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lack-brain

  • 1 lack-brain

    lack-brain noun obs. дурак

    Англо-русский словарь Мюллера > lack-brain

  • 2 lack-brain

    ˈlækbreɪn сущ.;
    уст. дурак Syn: fool n уст. дурак

    Большой англо-русский и русско-английский словарь > lack-brain

  • 3 lack-brain

    [`lækbreɪn]
    дурак

    Англо-русский большой универсальный переводческий словарь > lack-brain

  • 4 lack-brain

    n розм.
    дурень, недоумкуватий, безмозкий

    English-Ukrainian dictionary > lack-brain

  • 5 lack brain

    дурак

    Новый англо-русский словарь > lack brain

  • 6 lack-brain

    малоумный
    полоумный
    скудоумен
    скудоумный
    слабоумен
    слабоумный

    Новый англо-русский словарь > lack-brain

  • 7 lack-brain

    ['lækbreɪn]
    n розм.
    ду́рень, недоу́мкуватий

    English-Ukrainian transcription dictionary > lack-brain

  • 8 lack-brain

    ['lækbreɪn]
    сущ.; уст.
    Syn:

    Англо-русский современный словарь > lack-brain

  • 9 lack-brain

    малоумный
    полоумный
    скудоумен
    скудоумный
    слабоумен
    слабоумный

    English-Russian smart dictionary > lack-brain

  • 10 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

  • 11 Consciousness

       Consciousness is what makes the mind-body problem really intractable.
    ... Without consciousness the mind-body problem would be much less interesting. With consciousness it seems hopeless. (T. Nagel, 1979, pp. 165-166)
       This approach to understanding sensory qualia is both theoretically and empirically motivated... [;] it suggests an effective means of expressing the allegedly inexpressible. The "ineffable" pink of one's current visual sensation may be richly and precisely expressed as a 95Hz/80Hz/80Hz "chord" in the relevant triune cortical system. The "unconveyable" taste sensation produced by the fabled Australian health tonic Vegamite might be poignantly conveyed as a 85/80/90/15 "chord" in one's four channeled gustatory system.... And the "indescribably" olfactory sensation produced by a newly opened rose might be quite accurately described as a 95/35/10/80/60/55 "chord" in some six-dimensional space within one's olfactory bulb. (P. M. Churchland, 1989, p. 106)
       One of philosophy's favorite facets of mentality has received scant attention from cognitive psychologists, and that is consciousness itself: fullblown, introspective, inner-world phenomenological consciousness. In fact if one looks in the obvious places... one finds not so much a lack of interest as a deliberate and adroit avoidance of the issue. I think I know why. Consciousness appears to be the last bastion of occult properties, epiphenomena, and immeasurable subjective states-in short, the one area of mind best left to the philosophers, who are welcome to it. Let them make fools of themselves trying to corral the quicksilver of "phenomenology" into a respectable theory. (Dennett, 1978b, p. 149)
       When I am thinking about anything, my consciousness consists of a number of ideas.... But every idea can be resolved into elements... and these elements are sensations. (Titchener, 1910, p. 33)
       A Darwin machine now provides a framework for thinking about thought, indeed one that may be a reasonable first approximation to the actual brain machinery underlying thought. An intracerebral Darwin Machine need not try out one sequence at a time against memory; it may be able to try out dozens, if not hundreds, simultaneously, shape up new generations in milliseconds, and thus initiate insightful actions without overt trial and error. This massively parallel selection among stochastic sequences is more analogous to the ways of darwinian biology than to the "von Neumann" serial computer. Which is why I call it a Darwin Machine instead; it shapes up thoughts in milliseconds rather than millennia, and uses innocuous remembered environments rather than noxious real-life ones. It may well create the uniquely human aspect of our consciousness. (Calvin, 1990, pp. 261-262)
       To suppose the mind to exist in two different states, in the same moment, is a manifest absurdity. To the whole series of states of the mind, then, whatever the individual, momentary successive states may be, I give the name of our consciousness.... There are not sensations, thoughts, passions, and also consciousness, any more than there is quadruped or animal, as a separate being to be added to the wolves, tygers, elephants, and other living creatures.... The fallacy of conceiving consciousness to be something different from the feeling, which is said to be its object, has arisen, in a great measure, from the use of the personal pronoun I. (T. Brown, 1970, p. 336)
       The human capacity for speech is certainly unique. But the gulf between it and the behavior of animals no longer seems unbridgeable.... What does this leave us with, then, which is characteristically human?.... t resides in the human capacity for consciousness and self-consciousness. (Rose, 1976, p. 177)
       [Human consciousness] depends wholly on our seeing the outside world in such categories. And the problems of consciousness arise from putting reconstitution beside internalization, from our also being able to see ourselves as if we were objects in the outside world. That is in the very nature of language; it is impossible to have a symbolic system without it.... The Cartesian dualism between mind and body arises directly from this, and so do all the famous paradoxes, both in mathematics and in linguistics.... (Bronowski, 1978, pp. 38-39)
       It seems to me that there are at least four different viewpoints-or extremes of viewpoint-that one may reasonably hold on the matter [of computation and conscious thinking]:
       A. All thinking is computation; in particular, feelings of conscious awareness are evoked merely by the carrying out of appropriate computations.
       B. Awareness is a feature of the brain's physical action; and whereas any physical action can be simulated computationally, computational simulation cannot by itself evoke awareness.
       C. Appropriate physical action of the brain evokes awareness, but this physical action cannot even be properly simulated computationally.
       D. Awareness cannot be explained by physical, computational, or any other scientific terms. (Penrose, 1994, p. 12)

