degree+of+difficulty

utmost, utter, very great, highest.

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

2 1^st person singular (yo) present indicative of spanish verb: sumir.

* * *

► adjetivo

1 (supremo) supreme, highest

2 figurado (muy grande) greatest

\

a lo sumo at most, at the most

con sumo cuidado with extreme care

suma autoridad supreme authority

Sumo Pontífice Sovereign Pontiff

sumo sacerdote high priest

* * *

1) (=supremo) great, supreme

2) [rango] high, highest

3)

SM (Dep) sumo, sumo wrestling

* * *

- ma adjetivo great

- Sumo Sacerdote

* * *

= supreme.

Ex. The need for organic, in-depth and timely access to legal information is of supreme importance.

----

* a lo sumo = at best, at most, at the most.

* con el más sumo cuidado = with utmost care.

* de suma importancia = of the utmost importance.

* en sumo grado = in the extreme.

* en un grado sumo = in the extreme.

* lo sumo = the bee's knees, the cat's pyjamas, the cat's meow, the cat's whiskers, the dog's bollocks.

* sumo cuidado = extreme caution.

* * *

- ma adjetivo great

- Sumo Sacerdote

* * *

* * *

great

un detalle de suma importancia a detail of great o of the utmost importance

me interesa en grado sumo I find it extremely interesting

con sumo cuidado with great o extreme o the utmost care

la suma autoridad the highest o supreme authority

a lo sumo at the most

no eran tantos, a lo sumo unos diez there weren't that many, ten at the most

masculine ( frml); Supreme Pontiff ( frml)

masculine high priest

(deporte) sumo wrestling, sumo; (persona) sumo wrestler

* * *

1ª persona singular (yo) presente indicativo

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

1ª persona singular (yo) presente indicativo

a) ‹ cantidades› to add (up)

b) ( totalizar) to add up to;

◊ 8 y 5 suman 13 8 and 5 add up to o make 13

a) ( agregarse) sumose A algo:

◊ esto se suma a los problemas ya existentes this comes on top of o is in addition to any already existing problems

b) ( adherirse) sumose A algo ‹a protesta/celebración› to join sth

◊ -ma adjetivo

* * *

sumo¹, -a adj

1. [supremo] highest, supreme

sumo sacerdote high priest

2. [gran] extreme, great;

lo aprecio en grado sumo I think extremely highly of him;

con sumo cuidado with extreme o great care;

a lo sumo at most;

tendrá a lo sumo veinte años she can't be more than twenty

sumo² nm

* * *

adj supreme;

con sumo cuidado with the utmost care;

a lo sumo at the most

* * *

sumo, -ma adj

1) : extreme, great, high

la suma autoridad: the highest authority

a lo sumo : at the most

♦ sumamente adv

1 extreme, outermost, exaggerated, excessive.

2 extreme, ultimate.

1 extreme, farthest end, end, terminal.

2 extent, degree.

3 extremitas.

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

* * *

► adjetivo

1 (exagerado) extreme

■ calor extremo extreme heat

■ extrema vejez extreme old age

2 (distante) further

3 figurado (intenso) utmost

► nombre masculino extremo

1 (punta) extreme, end

■ el extremo de la calle the end of the street

2 (punto último) point, extreme

■ pasar de un extremo a otro to go from one extreme to another

■ llegó al extremo de mendigar por la calle she got to the point of begging in the street

3 (asunto, materia) matter, question

4 DEPORTE wing

\

en caso extremo as a last resort

en extremo extremely, very much

en último extremo as a last resort

hasta tal extremo to such a point

los extremos se tocan figurado extremes meet

pasar de un extremo a otro to go from one extreme to another

Extremo Oriente Far East

extremo-derecha (fútbol) right wing

extremo-izquierda (fútbol) left wing

► nombre masculino

1 (punta) extreme, end

■ el extremo de la calle the end of the street

2 (punto último) point, extreme

■ pasar de un extremo a otro to go from one extreme to another

■ llegó al extremo de mendigar por la calle she got to the point of begging in the street

3 (asunto, materia) matter, question

4 DEPORTE wing

* * *

* * *

1) (=máximo) extreme

2) (=alejado) furthest

3) (Pol) (=radical) extreme

1. SM

1) (=punta) end

- ser el extremo opuesto

- ser los dos extremos

- los extremos se tocan

2) (=límite) extreme

3) (=asunto) point

4) (=cuidado) great care

* * *

- ma adjetivo

a) (gen delante del n) <pobreza/cuidado> extreme

b) <caso/medida> extreme

- extrema derecha/izquierda

- extremo derecho/izquierdo

- Extremo Oriente

1)

a) (de palo, cable) end

b) ( postura extrema) extreme

c) ( límite)

d)

