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81 handling
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82 валюта валют·а
эк.обесценивать валюту — to depreciate / to devalue the currency
обменивать валюту на золото — to redeem (the) currency in gold
иностранная валюта — foreign currency, (foreign) exchange
получать / приобретать иностранную валюту — to secure foreign currency
недостаток иностранной валюты — foreign exchange gap / stringency
поступления иностранной валюты — (foreign) exchange earnings
клиринговая валюта, валюта клиринга — agreement / clearing currency
ключевая валюта — key / vehicle currency
конвертируемая — (обратимая, твёрдая) валюта convertible / hard currency
свободно конвертируемая валюта — freely convertible currency / exchange
локальная / местная валюта, валюта данной страны — domestic / home / local currency
"мягкая" валюта — soft currency
конвертировать переводные рубли в национальную валюту — to convert / to transfer roubles into national currency
неконвертируемая / необратимая валюта — inconvertibie / nonconvertible / soft currency
"плавающая" валюта — floating currency
верхний допустимый предел взаимного отклонения курсов совместно плавающих (европейских) валют — joint float ceiling
резервная валюта (выполняющая роль международного расчётного и резервного средства) — reserve currency
валюта, курс которой "привязан" к валюте другой страны — pegged currency
валюта, на которой базируется валютная оговорка — reference currency
валюта, полученная от продажи нефти — petro- / petroleum currency
валюта, "привязанная" к доллару — currency pegged to dollar
единица валюты — unit of currency, monetary unit
запасы / резервы валюты — currency reserves
курс валюты — rate of exchange, exchange rate
прекратить операции по обмену валют — to close foreign exchange / currency markets
паритет валюты — par / parity of exchange
перевод / пересчёт валюты — conversion of currency
покупательная сила / покупательная способность валюты — purchasing power of' currency
согласованное колебание / "плавание" валют — concerted float
товары, являющиеся источником поступления твёрдой валюты — currency earning commodities
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83 курс
1) (направление) course, policy, lineвзять курс на подъём чего-л. — to take the course / the path of raising smth.
изменять свой курс — to alter / to change one's course
намечать курс — to map out / to mark out a course; (в общих чертах) to outline a course
начертать курс — to chart a course (for)
придерживаться курса — to adhere / to stick to a policy / a course
проводить курс — to conduct / to pursue a policy, to hold / to pursue / to take a line, to steer / to tread a course
следовать курсом — to pursue / to follow the course
авантюристический курс — adventurist(ic) policy, policy of adventure
внешнеполитический курс — foreign policy, foreign policy course
генеральный курс — general line / course
жёсткий курс — hard / tough line, tough policy
проводить жёсткий курс в отношении страны — to take a strong / a hard line with a country
несговорчивый / упрямый сторонник жёсткого курса — intractable hard-liner
милитаристский курс — militarist course / policy
независимый курс — independent course / policy
искажать / фальсифицировать политический курс — to falsify a policy
сформулировать политический курс — to enunciate / to set out a policy
позитивный / положительный политический курс — positive policy
умеренный курс — moderate line, middle-of-the road course
курс на затягивание чего-л. — policy of dragging out smth. курс на конфронтацию collision course курс на оздоровление / улучшение отношений course toward(s) improving relations
курс на "прямое противоборство" — policy of "direct confrontation"
курс на сегрегацию без каких-л. отступлений — hard-line segregationist platform
курс партии — party line, party's policy
курс перестройки экономики — course for reorganization / restructuring of the economy
сторонник либерального курса — dove разг.