    Historical dictionary of quotations in cognitive science > Consciousness

  • 12 human

    1. adjective

    the human race — die menschliche Rasse

    I'm only human — ich bin auch nur ein Mensch

    be human! — sei kein Unmensch!; see also academic.ru/49183/nature">nature 4)

    2. noun
    Mensch, der
    * * *
    ['hju:mən] 1. adjective
    (of, natural to, concerning, or belonging to, mankind: human nature; The dog was so clever that he seemed almost human.) menschlich
    2. noun
    (a person: Humans are not as different from animals as we might think.) der Mensch
    - humanly
    - human being
    - human resources
    * * *
    hu·man
    [ˈhju:mən]
    I. n Mensch m
    II. adj behaviour, skeleton menschlich
    to form a \human chain eine Menschenkette bilden
    to be beyond \human power nicht in der Macht des Menschen liegen
    \human relationships/sexuality die Beziehungen/die Sexualität des Menschen
    * * *
    ['hjuːmən]
    1. adj
    menschlich; health, brain, part of the body des Menschen
    2. n
    Mensch m
    * * *
    human [ˈhjuːmən]
    A adj (adv → humanly)
    1. menschlich, Menschen…:
    I am only human ich bin auch nur ein Mensch;
    they’re only human too die kochen auch nur mit Wasser;
    that’s only human das ist doch menschlich;
    human being Mensch m;
    human chain Menschenkette f;
    human counter Human Counter m (der Strahlenschutzüberwachung dienendes Messgerät zur Bestimmung der vom menschlichen Körper aufgenommenen und wieder abgegebenen Strahlung);
    human dignity Menschenwürde f;
    human engineering Human Engineering n, Anthropotechnik f (Teilgebiet der Industrieanthropologie, das sich mit der Anpassung technischer Einrichtungen und Abläufe an die physischen, psychischen und sozialen Erfordernisse des Menschen befasst);
    human error menschliches Versagen;
    human flesh Menschenfleisch n;
    human history die Geschichte der Menschheit;
    human immunodeficiency virus MED humanes Immunschwächevirus;
    human interest (das) menschlich Ansprechende, (der) menschliche Aspekt;
    human-interest story ergreifende oder ein menschliches Schicksal behandelnde Geschichte;
    human medicine Humanmedizin f;
    human nature die menschliche Natur;
    it’s only human nature to do sth es ist nur allzu menschlich oder es liegt ganz einfach in der menschlichen Natur, etwas zu tun;
    human race Menschengeschlecht n;
    a) zwischenmenschliche Beziehungen,
    b) Human Relations, Kontaktpflege f;
    human resources pl Arbeitskräftepotential n;
    human resources department US Personalabteilung f;
    human rights Menschenrechte;
    human rights activist Menschenrechtler(in);
    human rights organization Menschenrechtsorganisation f;
    human touch menschliche Note; → err 1
    2. → humane 1
    B s Mensch m
    * * *
    1. adjective

    be human! — sei kein Unmensch!; see also nature 4)

    2. noun
    Mensch, der
    * * *
    adj.
    human adj.
    menschlich adj.

