software count

1) Information technology: software counter

2) Oil: software count

1 to sell, to vend.

vender algo a o por to sell something for

venden naranjas a 2 euros el kilo they're selling oranges for 2 euros a kilo

es capaz de vender a su madre he'd sell his own mother

es capaz de vender su alma al diablo por triunfar he'd sell his soul to the Devil if that's what it took to be successful

Ellos venden verduras They sell vegetables.

Ellos vendieron la casa They sold the house.

2 to expose for sale.

3 to soil, to betray for money, to prostitute.

El chico vendió a su mejor amigo The boy betrayed his best friend.

4 to persuade, to delude with false pretences.

5 to betray faith, confidence, or friendship. (Metaphorical)

6 to boast of talents or merits one does not possess.

7 to devote oneself to the service of another.

* * *

► verbo transitivo

1 (gen) to sell

■ vende enciclopedias he sells encyclopedias

■ lo vendieron por un millón de dólares they sold it for a million dollars

2 figurado (traicionar) to betray

■ sería capaz de vender a su propia familia he would even betray his own family

► verbo pronominal venderse

1 (uso impersonal) to be on sale, be sold

■ se vende en farmacias on sale at your chemist's

■ se vende a 40 pesetas el kilo it's sold at 40 pesetas a kilo

2 (dejarse sobornar) to sell oneself

\

'Se vende' "For sale"

sin vender unsold

vender a plazos to sell on credit

vender al contado to sell for cash

vender al por mayor to sell wholesale, wholesale

vender al por menor to sell retail, retail

vender caro to sell at a high price

venderse caro,-a to play hard to get

* * *

* * *

1. VT

1) [+ producto] to sell

- ¡a mí que las vendo!

2) (=traicionar) [+ amigo] to betray, sell out *; [+ cómplice] to shop *

VI to sell

venderse

* * *

verbo transitivo

1) <mercancías/casa> to sell

2)

a) ( traicionar) to betray

b) ( delatar) to give... away

venderse v pron to sell out

* * *

= market, sell, flog, dispose of, peddle.

Ex. In information retrieval applications it was more usual for one organisation to carry most of the burden of development of the system, and then to market it to others.

Ex. Since a software package is to be sold it must be visible on the marketplace.

Ex. Shops which keep on selling cigarettes to children under 16 will be banned from flogging tobacco.

Ex. List and describe the steps involved in withdrawing and disposing of books which are no longer required.

Ex. It could lose those shareholders who may not want to be associated with a conglomerate which also peddles death and destruction.

----

* arte de vender = salesmanship, specsmanship.

* con licencia para vender bebidas alcohólicas = licensed.

* no vendas la leche antes de ordeñar la vaca = don't count your chickens before they are hatched.

* que se vende = priced.

* tienda que vende de todo = general store.

* vender a Alguien como esclavo = sell + Nombre + into slavery.

* vender a crédito = make + charge sale.

* vender a cuenta = trade for + credit.

* vender al contado = trade for + cash.

* vender al detalle = retail.

* vender al por mayor = sell + in bulk, wholesale.

* vender al por menor = retail.

* vender a precio de costo = sell at + cost.

* vender a precio de ganga = sell at + bargain price.

* vender a un precio más barato que = undercut.

* vender de casa en casa = peddle.

* vender el alma al diablo = sell + Posesivo + soul to the devil.

* vender en el extranjero a precios inferiores que en el país de origen = dump.

* vender la moto a Alguien = pull + the wool over + Posesivo + eyes.

* vender más barato = undercut.

* venderse = change + hands.

* venderse caro = play + hard to get, play it + cool.

* venderse más que = outsell.

* venderse por + Dinero = fetch + Dinero.

* vender todas las entradas de un Evento = sell out.

* vender un producto = carry.

* vender un servicio = market + service.

* * *

verbo transitivo

1) <mercancías/casa> to sell

2)

a) ( traicionar) to betray

b) ( delatar) to give... away

venderse v pron to sell out

* * *

* * *

vender [E1 ]

A ‹mercancías/acciones/casa› to sell

trabaja vendiendo libros she sells books for a living

lo venden en todos lados it's on sale everywhere

vendió la casa muy bien she got a very good price for her house

le vendí el reloj a mi primo I sold my cousin the watch, I sold the watch to my cousin

esa línea se vende muy bien/poco that line sells very well/doesn't sell very well