2) эк. course, rate, quotation exchangeиграть на повышение курса — to be bullish, to go a bull
играть на понижение курса — to be bearish, to go bear
биржевой курс — exchange / market quotation, share price
валютный курс, курс валюты — (foreign) exchange rate, course / par / rate of exchange, exchange
выгодный валютный курс — profitable rate of exchange, favourable exchange
высокий валютный курс — high rate (of exchange) / exchange rate
гибкий валютный курс — flexible exchange rate / rate of exchange
двойной валютный курс — double exchange rate / rate of exchange
действующий / эффективный валютный курс — effective exchange rate / rate of exchange
заключительный валютный курс — closing rate (of exchange) / exchange rate
закреплённый валютный курс — fixed rate (of exchange) / exchange rate
искусственно поддерживаемый валютный курс — pegged rate (of exchange) / exchange
колеблющийся валютный курс — floating / fluctuating / free exchange rate, variable exchange
единый / унифицированный колеблющийся валютный курс — unitary floating rate of exchange
наличный валютный курс — current rate of exchange / exchange rate
начальный валютный курс — opening rate of exchange / exchange rate
неодинаковые / различные валютные курсы — different rates of exchange / exchange rates
неподдерживаемый / нерегулируемый валютный курс — unpegged rate of exchange / exchange rate
неустойчивый валютный курс — variable exchange rate / rate of exchange
обменный валютный курс — exchange rate, rate of exchange
официально объявленный / официальный валютный курс (установленный центральным банком) — official rate (of exchange) / exchange rate
плавающий валютный курс — floating rate of exchange / exchange rate, float
вводить плавающий / свободно колеблющийся валютный курс — to float
повышенный валютный курс — higher rate of exchange / exchange rate
пониженный валютный курс — reduced rate (of exchange) / exchange rate
свободный валютный курс — free rate of exchange / exchange rate
справочный валютный курс — posted rate of exchange / exchange
твёрдый / фиксированный валютный курс — fixed exchange rate / rate of exchange
текущий рыночный валютный курс — going market rate of exchange / exchange rate
центральный валютный курс (не основанный на паритете Международного валютного фонда) — central rate (of exchange) / exchange rate
введение нового соотношения / новой системы валютных курсов — exchange rate alignment
расчёт валютного курса — (exchange) rate calculation, calculation of exchange
движение / динамика валютных курсов — exchange rate movements, movement in the exchange rate
размах колебаний валютного курса, пределы отклонений валютного курса от паритета — fluctuation band
курс валюты — см. валюта
неустойчивый курс иностраннной валюты — fluctuant foreign exchange rate, variable exchange
падение валютного курса — fall in the exchange rate / in exchange
курс акций — stock exchange; stock price амер.
ежедневно / еженедельно публикуемый курс акций — daily / weekly average
курс дня (иностранной валюты) — exchange / rate of the day
падение курса доллара (по отношению к евро) — the dollar's fall (against the euro)
курс при закрытии банка / биржи / рынка — closing rate
курс при открытии банка / биржи / рынка — opening rate
курс ценных бумаг — rate of securities, price
согласованный (в ходе переговоров) курс ценных бумаг — negotiated price
твёрдый / устойчивый курс ценных бумаг — firm price
курс, предлагаемый покупателем ценных бумаг — bid price
курс, предлагаемый продавцом ценных бумаг — asked price
3)быть в курсе политики — to be well informed / versed in politics
ввести в курс дела — to bring (smb.) up to date
держать в курсе дела — to keep (someone) informed
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84 chart