    English-german dictionary > human

  • 13 Intelligence

       There is no mystery about it: the child who is familiar with books, ideas, conversation-the ways and means of the intellectual life-before he begins school, indeed, before he begins consciously to think, has a marked advantage. He is at home in the House of intellect just as the stableboy is at home among horses, or the child of actors on the stage. (Barzun, 1959, p. 142)
       It is... no exaggeration to say that sensory-motor intelligence is limited to desiring success or practical adaptation, whereas the function of verbal or conceptual thought is to know and state truth. (Piaget, 1954, p. 359)
       ntelligence has two parts, which we shall call the epistemological and the heuristic. The epistemological part is the representation of the world in such a form that the solution of problems follows from the facts expressed in the representation. The heuristic part is the mechanism that on the basis of the information solves the problem and decides what to do. (McCarthy & Hayes, 1969, p. 466)
       Many scientists implicitly assume that, among all animals, the behavior and intelligence of nonhuman primates are most like our own. Nonhuman primates have relatively larger brains and proportionally more neocortex than other species... and it now seems likely that humans, chimpanzees, and gorillas shared a common ancestor as recently as 5 to 7 million years ago.... This assumption about the unique status of primate intelligence is, however, just that: an assumption. The relations between intelligence and measures of brain size is poorly understood, and evolutionary affinity does not always ensure behavioral similarity. Moreover, the view that nonhuman primates are the animals most like ourselves coexists uneasily in our minds with the equally pervasive view that primates differ fundamentally from us because they lack language; lacking language, they also lack many of the capacities necessary for reasoning and abstract thought. (Cheney & Seyfarth, 1990, p. 4)
       Few constructs are asked to serve as many functions in psychology as is the construct of human intelligence.... Consider four of the main functions addressed in theory and research on intelligence, and how they differ from one another.
       1. Biological. This type of account looks at biological processes. To qualify as a useful biological construct, intelligence should be a biochemical or biophysical process or at least somehow a resultant of biochemical or biophysical processes.
       2. Cognitive approaches. This type of account looks at molar cognitive representations and processes. To qualify as a useful mental construct, intelligence should be specifiable as a set of mental representations and processes that are identifiable through experimental, mathematical, or computational means.
       3. Contextual approaches. To qualify as a useful contextual construct, intelligence should be a source of individual differences in accomplishments in "real-world" performances. It is not enough just to account for performance in the laboratory. On [sic] the contextual view, what a person does in the lab may not even remotely resemble what the person would do outside it. Moreover, different cultures may have different conceptions of intelligence, which affect what would count as intelligent in one cultural context versus another.
       4. Systems approaches. Systems approaches attempt to understand intelligence through the interaction of cognition with context. They attempt to establish a link between the two levels of analysis, and to analyze what forms this link takes. (Sternberg, 1994, pp. 263-264)
       High but not the highest intelligence, combined with the greatest degrees of persistence, will achieve greater eminence than the highest degree of intelligence with somewhat less persistence. (Cox, 1926, p. 187)
       There are no definitive criteria of intelligence, just as there are none for chairness; it is a fuzzy-edged concept to which many features are relevant. Two people may both be quite intelligent and yet have very few traits in common-they resemble the prototype along different dimensions.... [Intelligence] is a resemblance between two individuals, one real and the other prototypical. (Neisser, 1979, p. 185)
       Given the complementary strengths and weaknesses of the differential and information-processing approaches, it should be possible, at least in theory, to synthesise an approach that would capitalise upon the strength of each approach, and thereby share the weakness of neither. (Sternberg, 1977, p. 65)

    Historical dictionary of quotations in cognitive science > Intelligence

  • 14 idle

    1. [aıdl] a
    1. 1) незанятый, неработающий, свободный

    our team will be idle tomorrow - завтра наша команда не играет /не участвует в соревнованиях/

    2) безработный

    the depression rendered thousands idle - из-за кризиса тысячи людей остались без работы