[ S ] se vende for sale

[ S ] se vende bicicleta señora lady's bicycle for sale

vender al por mayor/menor to sell wholesale/retail

es capaz de vender a su padre/madre con tal de conseguirlo she would sell her own father/mother to get it

intentando vender una imagen moderna del país trying to sell a more modern image of the country

vender algo A algo to sell sth AT sth

lo venden a $500 el kilo they sell it at $500 a kilo, it sells for $500 a kilo

vender algo EN or POR algo to sell sth FOR sth

vendí el cuadro en or por $20.000 I sold the painting for $20,000

se vende por kilo/unidad it's sold by the kilo/unit

venderse como churros or pan caliente or rosquillas ( fam); to sell like hotcakes

el libro se vende como pan caliente the book is selling like hotcakes

1 (traicionar) ‹amigo› to betray, sell … down the river ( colloq)

2 (delatar) ‹persona› to give … away

el acento lo vende his accent gives him away

1 «producto» to sell

2 «pintor» to be successful; «actor/jugador» to be successful, be a crowdpuller

una escritora que vende a best-selling author

to sell out

se vendió por un ascenso he abandoned all his principles o sold out to get promotion

se ha vendido a los intereses extranjeros he has sold out to foreign interests

* * *

◊ le vendí el reloj I sold him the watch;

◊ lo venden a $500 el kilo they sell it at $500 a kilo;

* * *

♦ vt

1. [productos] to sell;

vender algo a o [m5] por to sell sth for;

venden naranjas a 20 pesos el kilo they're selling oranges for 20 pesos a kilo;

se vende [en letrero] for sale;

este modelo se vende mucho this model is selling very well;

es capaz de vender a su madre he'd sell his own mother;

vender su alma al diablo: es capaz de vender su alma al diablo por triunfar he'd sell his soul to the Devil if that's what it took to be successful;

vender caro algo not to give sth up without a fight;

el equipo vendió caro su título the team did not give up its title without a fight;

la oposición venderá caro su apoyo the opposition will demand a high price for its support;

no vender ni una escoba to get absolutely nowhere;

vender la moto a alguien: les vendió la moto de que iban a ser estrellas he fooled them into believing they were going to be stars;

nos quieren vender la moto de que no van a subir los impuestos they want us to swallow the story that they're not going to increase taxes;

vender salud to be bursting with health

2. [idea, proyecto] to sell

3. [amigo, familia] to betray

♦ vi

eso no vende hoy día that doesn't sell these days

♦ See also the pronominal verb venderse

* * *

1 sell;

vender caro algo a alguien fig make s.o. pay dearly for sth

2 fig ( traicionar) betray

* * *

vender vt

1) : to sell

2) : to sell out, to betray

♦ See also the reflexive verb venderse

* * *

vender vb to sell [pt. & pp. sold]

1 support (also figurative).

2 hold, support, stay, buttress.

3 help, co-operation, assistance, cooperation.

4 supporter, person who lends support, backer, prop.

5 crutch.

1^st person singular (yo) present indicative of spanish verb: apoyar.

* * *

► nombre masculino

1 support

2 figurado support, backing, help

* * *

* * *

1) (=ayuda) support

2) [a una propuesta, idea] support, backing

3) (=apoyatura) support

* * *

masculino support

* * *

= backing, endorsement, support, advocacy, prop, escort, anchor, anchor point, supportiveness, sustainment, a shoulder to cry on, backup [back-up], buttress.

Ex. Thus the scheme has a sound organisational backing.

Ex. The project was given endorsement by the Standing Committees of the IFLA Section on Cataloguing and the then Section on Mechanization.

Ex. BSO was prepared by the International Federation for Documentation with the support of UNESCO (United Nations Educational, Scientific, and Cultural Organization), and was published in 1978/79.

Ex. However, what American libraries mean by advocacy is 'Work to overcome obstacles that the enquirer encounters in trying to secure help from outside resource agencies'.

Ex. The main props to any retrospective bibliography must be a well formed national library which has a long history of collecting the records of a nation's culture.

Ex. Escort can be seen as part of the referral process or as a separate activity of accompanying a client to ensure that the person reaches the source of help.

Ex. This format can provide an anchor for instructional designers attempting to come to terms with the vast potential of hypertext and hypermedia.

Ex. This article stresses the importance of the library as a permanent anchor point for the local community.

Ex. Percentage of books in a discipline charged out by students majoring in other disciplines was defined as the ' supportiveness' of that discipline.

Ex. America's present need is not heroics, but healing; not nostrums, but normalcy; not experiment, but equipoise; not submergence in internationality, but sustainment in triumphant nationality.