1) график; диаграмма; схема; таблица; чертёж; схематическое представление2) карта || составлять карту4) список; реестр• -
85 control
1. n управление, руководствоfailsoft control — управление с "мягким отказом"
2. n полит. контроль, власть; обладаниеislands under British control — острова, управляемые Великобританией
3. n контроль, проверка; надзорquality control — контроль, проверка качества
4. n регулировка, управлениеremote control — управление на расстоянии; телеуправление, дистанционное управление
control key — кнопка управления; ключ управления
control line — шина управления; линия управления
5. n регулирование; ограничениеexchange control — валютный контроль; валютное регулирование
6. n борьба7. n сдержанность, самообладание8. n тех. органы управления9. n топ. сеть опорных пунктов10. n пробный удар11. n радио регулировка, модуляция12. n «хозяин», дух, который вещает устами медиума«хозяин», шеф, руководящий деятельностью агента, шпиона
ink control zone — зона, в которой контролируется подача краски
13. a контрольный14. a относящийся к управлениюcontrol board — приборный щиток, панель или пульт управления
15. v управлять, руководитьtake control of — управлять; контролировать
have control over — контролировать; управлять
hold control over — контролировать; управлять
16. v контролировать, владетьkeep control over — контролировать; управлять
17. v контролировать, проверятьexercise control — осуществлять контроль; контролировать
to control crime — контролировать, сдерживать преступность
18. v регулировать, контролировать; ограничивать19. v радио настраивать20. v сдерживатьto control nature — сдерживать инстинкты; владеть собой
21. v делать пробный ударСинонимический ряд:1. aplomb (noun) aplomb; composure; self-control2. check (noun) check; curb; restraint; suppressant3. direction (noun) authority; charge; command; direction; disposition; domination; dominion; hold; jurisdiction; might; power; prerogative; strings4. discipline (noun) discipline; limitation; mastery; poise; qualification; regulation; restriction; subordination5. monopoly (noun) corner; dominance; holding the reins; manipulation; monopoly; strategy6. political power (noun) administration; ascendancy; governance; government; political power; regimentation; reign; rule; sovereignty; subjugation; sway7. reserve (noun) reserve; reticence; self-restraint; taciturnity8. compose (verb) check; collect; compose; contain; cool; hinder; re-collect; reduce; rein; repress; restrain; restrict; simmer down; smother; suppress9. direct (verb) command; direct; govern; guide; handle; lead; manage; oversee; regulate; rule; subject; supervise10. dominate (verb) dominate; domineer; master; overpower11. steer (verb) drive; navigate; pilot; steer12. subdue (verb) bully; intimidate; manipulate; monopolise; monopolize; subdue; tame; whip13. verify (verb) establish; experiment; prove; test; validate; verifyАнтонимический ряд:encouragement; forsake; free; give up; ignore; leave; liberate; misconduct; mismanage; neglect; obey; quit; renounce -
86 центр обработки данных
1. data processing centerспецификация данных; определение данных — data specification
совокупность данных; данные объединенные в пул — pooled data
2. processing centerРусско-английский большой базовый словарь > центр обработки данных
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87 τάξις
A arranging, arrangement:I in military sense:1 drawing up in rank and file, order or disposition of an army, Th.5.68 (init.), 7.5, etc.; τὰ ἀμφὶ τάξεις rules for it, tactics, X.An.2.1.7;τ. καὶ ἀντίταξις Phld.Piet.12
.2 battle array, order of battle,κατὰ τάξιν Hdt.8.86
;ἐν τάξει Th.4.72
, etc.; ἐς τάξιν καθίστασθαι, ἀνάγειν, ib.93, Ar.Av. 400 (anap.); ἵνα μὴ διασπασθείη ἡ τ. Th.5.70; of ships,ἀποπλῶσαι ἐκ τῆς τάξιος Hdt.6.14