    3) неиспользуемый, бездействующий, простаивающий

    idle plant - простаивающее /бездействующее/ предприятие

    idle machines - бездействующие машины /-ее оборудование/

    idle capacity - резервная /неиспользуемая/ мощность

    idle premises - пустующее /неиспользуемое/ помещение

    idle capital /money/ - мёртвый капитал

    to stand idle - не работать, простаивать

    the market is idle - эк. на рынке царит застой

    4) незаполненный, незанятый, свободный ( о времени)

    idle day - день, свободный от работы

    idle time - а) простой, перерыв в работе; б) свободное время

    2. ленивый, праздный

    the idle rich - бездельники-богачи, живущие в праздности богачи

    3. бесполезный, тщетный
    4. праздный, пустой; необоснованный

    idle conceit - пустое самодовольство /-ая самонадеянность/

    idle dreams [words] - пустые мечты [слова]

    idle fears - напрасные страхи /опасения/

    idle rumours - пустые /необоснованные/ слухи

    idle pleasures - пустые /праздные/ развлечения

    out of /through/ idle curiosity - из праздного любопытства

    5. тех. холостой; работающий на малых оборотах

    idle jet - авт. жиклёр холостого хода или малых оборотов

    6. тех. промежуточный, нейтральный; паразитный
    7. эл. безваттный, реактивный ( о токе)

    ♢ idle Monday - прогул

    idle folk lack no excuses - посл. у лодырей оправдание всегда найдётся

    an idle brain is the devil's workshop - посл. ≅ лень - мать всех пороков

    idle folks have the least leisure - посл. меньше всего свободного времени у бездельников, бездельникам всегда некогда

    2. [aıdl] v
    1. бездельничать, лодырничать

    don't idle about! - перестань слоняться без дела!

    2. тратить время попусту (преим. idle away)

    to idle away one's time [one's life] - растрачивать своё время [свою жизнь]

    3. лишать работы
    4. оставлять без дела или занятия
    5. тех. работать на холостом ходу

    НБАРС > idle

  • 15 disorder

    noun
    1) Unordnung, die; Durcheinander, das

    everything was in [complete] disorder — alles war ein einziges[, heilloses] Durcheinander

    the meeting broke up in disorder — die Versammlung endete in einem heillosen Durcheinander

    2) (rioting, disturbance) Unruhen Pl.
    3) (Med.) [Funktions]störung, die

    a stomach/liver disorder — ein Magen-/Leberleiden

    * * *
    [dis'o:də]
    1) (lack of order; confusion or disturbance: The strike threw the whole country into disorder; scenes of disorder and rioting.) die Unordnung
    2) (a disease: a disorder of the lungs.) die Erkrankung
    •
    - academic.ru/21108/disorderly">disorderly
    * * *
    dis·or·der
    [dɪˈsɔ:dəʳ, AM -ɔ:rdɚ]
    n
    1. no pl (disarray) Unordnung f
    state of \disorder chaotischer Zustand
    to be in \disorder in Unordnung sein
    to retreat in \disorder MIL sich akk ungeordnet zurückziehen
    to throw sth into \disorder etw in Unordnung bringen [o durcheinanderbringen
    2. MED [Funktions]störung f
    brain \disorder Störung f der Gehirnfunktion
    circulatory \disorder Kreislaufstörung f
    digestive [or intestinal] \disorder Verdauungsstörung f
    kidney \disorder Nierenleiden nt
    mental \disorder Geistesstörung f
    neurotic \disorder Neurose f
    personality \disorder Persönlichkeitsstörung f
    respiratory \disorder Störung f der Atemwege
    skin \disorder Hautirritation f
    3. no pl (riot) Aufruhr m
    civil \disorder Bürgerunruhen pl
    public \disorder öffentliche Unruhen
    * * *
    [dɪs'ɔːdə(r)]
    1. n
    1) Durcheinander nt; (in room etc) Unordnung f, Durcheinander nt

    in disorder — durcheinander, in Unordnung

    2) (POL: rioting) Unruhen pl

    eating disorder — Störung f des Essverhaltens

    2. vt
    1) (= mess up) durcheinanderbringen; room in Unordnung bringen
    2) (MED) angreifen
    * * *
    disorder [dısˈɔː(r)də(r)]
    A s
    1. Unordnung f, Durcheinander n (beide auch fig):
    be in (a state of) disorder in Unordnung oder durcheinander sein;
    2. Systemlosigkeit f
    3. (öffentliche) Ruhestörung, Aufruhr m, Unruhen pl
    4. ungebührliches Benehmen
    5. MED Störung f, Erkrankung f:
    mental disorder Geistesstörung
    B v/t
    1. in Unordnung bringen, durcheinanderbringen (beide auch fig)
    2. MED Störungen hervorrufen in (dat), besonders den Magen verderben
    * * *
    noun
    1) Unordnung, die; Durcheinander, das

    everything was in [complete] disorder — alles war ein einziges[, heilloses] Durcheinander

    2) (rioting, disturbance) Unruhen Pl.
    3) (Med.) [Funktions]störung, die

    a stomach/liver disorder — ein Magen-/Leberleiden

    * * *
    n.
    Unordnung f.

