin's Study of Thinking and George Miller's "The Magical Number Seven"; in linguistics, by Noam Chomsky's "Three Models of Language"; and in computer science, by our own paper on the Logic Theory Machine. (Newell & Simon, 1972, p. 4)

   1) A Comparison of the Digital Computer and the Brain

   The brain has been compared to a digital computer because the neuron, like a switch or valve, either does or does not complete a circuit. But at that point the similarity ends. The switch in the digital computer is constant in its effect, and its effect is large in proportion to the total output of the machine. The effect produced by the neuron varies with its recovery from [the] refractory phase and with its metabolic state. The number of neurons involved in any action runs into millions so that the influence of any one is negligible.... Any cell in the system can be dispensed with.... The brain is an analogical machine, not digital. Analysis of the integrative activities will probably have to be in statistical terms. (Lashley, quoted in Beach, Hebb, Morgan & Nissen, 1960, p. 539)

   2) Computers Do Not Crunch Numbers, They Manipulate Symbols

   It is essential to realize that a computer is not a mere "number cruncher," or supercalculating arithmetic machine, although this is how computers are commonly regarded by people having no familiarity with artificial intelligence. Computers do not crunch numbers; they manipulate symbols.... Digital computers originally developed with mathematical problems in mind, are in fact general purpose symbol manipulating machines....

   The terms "computer" and "computation" are themselves unfortunate, in view of their misleading arithmetical connotations. The definition of artificial intelligence previously cited-"the study of intelligence as computation"-does not imply that intelligence is really counting. Intelligence may be defined as the ability creatively to manipulate symbols, or process information, given the requirements of the task in hand. (Boden, 1981, pp. 15, 16-17)

   3) Getting Computers to Explain Things to Themselves

   The task is to get computers to explain things to themselves, to ask questions about their experiences so as to cause those explanations to be forthcoming, and to be creative in coming up with explanations that have not been previously available. (Schank, 1986, p. 19)

   4) Some Limits of Artificial Intelligence

   In What Computers Can't Do, written in 1969 (2nd edition, 1972), the main objection to AI was the impossibility of using rules to select only those facts about the real world that were relevant in a given situation. The "Introduction" to the paperback edition of the book, published by Harper & Row in 1979, pointed out further that no one had the slightest idea how to represent the common sense understanding possessed even by a four-year-old. (Dreyfus & Dreyfus, 1986, p. 102)

   5) The Computer as a Humanizing Influence

   A popular myth says that the invention of the computer diminishes our sense of ourselves, because it shows that rational thought is not special to human beings, but can be carried on by a mere machine. It is a short stop from there to the conclusion that intelligence is mechanical, which many people find to be an affront to all that is most precious and singular about their humanness.

   In fact, the computer, early in its career, was not an instrument of the philistines, but a humanizing influence. It helped to revive an idea that had fallen into disrepute: the idea that the mind is real, that it has an inner structure and a complex organization, and can be understood in scientific terms. For some three decades, until the 1940s, American psychology had lain in the grip of the ice age of behaviorism, which was antimental through and through. During these years, extreme behaviorists banished the study of thought from their agenda. Mind and consciousness, thinking, imagining, planning, solving problems, were dismissed as worthless for anything except speculation. Only the external aspects of behavior, the surface manifestations, were grist for the scientist's mill, because only they could be observed and measured....

   It is one of the surprising gifts of the computer in the history of ideas that it played a part in giving back to psychology what it had lost, which was nothing less than the mind itself. In particular, there was a revival of interest in how the mind represents the world internally to itself, by means of knowledge structures such as ideas, symbols, images, and inner narratives, all of which had been consigned to the realm of mysticism. (Campbell, 1989, p. 10)

   6) The Intentionality of Computers Is Essentially Borrowed, Hence Derivative

   [Our artifacts] only have meaning because we give it to them; their intentionality, like that of smoke signals and writing, is essentially borrowed, hence derivative. To put it bluntly: computers themselves don't mean anything by their tokens (any more than books do)-they only mean what we say they do. Genuine understanding, on the other hand, is intentional "in its own right" and not derivatively from something else. (Haugeland, 1981a, pp. 32-33)

   7) The Possibility of Computer Thought

   he debate over the possibility of computer thought will never be won or lost; it will simply cease to be of interest, like the previous debate over man as a clockwork mechanism. (Bolter, 1984, p. 190)

   8) We Are Getting Better at Building Even Better Computers, an Ever- Escalating Upward Spiral

   t takes us a long time to emotionally digest a new idea. The computer is too big a step, and too recently made, for us to quickly recover our balance and gauge its potential. It's an enormous accelerator, perhaps the greatest one since the plow, twelve thousand years ago. As an intelligence amplifier, it speeds up everything-including itself-and it continually improves because its heart is information or, more plainly, ideas. We can no more calculate its consequences than Babbage could have foreseen antibiotics, the Pill, or space stations.

   According to weak AI, the principle value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion than before. But according to strong AI the computer is not merely a tool in the study of the mind; rather the appropriately programmed computer really is a mind in the sense that computers given the right programs can be literally said to understand and have other cognitive states. And according to strong AI, because the programmed computer has cognitive states, the programs are not mere tools that enable us to test psychological explanations; rather, the programs are themselves the explanations. (Searle, 1981b, p. 353)

    10) Why People Are Smarter Than Computers

   What makes people smarter than machines? They certainly are not quicker or more precise. Yet people are far better at perceiving objects in natural scenes and noting their relations, at understanding language and retrieving contextually appropriate information from memory, at making plans and carrying out contextually appropriate actions, and at a wide range of other natural cognitive tasks. People are also far better at learning to do these things more accurately and fluently through processing experience.

   What is the basis for these differences? One answer, perhaps the classic one we might expect from artificial intelligence, is "software." If we only had the right computer program, the argument goes, we might be able to capture the fluidity and adaptability of human information processing. Certainly this answer is partially correct. There have been great breakthroughs in our understanding of cognition as a result of the development of expressive high-level computer languages and powerful algorithms. However, we do not think that software is the whole story.

   In our view, people are smarter than today's computers because the brain employs a basic computational architecture that is more suited to deal with a central aspect of the natural information processing tasks that people are so good at.... hese tasks generally require the simultaneous consideration of many pieces of information or constraints. Each constraint may be imperfectly specified and ambiguous, yet each can play a potentially decisive role in determining the outcome of processing. (McClelland, Rumelhart & Hinton, 1986, pp. 3-4)