.3 a single rank or line of soldiers, ἐπὶ τάξιας ὀλίγας γίγνεσθαι to be drawn up a few lines deep, ib. 111, cf. 9.31;ἐλύθησαν αἱ τ. τῶν Περσῶν Pl.La. 191c
.4 body of soldiers, A.Pers. 298, S.OC 1311; esp. at Athens, the quota of infantry furnished by each φυλή (cf.ταξίαρχος 11
), Lys.16.16; but freq. of smaller bodies, company, X.An. 1.2.16, 6.5.11, etc.; ἱππέων τ. ib.1.8.21; so of ships, squadron, A.Pers. 380: generally, band, company, φιλία γὰρ ἥδε τ., of the chorus, Id.Pr. 128 (lyr.);ἐμφανίσας μοι ἐν ᾗ ἔσομαι τάξει PCair.Zen. 409.6
(iii B.C.).b esp. a contingent of 128 men, Ascl.Tact.2.8, Arr.Tact.10.2, Ael.Tact.9.3.c in late Gr., membership of the militia palatina (cf. ταξεώτης), Lib.Or.27.17.5 post or place in the line of battle, ἀξιεύμεθα ταύτης τῆς τ. Hdt.9.26, cf. 27;ἐν τῇ τ. εἶχε ἑωυτόν Id.1.82
; μένειν ἐν τῇ ἑωυτοῦ τ. Id.3.158;τ. φυλάξων E.Rh. 664
;ἡ τ. φυλακτέα X.Cyr.5.3.43
;ᾗ ἕκαστος τὴν τ. εἶχεν Id.An. 4.3.29
;τῆς πρώτης τ. τεταγμένος Lys.14.11
, cf. Th.5.68 (fin.); ἐκλιπόντας τὴν τ. Hdt.5.75, cf. 9.21; λείπειν τὴν τ. And.1.74, Pl.Ap. 29a, D.13.34, 15.32, Aeschin.3.159, etc.;παραχωρεῖν τῆς τάξεως D.3.36
, etc.; but ἡγεμὼν ἔξω τάξεων officer on the unattached list, Arch.Pap.3.188, cf. Sammelb. 599, OGI 69 ([place name] Coptos); so οἱ ἔξω τάξεως staff-officers, aides-de-camp, D.S.19.22.II generally, arrangement, order,ἡμερῶν τ. εἰς μηνῶν περιόδους Pl.Lg. 809d
; ἡ τῶν ὅλων τ. X.Cyr.8.7.22; disposition,τῆς ψυχῆς Gorg.Hel.14
: Rhet., disposition, opp. λέξις, Arist.Rh. 1414a29;ἡ τ. τοῦ λόγου Aeschin.3.205
, cf. D.18.2, Sor.1.18, Gal.Libr.Ord.1; ὕστερον τῇ τ. D.3.15, cf. Gal.6.68, 16.533; ἐν τ. εἶναι, = μένειν, Pl.Tht. 153e;τ. καὶ ἠρεμία Arist.EE 1218a23
;εἰ τὰ γυμνάσια ἔχοι τὴν τ. ἐνταῦθα Id.Pol. 1331a37
; difft. from θέσις or mere position, Id.Ph. 188a24, Thphr.Sens. 60 ( θέσεως τ. Gal.6.194; τ. θέσεως is dub. l. in 16.709); ἡ κατὰ τ. τινὰ βασιλεία, opp. ἀόριστος τυραννίς, Arist.Rh. 1366a2; καὶ τοῦτο κατὰ τ., ἕως.. and so on, until.., Sor.2.62.2 order, regularity,εἰς τ. ἄγειν ἐκ τῆς ἀταξίας Pl.Ti. 30a
;τ. καὶ κόσμος Id.Grg. 504a
; οὔτε νόμος οὔτε τ. Id.Lg. 875c, cf. R. 587a;τ. περιόδου Epicur.Ep.2p.42U.
;διὰ τάξεως γίγνεσθαι Pl.Lg. 780a
; τάξιν ἔχειν to be regular, Thphr. HP3.9.6; ἐν τάξει in an orderly manner, Pl.Lg. 637e; so (Nysa, i B.C., rendering of Lat. ordine).b prescription, τὴν τοῦ λυσιτελοῦντος τοῖς σώμασι ποιεῖσθαι τ. Id.Plt. 294e; recipe, cj. in PHolm.2.2.4 τ. τοῦ φόρου assessment of tribute, X.Ath.3.5, cf. IG12.63.2, al.; τῶν ὀφειλημάτων περὶ τῆς πράξεως ib.57.13, cf. Lex ap.D.24.45; τ. τῆς ὑδρείας a ration of water, Pl.Lg. 844b.III metaph. from 1.5, post, rank, position, station,ὑπὸ χθόνα τάξιν ἔχουσα A.Eu. 396
(lyr.); ἡ τῶν ἀκοντιζόντων τ. Antipho 3.2.7; ἰδία τοῦ βίου τ. Isoc. 6.2; ἀνὴρ τῆς πρώτης τ. CIG2767.4 ([place name] Aphrodisias); οἰκέτου τ. D.18.258, cf. PGnom.43, 196 (ii A.D.), Mitteis Chr. 372 v 18 (ii A.D.);τ. ἔχοντος ἐν τῷ Μουσείῳ Sammelb.6674.10
(ii A.D.); ἐν τῇ Θετταλῶν τάξει ranging herself with the T., D.18.63; ἐν ἐχθροῦ τ. as an enemy, Id.20.81, etc.; ἐν ἐπηρείας τάξει by way of insult, Id.18.13; ἀδύνατον εἶχεν τ. occupied an impossible position, i.e. was unthinkable, Hyp.(?) Oxy.1607.60; τὴν ὑπὲρ ὑμῶν ἑλόμενον τάξιν πολιτεύεσθαι championship of your cause, D.18.138, cf. Ep.3.15; ἐγὼ τὴν τῆς εὐνοίας τ... οὐκ ἔλιπον post of patriotism, Id.18.173.2 list, register, ὅπως ταγῇ αὐτοῦ τὸ ὄνομα ἐν τῇ τῶν τετελευτηκότων τ. Sammelb.7359.15, cf. 7404.6, PSI9.1064.38, 10.1141.10 (all ii A.D.);ἡ τ. τῶν κατοχίμων PTeb.318.21
(ii A.D.);τ. λαογράφων PLond.2.182b2
(ii A.D.).V reduction of hernia by manipulation, Gal.14.781.VIII fixed point of time, term,κατ' ἐνιαυτὸν ἢ κατά τινα ἄλλην τ. ἢ χρόνον Arist.Pol. 1261a34
; end (or perh. date fixed for the end),μέχρι τάξεως αὐτῆς τῆς τρύγης Sammelb.5810.15
(iv A.D.). -
