computing+engine

compression [kəm'preʃən]

noun

(a) (of material) compression f;

∎ Technology in compression comprimé

(b) figurative (condensing) réduction f

(c) Computing (of file) compression f

►► Technology compression chamber chambre f de compression;

Cars compression ignition allumage m par compression;

compression period période f de compression;

compression pump pompe f de compression;

Technology compression ratio taux m de compression;

Technology compression stroke (in engine) (temps m de) compression f

lease [li:s]

1 noun

(a) Law bail m; (of equipment) location f; (of house to let) bail m (à loyer); (of farming land) bail m à ferme; (document) (contrat m de) bail m;

∎ a 99-year lease un bail de 99 ans;

∎ to take (out) a lease on a house, to take a house on lease prendre une maison à bail;

∎ to sign a lease signer un bail;

∎ the lease runs out in May le bail expire en mai

(b) (idioms)

∎ to take on a new lease of life (person) renaître à la vie; (industry, town, football club) retrouver un nouveau souffle;

∎ the trip has given her a new lease British of or American on life le voyage l'a remise en forme ou lui a redonné du tonus;

∎ cleaning the engine will give the car a new lease of life ça va retaper la voiture de nettoyer le moteur

2 transitive verb

(a) (of owner → house) louer ou céder à bail; (→ equipment, vehicle) louer; (→ land) affermer;

(b) (of tenant → house) louer, prendre à bail; (of person → equipment, vehicle) louer; (→ land) prendre en fermage

►► Accountancy lease charges charges fpl locatives;

lease contract (for property) contrat m de bail; (for equipment) contrat m en location;

Finance lease financing leasing m, location f avec option d'achat;

Computing leased line ligne f louée;

Accountancy lease revenue loyers mpl

➲ lease back separable transitive verb

Finance = louer dans le cadre d'une cession-bail

➲ lease out separable transitive verb

(of owner → house) louer ou céder à bail; (→ equipment, vehicle) louer; (→ land) affermer

pack [pæk]

remplir ⇒ 1 (a) bourrer ⇒ 1 (a), 1 (c) emballer ⇒ 1 (b) tasser ⇒ 1 (d) charger ⇒ 1 (e) faire sa valise ⇒ 2 (a) rentrer ⇒ 2 (b) s'entasser ⇒ 2 (c) sac a dos ⇒ 3 (a) paquet ⇒ 3 (b) bande ⇒ 3 (d) meute ⇒ 3 (d)

1 transitive verb

(a) (fill) remplir, bourrer ( with de); Building industry & Mining (trench) remblayer;

∎ to pack one's case/one's bags faire sa valise/ses bagages;

∎ figurative to pack one's bags (leave) plier bagages;

∎ we're not packed nous n'avons pas fait nos bagages;

∎ Theatre she packs the house every night elle fait salle comble chaque soir

(b) (put into box, carton etc) emballer, empaqueter; (put into suitcase, bag, trunk etc) mettre dans sa valise/son sac/sa malle/ etc;

∎ I've already packed the towels j'ai déjà mis les serviettes dans la valise;

∎ shall I pack the camera? est-ce que j'emporte ou je prends l'appareil photo?;

∎ I've packed a lunch for you je t'ai préparé de quoi déjeuner;

∎ the equipment is packed in polystyrene le matériel est emballé dans du polystyrène;

∎ esp American shall I pack these for you? (in supermarket) je vous emballe vos achats?

(c) (cram tightly → cupboard, container) bourrer; (→ belongings, people) entasser;

∎ he packed his pockets with sweets, he packed sweets into his pockets il a bourré ses poches de bonbons;

∎ commuters pack the morning trains les banlieusards s'entassent dans les trains du matin;

∎ figurative we managed to pack a lot into a week's holiday on a réussi à faire énormément de choses en une semaine de vacances

(d) (compress → soil) tasser;

∎ the wind had packed the snow against the wall le vent avait tassé la neige contre le mur

(e) (load → horse, donkey) charger

(f) (rig)

∎ to pack a jury se composer un jury favorable;