    English-german dictionary > disorder

  • 16 _лінощі; недбалість

    at open doors dogs come in the devil finds work for idle hands to do do not wait for a rainy day to fix your roof drowsiness dresses a man is rags an idle brain is the devil's workshop idle folks have the most labor idle folks lack no excuses idle people have the least leisure idleness goes in rags idleness makes the wit rust laziness travels so slow that poverty overtakes him lazy folks' stomachs don't get tired a lazy sheep thinks its wool heavy a long thread, a lazy tailor sloth is the mother of poverty sloth is the mother of vice sloth makes all things difficult, but industry makes all things easy they must hunger in winter that will not work in summer

    English-Ukrainian dictionary of proverbs > _лінощі; недбалість

  • 17 signal

    signal ['sɪgnəl] ( British pt & pp signalled, cont signalling, American pt & pp signaled, cont signaling)
    1 noun
    (a) (indication) signal m;
    ∎ to give sb the signal to do sth donner à qn le signal de faire qch;
    ∎ he'll give the signal to attack il donnera le signal de l'attaque;
    ∎ she gave the signal for us to leave elle nous a donné le signal de départ;
    ∎ you're sending all the wrong signals if you want her to realize you're attracted to her si tu veux qu'elle comprenne que tu es attiré par elle, il faut que ton attitude le montre;
    ∎ he's putting out a lot of confusing signals son attitude n'est pas claire;
    ∎ it was the first signal (that) the regime was weakening c'était le premier signe de l'affaiblissement du régime;
    ∎ the demonstration is a clear signal to the government to change its policy la manifestation signifie clairement que le gouvernement doit changer de politique;
    ∎ to send smoke signals envoyer des signaux de fumée
    (b) Railways sémaphore m
    ∎ radio signal signal m radio;
    ∎ Radio station signal indicatif m (de l'émetteur)
    Radio & Telecommunications (strength, frequency) de signal
    formal insigne;
    ∎ you showed a signal lack of tact vous avez fait preuve d'une maladresse insigne
    (a) (send signal to) envoyer un signal à;
    ∎ to signal sb faire signe à qn;
    ∎ he signalled the plane forward il a fait signe au pilote d'avancer;
    ∎ the brain signals the muscles to contract le cerveau envoie aux muscles le signal de se contracter
    (b) (indicate → refusal) indiquer, signaler; (→ malfunction) signaler, avertir de;
    ∎ the parachutist signalled his readiness to jump le parachutiste fit signe qu'il était prêt à sauter;
    ∎ the linesman signalled the ball out le juge de ligne a signalé que le ballon était sorti;
    ∎ the cyclist signalled a left turn le cycliste a indiqué qu'il tournait à gauche
    (c) (announce, mark → beginning, end, change) marquer;
    ∎ the speech signalled a radical change in policy le discours a marqué une réorientation politique radicale;
    ∎ this signals the start of the rainy season cela indique le début ou c'est le signe du début de la saison des pluies;
    ∎ her resignation signalled the beginning of the end sa démission a marqué le début de la fin
    (a) (gesture) faire des signes;
    ∎ to signal to sb to do sth faire signe à qn de faire qch;
    ∎ he signalled for the bill il a fait signe qu'il voulait l'addition;
    ∎ she was signalling for us to stop elle nous faisait signe de nous arrêter
    (b) (send signal) envoyer un signal;
    ∎ the satellite is still signalling le satellite émet ou envoie toujours des signaux
    (c) Cars (with indicator) mettre son clignotant; (with arm) indiquer de la main un changement de direction
    ►► Aviation & Nautical signal beacon balise f;
    Nautical signal book code m international des signaux;
    Railways signal box poste m de signalisation;
    signal communications télécommunications fpl, transmissions fpl;
    signal flag Military fanion m de signalisation; Nautical pavillon m pour signaux;
    signal flare (rocket) fusée f éclairante; (stationary) feu m de Bengale;
    signal lamp (for making signals) lampe f ou projecteur m de signalisation; (serving as a signal) (lampe f) témoin m;
    signal light Nautical fanal m; Military voyant m (lumineux);
    British Military signals officer officier m des transmissions;
    American signal red vermillon m chinois;
    signal rocket fusée f de signalisation;
    American signal tower poste m d'aiguillage

    Un panorama unique de l'anglais et du français > signal

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