88 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, EventuallyJust 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)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany 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 FormThe 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 FormationIt 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 ContextsEven 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)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 IntelligenceThe 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 PropositionsIn 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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89 Brain
Among the higher mammals the great development of neocortex occurs.In each group of mammals there is a steady increase in the area of the association cortex from the most primitive to the evolutionarily most recent type; there is an increase in the number of neurons and their connections. The degree of consciousness of an organism is some function of neuronal cell number and connectivity, perhaps of neurons of a particular type in association cortex regions. This function is of a threshold type such that there is a significant quantitative break with the emergence of humans. Although the importance of language and the argument that it is genetically specified and unique to humans must be reconsidered in the light of the recent evidence as to the possibility of teaching chimpanzees, if not to speak, then to manipulate symbolic words and phrases, there are a number of unique human features which combine to make the transition not merely quantitative, but also qualitative. In particular these include the social, productive nature of human existence, and the range and extent of the human capacity to communicate. These features have made human history not so much one of biological but of social evolution, of continuous cultural transformation. (Rose, 1976, pp. 180-181)[S]ome particular property of higher primate and cetacean brains did not evolve until recently. But what was that property? I can suggest at least four possibilities...: (1) Never before was there a brain so massive; (2) Never before was there a brain with so large a ratio of brain to body mass; (3) Never before was there a brain with certain functional units (large frontal and temporal lobes, for example); (4) Never before was there a brain with so many neural connections or synapses.... Explanations 1, 2 and 4 argue that a quantitative change produced a qualitative change. It does not seem to me that a crisp choice among these four alternatives can be made at the present time, and I suspect that the truth will actually embrace most or all of these possibilities. (Sagan, 1978, pp. 107-109)The crucial change in the human brain in this million years or so has not been so much the increase in size by a factor of three, but the concentration of that increase in three or four main areas. The visual area has increased considerably, and, compared with the chimpanzee, the actual density of human brain cells is at least 50 percent greater. A second increase has taken place in the area of manipulation of the hand, which is natural since we are much more hand-driven animals than monkeys and apes. Another main increase has taken place in the temporal lobe, in which visual memory, integration, and speech all lie fairly close together. And the fourth great increase has taken place in the frontal lobes. Their function is extremely difficult to understand... ; but it is clear that they're largely responsible for the ability to initiate a task, to be attentive while it is being done, and to persevere with it. (Bronowski, 1978, pp. 23-24)The human brain works however it works. Wishing for it to work in some way as a shortcut to justifying some ethical principle undermines both the science and the ethics (for what happens to the principle if the scientific facts turn out to go the other way?). (Pinker, 1994, p. 427)Historical dictionary of quotations in cognitive science > Brain