∎ to pack a meeting s'assurer un nombre prépondérant de partisans à une réunion;

∎ Cards to pack the cards apprêter les cartes

(g) Technology (packing box) garnir, étouper

(h) Computing (database) condenser, compacter

(i) American (carry in a backpack) transporter dans un sac à dos

(j) (idioms)

∎ he packs a lot of influence in cabinet/ministerial circles il a beaucoup d'influence au conseil des ministres/dans les milieux ministériels;

∎ familiar to pack a punch (person) cogner dur; (drink) donner un coup de fouet;

∎ American familiar to pack a gun être armé^□, être chargé

2 intransitive verb

(a) (for journey) faire sa valise ou ses bagages;

∎ have you finished packing? as-tu fini tes bagages?

(b) (fit → into container) rentrer;

∎ the keyboard will pack easily into a briefcase on peut facilement faire tenir le clavier dans un attaché-case;

∎ this dress packs well cette robe ne se froisse pas (même dans une valise)

(c) (crowd together → spectators, passengers) s'entasser;

∎ we all packed into her car nous nous sommes tous entassés dans sa voiture

(d) (in rugby) former une mêlée

3 noun

(a) (rucksack) sac m à dos; (bundle) ballot m; (bale) balle f; (on animal) charge f;

∎ parachute pack sac m à parachute

(b) (packet) paquet m;

∎ British a pack of washing powder un paquet de lessive;

∎ American a pack of cigarettes un paquet de cigarettes;

∎ a four-/six-pack of beer un pack de quatre/six

(c) British (deck of cards) jeu m

(d) (group → of people) bande f; (→ of cub scouts) meute f; (→ of hunting hounds) meute f; (→ of wolves) meute f, bande f; (→ of runners, cyclists) peloton m;

∎ wolves hunt in packs les loups chassent en meute;

∎ figurative press photographers often hunt in packs les photographes de presse se déplacent souvent en bande;

∎ a pack of fools une bande ou un tas d'imbéciles;

∎ British that's a pack of lies! c'est un tissu de mensonges!

(e) (in rugby) pack m

(f) Medicine compresse f;

∎ wet/cold pack enveloppement m humide/froid

(g) (pack ice) pack m, banquise f

(h) (in snooker) = triangle formé par les boules rouges

►► pack animal bête f de somme;

Military pack drill exercice m avec paquetage (à titre de punition);

∎ no names, no pack drill je ne citerai pas de noms;

pack ice pack m, banquise f;

pack leader (in rugby) responsable m des avants;

American Zoology pack rat rat m des bois, néotome m;

∎ familiar figurative to be a pack rat (person) avoir la manie de tout garder^□ ;

Television & Cinema pack shot pack shot m;

pack train convoi m de bêtes de somme

➲ pack away

1 separable transitive verb

(a) (tidy up) ranger; (bed, folding table, chair) replier

(b) familiar (eat) bouffer;

∎ he really packs it away! qu'est-ce qu'il bouffe!;

∎ she can really pack away the food when she gets going ce qu'elle peut engouffrer quand elle s'y met

(c) familiar (send away) expédier^□ ;

∎ I packed the kids away to bed/school j'ai envoyé les gosses au lit/à l'école

2 intransitive verb

(of bed, folding table, chair) se replier;

∎ this tent packs away easily cette tente se replie ou se range facilement

➲ pack down

1 separable transitive verb

(soil, snow) tasser

2 intransitive verb

(in rugby) former une mêlée

➲ pack in

1 separable transitive verb British

(a) (cram in) entasser;

∎ I couldn't pack anything more in je ne pouvais pas en faire rentrer plus;

∎ the play is packing them in la pièce fait salle comble;

∎ we were packed in like sardines nous étions serrés comme des harengs (en caque) ou comme des sardines

(b) familiar (task) laisser tomber; (job, boyfriend, girlfriend) plaquer;

∎ you should pack in smoking tu devrais arrêter de fumer^□ ;

∎ pack it in! arrête!^□, ça suffit!^□

2 intransitive verb

(a) (crowd in) s'entasser (à l'intérieur)