Ex. I recalled how bereft we felt when we lost our son and how friends and neighbours rallied round and offered a shoulder to cry on.

Ex. The aggressiveness of a number of publications on this subject, replete with their accusations without any backup, can be interpreted as settling of scores.

Ex. They used schools as a buttress of a caste system designed to subordinate blacks socially, to cramp them economically under a rigid job ceiling.

----

* administrativo de apoyo = clerical employee.

* apoyo administrativo = administrative support.

* apoyo a la toma de decisiones = decision support.

* apoyo del personal = staff support.

* apoyo económico = financial support, financial backing.

* apoyo estatal = state support.

* apoyo financiero = financial backing.

* apoyo moral = moral support.

* apoyo mutuo = mutual support.

* apoyo para los pies = footrest.

* apoyo técnico = service support, technical support, product support, tech support.

* apoyo técnico de aplicaciones informáticas = software support.

* buscar apoyo = line up + support.

* buscar el apoyo de = woo.

* carta de apoyo = letter of support.

* centro de apoyo a los programas de estudios = curriculum material center.

* clases de apoyo = remedial teaching.

* como apoyo a = in support of.

* conseguir apoyo = mobilise + support, win + support, line up + support, gain + support.

* contar con apoyo para = have + support for.

* contar con el apoyo de Alguien = have + Nombre + behind + Pronombre.

* contar con el apoyo necesario para = have + the power behind to.

* crear apoyo = build + support.

* dar apoyo = give + support, support, provide + support.

* de apoyo = enabling, supportive.

* destreza de apoyo = ancillary skill.

* educación de apoyo = remedial education.

* en apoyo a = in support of.

* estructura de apoyo = support structure.

* fomentar apoyo = build + support.

* ganarse el apoyo = earn + support.

* grupo de apoyo = interest group, support group.

* herramienta de apoyo = enabler.

* material didáctico de apoyo = study aide.

* mecanismo de apoyo = enabler.

* merecer apoyo = be deserving of support.

* ofrecer apoyo = support, provide + support, rally (a)round, rally behind.

* personal administrativo de apoyo = clerical staff, clerical worker, clerical personnel.

* personal de apoyo = paraprofessional staff, support staff.

* personal de apoyo bibliotecario = library support staff.

* personal técnico de apoyo = support staff.

* prestar apoyo = lend + support, support.

* prestar apoyo a = go to + bat for, bat for.

* proporcionar apoyo = provide + support, support.

* punto de apoyo = foothold.

* que actúa de apoyo = supporting, supporting.

* recabar apoyo = garner + support.

* recibir apoyo = receive + support, attract + support.

* redirigir el apoyo = divert + support.

* ser un gran apoyo = be a tower of strength.

* servicio auxiliar de apoyo familiar = respite care.

* servicio de apoyo = backup service, support service.

* servir de apoyo a = inform.

* sin apoyo = unsupported.

* sistema de apoyo a la toma de decisiones = decision support system, decision making system.

* solicitar apoyo = canvass + support.

* técnica de apoyo = enabling skill.

* tecnología de apoyo = enabling technology.

* trabajo administrativo de apoyo = clerical work.

* trabajo de apoyo = escort work.

* * *

masculino support

* * *

* * *

1 (respaldo) support

no cuentan con el apoyo popular they do not have the support of the people o enjoy popular support

agradezco el apoyo que me han brindado en todo momento I am grateful for the support you have given me throughout

apoyo A algo support FOR sth

han retirado su apoyo a esta iniciativa they have withdrawn their support for o their backing of this initiative

una campaña de apoyo a la investigación científica a campaign in support of scientific research

2 ( Ling):

vocal/consonante de apoyo intrusive vowel/consonant

* * *

1ª persona singular (yo) presente indicativo

3ª persona singular (él/ella/usted) pretérito indicativo

◊ apóyalo contra la pared lean it against the wall

a) ( respaldar) ‹propuesta/persona› to back, support

b) ‹ teoría› to support, bear out

* * *

apoyo nm

support;

salieron adelante con el apoyo de su familia they got by with the support of her family;

me dio su apoyo moral she gave me her moral support;

buscan apoyos económicos para el proyecto they are seeking funding o financial support for the project;

anunciaron su apoyo a la iniciativa they declared their support for the initiative;

presentó las pruebas en apoyo de su teoría he presented the evidence to support his theory

* * *

m fig

support;

en apoyo de in support of

* * *

apoyo nm

: support, backing

* * *

apoyo n support

1) accumulator

1 to arrange, to put in order (poner en orden) (alfabéticamente, numéricamente).