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90 נסךְ
נָסַךְ(b. h.) to pour, cast. Y.Ber.I, 2d top, v. מָסַךְ II. Pi. נִסֵּךְ 1) to offer a libation. Succ.IV, 9 ולִמְנַסֵּךְ אומרים לווכ׳ and they said to him who offered the libation (of water), raise thy hand. Ib. שפעם אחת ני׳ אחדוכ׳ for once it happened, that a priest poured the libation out at his feet. Snh.62b זיבח … וני׳וכ׳ if one sacrificed, burnt incense, and offered a libation (to an idol) ; a. fr.Cant. R. to IV, 12 מֵאָן היו ישראל מנטרים כלוכ׳ (read: מְנַסְּכִים, v. Matt. K. a. l.) whence did the Israelites take wine for their festive gatherings during the forty years ? 2) to make wine forbidden (יֵין נֶסֶךְ) by the manipulation of a gentile suspected of dedicating it to idolatrous purposes. Keth.27a; Sabb.41a אין פנאי לנַסֵּךְ they do not take the time to manipulate the wine. Ab. Zar.56b (in Chald. dict.) והא קא מנסך בידיה but might he not dedicate it to idolatry by putting his hand into it?; והא קא מנסך ברגל might he not do it with his foot (while treading the wine)? Gitt.V, 4 המנסך he who does damage to his neighbor by touching his wine for idolatrous purposes (v. interpret. ib. 52b). Y.Ab. Zar. IV, 44a bot. מנסך כל הבור he causes all the wine in the pit to be forbidden; a. fr. Nif. נִיסָּךְ to be offered as libation, to be poured on the altar. Pes.22a כמים הנִיסָּסִין like the water which is poured on the altar, opp. הנשפכין which is poured out at the foot of the altar. Hithpa. הִתְנַסֵּךְ, Nithpa. וִתְנַסֵּךְ 1) same. Ib. המִתְנַּסְּכִים; s. fr. 2) to be made forbidden ( as dedicated to idolatry). Y. Ab. Zar. l. c. נתנ׳ הבורוכ׳ if the wine in the pit has been manipulated and become forbidden, the jet of wine poured into the pit becomes forbidden (affecting the wine in the vessel). -
91 נָסַךְ
נָסַךְ(b. h.) to pour, cast. Y.Ber.I, 2d top, v. מָסַךְ II. Pi. נִסֵּךְ 1) to offer a libation. Succ.IV, 9 ולִמְנַסֵּךְ אומרים לווכ׳ and they said to him who offered the libation (of water), raise thy hand. Ib. שפעם אחת ני׳ אחדוכ׳ for once it happened, that a priest poured the libation out at his feet. Snh.62b זיבח … וני׳וכ׳ if one sacrificed, burnt incense, and offered a libation (to an idol) ; a. fr.Cant. R. to IV, 12 מֵאָן היו ישראל מנטרים כלוכ׳ (read: מְנַסְּכִים, v. Matt. K. a. l.) whence did the Israelites take wine for their festive gatherings during the forty years ? 2) to make wine forbidden (יֵין נֶסֶךְ) by the manipulation of a gentile suspected of dedicating it to idolatrous purposes. Keth.27a; Sabb.41a אין פנאי לנַסֵּךְ they do not take the time to manipulate the wine. Ab. Zar.56b (in Chald. dict.) והא קא מנסך בידיה but might he not dedicate it to idolatry by putting his hand into it?; והא קא מנסך ברגל might he not do it with his foot (while treading the wine)? Gitt.V, 4 המנסך he who does damage to his neighbor by touching his wine for idolatrous purposes (v. interpret. ib. 52b). Y.Ab. Zar. IV, 44a bot. מנסך כל הבור he causes all the wine in the pit to be forbidden; a. fr. Nif. נִיסָּךְ to be offered as libation, to be poured on the altar. Pes.22a כמים הנִיסָּסִין like the water which is poured on the altar, opp. הנשפכין which is poured out at the foot of the altar. Hithpa. הִתְנַסֵּךְ, Nithpa. וִתְנַסֵּךְ 1) same. Ib. המִתְנַּסְּכִים; s. fr. 2) to be made forbidden ( as dedicated to idolatry). Y. Ab. Zar. l. c. נתנ׳ הבורוכ׳ if the wine in the pit has been manipulated and become forbidden, the jet of wine poured into the pit becomes forbidden (affecting the wine in the vessel).
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