(b) British familiar (break down → machine, engine) tomber en panne^□ ;

∎ the photocopier's just packed in on me la photocopieuse vient de me lâcher

➲ pack off separable transitive verb

familiar expédier^□ ;

∎ I packed the kids off to bed/school j'ai envoyé les gosses au lit/à l'école

➲ pack on inseparable transitive verb

Nautical

∎ to pack on all sail mettre toutes voiles dehors

➲ pack out separable transitive verb

familiar (fill completely → room) remplir à craquer;

∎ the hall was packed out la salle était pleine à craquer ou comble ou bondée;

∎ the theatre had been packed out for weeks le théâtre faisait salle comble depuis des semaines;

∎ the show was completely packed out il n'y avait plus un seul billet pour ce spectacle^□

➲ pack up

1 intransitive verb

(a) (pack one's suitcase) faire sa valise ou ses bagages

(b) (tidy up) ranger

(c) British familiar (break down) tomber en panne^□ ;

∎ my car's packed up ma voiture m'a lâché;

∎ her heart has packed up son cœur a lâché ou cédé

(d) British familiar (stop work) dételer;

∎ I'm packing up for today j'arrête pour aujourd'hui^□

2 separable transitive verb

(a) (suitcase, bags) faire

(b) (tidy up → clothes, belongings, tools) ranger;

∎ help me pack up the tent aide-moi à plier la tente

shut [ʃʌt] (pt & pp shut, cont shutting)

1 transitive verb

(a) (close) fermer;

∎ shut your eyes! fermez les yeux!;

∎ figurative you shouldn't shut your eyes to the problem vous ne devriez pas fermer les yeux sur le problème;

∎ shut your books refermez ou fermez vos livres;

∎ please shut the door after you veuillez fermer ou refermer la porte derrière vous;

∎ familiar shut your mouth or face, shut it! ferme ton clapet!, la ferme!

(b) (trap)

∎ her skirt got shut in the door sa robe est restée coincée dans la porte;

∎ I shut my finger in the door je me suis pris le doigt dans la porte

2 intransitive verb

(a) (door, window, container etc) (se) fermer;

∎ the door won't shut la porte ne ferme pas;

∎ the lid shuts very tightly le couvercle ferme hermétiquement

(b) (shop, gallery etc) fermer;

∎ the post office shuts at 6 p.m. la poste ferme à 18 heures

3 adjective

fermé;

∎ familiar keep your mouth or trap shut! ferme-la!, boucle-la!

➲ shut away separable transitive verb

(criminal, animal) enfermer; (precious objects) mettre sous clé;

∎ I shut myself away for two months to finish my novel je me suis enfermé pendant deux mois pour terminer d'écrire mon roman

➲ shut down

1 separable transitive verb

(a) (store, factory, cinema) fermer

(b) (machine, engine) arrêter; (computer) éteindre

(c) Sport (mark closely) marquer de près

2 intransitive verb

(a) (store, factory, cinema) fermer

(b) Computing (system) s'arrêter

➲ shut in separable transitive verb

enfermer;

∎ he went to the bathroom and shut himself in il est allé à la salle de bains et s'y est enfermé;

∎ to feel shut in avoir un sentiment d'étouffement;

∎ we're shut in by hills nous sommes entourés de collines

➲ shut off

1 separable transitive verb

(a) (cut off → supplies, water, electricity) couper; (→ radio, machine) éteindre, arrêter; (→ light) éteindre

(b) (isolate) couper, isoler;

∎ the village was shut off from the rest of the world le village a été coupé du reste du monde;

∎ she shut herself off from other people elle s'isolait du reste des gens

(c) (block) boucher;

∎ that new building shuts off all our sunlight ce nouvel immeuble nous cache la lumière du jour

2 intransitive verb

se couper, s'arrêter;

∎ it shuts off automatically ça s'arrête automatiquement

➲ shut out separable transitive verb

(a) (out of building, room)

∎ she shut us out elle nous a enfermés dehors;