2 to order.

Le ordené ir I ordered him to go

Ordené la habitación I straightened up the room.

La maestra ordenó silencio The teacher ordered silence.

3 to ordain (religion).

4 to order. ( Latin American Spanish)

5 to sort, to classify in a given order, to order.

Ordené mis papeles I sorted my papers.

6 to ordain as.

Ricardo ordenó a Manolo sacerdote Richard ordained Manolo as priest.

7 to be ordered to, to be told to, to receive orders to.

Se me ordenó matar I was ordered to kill.

* * *

► verbo transitivo

1 (arreglar) to put in order; (habitación) to tidy up

■ ordenó a los alumnos en filas she lined up the students

■ los libros estaban ordenados por materias the books were classified by subject matter

2 (mandar) to order

■ me ordenó que saliera de la habitación he ordered me to leave the room

3 RELIGIÓN to ordain

4 (encaminar) to direct

\

ordenar las ideas figurado to collect one's thoughts

* * *

1) to order

2) arrange

* * *

1. VT

1) (=poner en orden) [siguiendo un sistema] to arrange; [colocando en su sitio] to tidy; (Inform) to sort

2) (=mandar) to order

3) (Rel) to ordain

ordenarse

* * *

verbo transitivo

1) <habitación/armario> to straighten (up) (AmE), to tidy (up) (BrE)

2)

a) ( dar una orden) to order

b) (AmL) (en bar, restaurante) to order

3) < sacerdote> to ordain

ordenarse v pron to be ordained

* * *

= milk.

Ex. Results showed that the first colostrum of ewes milked one hour postpartum had significantly more protein than that of nanny-goats.

----

* no vendas la leche antes de ordeñar la vaca = don't count your chickens before they are hatched.

* ordeñar una vaca = milk + a cow.

* sala de ordeñar = milking parlour.

* * *

verbo transitivo

1) <habitación/armario> to straighten (up) (AmE), to tidy (up) (BrE)

2)

a) ( dar una orden) to order

b) (AmL) (en bar, restaurante) to order

3) < sacerdote> to ordain

ordenarse v pron to be ordained

* * *

* * *

ordenar [A1 ]

A ‹habitación/armario/cajón› to straighten (up) ( AmE), to tidy (up) ( BrE)

hay que ordenar los libros por materias the books have to be arranged according to subject

ordena estas fichas sort out these cards, put these cards in order

1 (dar una orden) to order

la policía ordenó el cierre del local the police ordered the closure of the establishment o ordered the establishment to be closed

el médico le ordenó reposo absoluto the doctor ordered him to have complete rest

le ordenó salir inmediatamente de la oficina she ordered him to leave the office immediately

me ordenó que guardara silencio he ordered me to keep quiet

2 ( AmL) (en un bar, restaurante) to order

ordenar un taxi to call a taxi

C ‹sacerdote› to ordain

to be ordained

se ordenó sacerdote he was ordained a priest

* * *

◊ ordené los libros por materias I arranged the books according to subject

a) ( dar una orden) to order;

◊ le ordenó salir de la oficina she ordered him to leave the office

b) (AmL) ( pedir) ‹taxi/bebida/postre› to order

* * *

♦ vt

1. [poner en orden] [alfabéticamente, numéricamente] to arrange, to put in order;

ordenar alfabéticamente to put in alphabetical order;

ordenar en montones to sort into piles;

ordenar por temas to arrange by subject

2. Informát to sort

3. [mandar] to order;

te ordeno que te vayas I order you to go;

me ordenó callarme he ordered me to be quiet

4. Rel to ordain

5. Am [pedir] to order;

acabamos de ordenar el desayuno we've just ordered breakfast

♦ vi

1. [mandar] to give orders;

(yo) ordeno y mando: Ana es de las de (yo) ordeno y mando Ana's the sort of person who likes telling everybody what to do

2. Am [pedir] to order;

¿ya eligieron?, ¿quieren ordenar? are you ready to order?

♦ See also the pronominal verb ordenarse

* * *

1 habitación tidy up

2 alfabéticamente arrange; INFOR sort

3 ( mandar) order

4 L.Am. ( pedir) order

* * *

ordenar vt

1) mandar: to order, to command

2) arreglar: to put in order, to arrange

3) : to ordain (a priest)

* * *

ordenar vb

1. (colocar por orden) to arrange / to put in order [pt. & pp. put]

2. (recoger) to tidy [pt. & pp. tidied]

3. (mandar) to order

   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)