∎ we got shut out nous ne pouvions plus rentrer

(b) (exclude) exclure;

∎ he drew the curtains to shut out the light il tira les rideaux pour empêcher la lumière d'entrer;

∎ she felt shut out from all decision-making elle avait l'impression que toutes les décisions étaient prises sans qu'elle soit consultée

(c) (block out → thought, feeling) chasser (de son esprit)

(d) (turn off → light) éteindre

(e) Sport (opponent) empêcher de marquer

➲ shut up

1 intransitive verb

(a) familiar (be quiet) la fermer, la boucler;

∎ shut up! la ferme!, boucle-la!;

∎ shut up and do your work ferme-la et fais ton travail;

∎ he never knows when to shut up il ne sait pas se taire^□ ou la fermer quand il faut;

∎ she hasn't shut up about her holiday since she got back elle n'a pas arrêté de parler de ses vacances depuis qu'elle est rentrée^□

(b) (close) fermer;

∎ we decided to shut up early nous avons décidé de fermer tôt

2 separable transitive verb

(a) (close → shop, factory) fermer;

∎ to shut up shop (close shop at end of day) fermer le magasin; (close shop permanently) fermer boutique; (of theatre, factory) fermer ses portes

(b) (lock up) enfermer;

∎ to shut oneself up s'enfermer chez soi

(c) familiar (silence)

∎ to shut sb up clouer le bec à qn;

∎ that shut him up! ça lui a cloué le bec!;

∎ will somebody shut those kids up! faites taire ces gosses!

turbo ['tɜ:bəʊ] (pl turbos)

noun

(a) Cars turbo m

(b) (turbine) turbine f

►► Computing turbo button bouton m de turbo;

Cars turbo diesel turbodiesel m;

Cars turbo diesel engine moteur m turbodiesel

[ˈpauə]

air power могущество в воздухе, воздушная мощь ancillary power акцессорное право arbitrary power дискреционные полномочия autonomous power самоуправление bargaining power рыночная позиция bargaining power сила которой обладают стороны при переговорах blanket power полные полномочия buying power полномочия на совершение сделки power сила; мощность, энергия; производительность; by power механической силой, приводом от двигателя colonial power колониальная держава commercial power торговая держава competitive power конкурентоспособность computational power вчт. вычислительные возможности computer power вычислительная мощность computer power вычислительный ресурс computer power вчт. производительность компьютера computing power вчт. вычислительные возможности conquering power завоевательная держава continental power континентальная держава data power эффективность данных decision-making power полномочие на принятие решений discretionary power дискреционная власть discretionary power дискреционные полномочия dispositive power юридические полномочия driving power движущая сила earning power возможность зарабатывать earning power доходность earning power прибыльность earning power способность приносить доход power мат. степень; eight is the third power of two восемь представляет собой два в третьей степени engine power мощность двигателя excess purchasing power чрезмерная покупательная способность executive power исполнительная власть executive power исполнительные полномочия explanatory power полномочия давать объяснения expressive power выразительная сила financial power финансовая власть fiscal power финансовые полномочия foreign power иностранная держава general power общая компетенция general power общие полномочия general purchasing power всеобщая покупательная способность grant a power предоставлять полномочия grant a power уполномочивать great power великая держава power держава; the Great Powers великие державы housekeeping power юр. право ведения домашнего хозяйства power способность; возможность; I will do all in my power я сделаю все, что в моих силах; it is beyond my power это не в моей власти power способность; возможность; I will do all in my power я сделаю все, что в моих силах; it is beyond my power это не в моей власти joint decision-making power совместное право принятия решений judicial power судебная власть land power военная мощь land power мощная военная держава legislative power законодательная власть machine power машинная мощность major power главная держава mandatory power государство-мандатарий mandatory power мандатные полномочия maritime power морская держава market power власть на рынке market power рыночная власть mechanical power механическая мощность without power с выключенным двигателем; the mechanical powers простые машины the powers that be власти предержащие, сильные мира сего; merciful powers! силы небесные! military power военная держава power politics политика с позиции силы; more power to your elbow! желаю успеха! naval power морская держава nuclear power государство, обладающее атомным оружием nuclear power ядерная держава nuclear power ядерное государство occupying power оккупационная держава paternal power родительская власть placing power способность разместить ценные бумаги power власть power возможность power дееспособность power держава; the Great Powers великие державы power держава power доверенность power компетенция power разг. много, множество; a power of money куча денег; a power of good много пользы power могущество, власть (тж. государственная); влияние, мощь; supreme power верховная власть; the party in power партия, стоящая у власти power мощность power мощь power полномочие; the power of attorney доверенность power полномочие power право power правоспособность power производительность power сила; мощность, энергия; производительность; by power механической силой, приводом от двигателя power сила power опт. сила увеличения (линзы, микроскопа и т. п.) power снабжать силовым двигателем power способность, право, правомочие, полномочие, компетенция power способность; возможность; I will do all in my power я сделаю все, что в моих силах; it is beyond my power это не в моей власти power способность power степень power мат. степень; eight is the third power of two восемь представляет собой два в третьей степени power энергия power attr. силовой, энергетический; моторный; машинный power of appointment доверенность на распределение наследственного имущества power полномочие; the power of attorney доверенность power of attorney доверенность power of attorney полномочие power of attorney concerning safe custody полномочие на хранение ценных бумаг в банковском сейфе power of attorney given for business purposes полномочие на ведение дел power of attorney to represent another person in court полномочия представлять в суде интересы другого лица power of codecisions полеомочия принимать совместные решения power of decisions право принимать решения power of discretion полномочия решать по собственному усмотрению power of eminent domain право государства на принудительное отчуждение частной собственности power разг. много, множество; a power of money куча денег; a power of good много пользы power of inquiry право подавать запрос power разг. много, множество; a power of money куча денег; a power of good много пользы power of procuration полномочие на ведение дел power of sale право продажи power of taxation право обложения налогом power of testation право на завещательное распоряжение power politics политика с позиции силы; more power to your elbow! желаю успеха! power to coopt право кооптировать power to take decisions право принимать решения the powers that be власти предержащие, сильные мира сего; merciful powers! силы небесные! prosecutorial power обвинительные полномочия protective power протекционистская держава pulling power привлекательность рекламы purchasing power покупательная сила purchasing power эк. покупательная способность purchasing power покупательная способность purchasing power покупательная способность денег raising to a power возведение в степень real purchasing power реальная покупательная способность regulatory power распорядительные полномочия sea power морская держава signatory power подписавшаяся страна signatory power страна, подписавшая документ spending power покупательная способность; speech power дар речи spending power покупательная способность; speech power дар речи state power государственная власть staying power страна пребывания staying: power остающийся неизменным; неослабевающий; staying power(s) выносливость, выдержка power могущество, власть (тж. государственная); влияние, мощь; supreme power верховная власть; the party in power партия, стоящая у власти supreme power высшая власть taxpaying power налогоспособность treaty power полномочия на заключение договора unlimited power неограниченная мощность victorious power победоносная держава voting power право голоса without power с выключенным двигателем; the mechanical powers простые машины

   1) Programs and the Complexity of Human Mental Processes

   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)

   2) Artificial Intelligence Is an Engineering Discipline

   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)

   3) A Sceptical View of Artificial Intelligence

   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)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   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)

   6) The Meaning of a Symbolic Description

   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)

   7) The Principle of Artificial Intelligence

   [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)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   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)

    10) There Are Many Types of Reasoning

   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)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   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)

    12) The Synthesis of Man and Machine

   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)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   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)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological 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.

   ♦ Weak Psychological AI

   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.

   ♦ Strong Psychological AI

... 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)

   ♦ Suprapsychological AI

   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)

    17) Form and Content Are Not Fundamentally Different

   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)

    20) Mathematical Logic Provides the Basis for Theory in AI

   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)

    22) Definitions of Artificial Intelligence

   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)

    23) The Computer Can Not Be a Model of the Mind

   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)

    24) Computers Will Not Always Be Inferior to Human Brains

   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)