2) (period) (punto, cuestión)

- ma masculino, femenino (en fútbol, rugby) winger

- extremo cerrado/defensivo

* * *

- ma adjetivo

a) (gen delante del n) <pobreza/cuidado> extreme

b) <caso/medida> extreme

- extrema derecha/izquierda

- extremo derecho/izquierdo

- Extremo Oriente

1)

a) (de palo, cable) end

b) ( postura extrema) extreme

c) ( límite)

d)

2) (period) (punto, cuestión)

- ma masculino, femenino (en fútbol, rugby) winger

- extremo cerrado/defensivo

* * *

extremo¹

¹ = end, extreme, far + Localización, reaches, extreme end, end point [endpoint], tip.

extremo²

² = extreme.

Nota: Adjetivo.

* * *

1 ( gen delante del n) ‹pobreza/gravedad› extreme

viven en una situación de extrema necesidad they live in extreme poverty

un caso de extrema gravedad an extremely serious case

2 ‹caso/postura/medida› extreme

casos extremos, que no suceden todos los días extreme cases which don't happen every day

en caso extremo as a last resort

feminine ( Pol) extreme right/left

masculine and feminine ( Dep) right/left wing

masculine Far East

1 (de un palo, cable) end

al otro extremo del pasillo at the other end of the corridor

viven al otro extremo de la ciudad they live right on the other side of the city

2 (postura extrema) extreme

va de un extremo a otro she goes from one extreme to the other o to another

son extremos opuestos, no se parecen en nada they are complete opposites, different in every way

no soy una persona de extremos I'm not given to extremes

los extremos se tocan ( fr hecha); extremes meet

(límite, punto): han llegado al extremo de no saludarse they've reached the point where they don't even say hello to each other

si se llega a ese extremo tendremos que operar if it gets that bad o to that point we'll have to operate

su descaro alcanzó extremos insospechados her effrontery reached unimagined extremes o limits

es cuidadoso al extremo he is extremely careful, he is careful to a fault

en último extremo as a last resort, if all else fails

en extremo in the extreme

fue una situación en extremo peligrosa it was a situation which was dangerous in the extreme, it was an extremely dangerous situation

B ( period)

(punto, cuestión): en ese extremo no estoy de acuerdo I do not agree on that point

tenían esperanzas de que volviera, extremo que no se confirmó they hoped that she would return but, in the event, this did not happen

para establecer los extremos de la denuncia to establish the main points of the accusation

(en fútbol, rugby) winger

tight end

defensive end

* * *

1ª persona singular (yo) presente indicativo

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

◊ extremo (en hacer algo) to make a great effort (to do sth)

a) (de palo, cable) end

b) ( postura extrema) extreme;

◊ va de un extremo a otro she goes from one extreme to the other;

c) ( límite):

◊ si se llega a ese extremo … if it gets that bad o to that point …;

* * *

♦ adj

1. [sumo] extreme;

con extremo cuidado with extreme care

2. [al límite] extreme;

una situación de pobreza extrema a situation of extreme poverty;

las condiciones climáticas de ese lugar son extremas the climate here is extreme;

la extrema izquierda/derecha the far left/right

3. [lejano] far, furthest

♦ nm

1. [punta] end;

agárralo por este extremo hold it by this end;

al otro extremo de la calle at the other end of the street;

mientras, en el otro extremo del país,… meanwhile, at the other end of the country,…;

los extremos se tocan extremes meet

2. [límite] extreme;

llegar a extremos ridículos/peligrosos to reach ridiculous/dangerous extremes;

no desearía llegar a ese extremo I wouldn't want to go to those lengths;

llegamos al extremo de pegarnos we actually ended up coming to blows;

en extremo: le mimas en extremo you spoil him far too much;

es meticuloso en extremo he is extremely meticulous o meticulous to a fault;

una decisión en extremo sorprendente an extremely surprising decision;

en último extremo as a last resort;

ir o [m5] pasar de un extremo al otro to go from one extreme to the other

3. [en fútbol] winger

extremo izquierdo [en fútbol] outside left;

4. [punto, asunto] issue, question;

…extremo que ha sido rechazado por… …a claim which has been denied by…;

este extremo está aún por confirmar that remains to be confirmed

* * *

I adj

1 extreme

la extrema derecha/izquierda the far right/left

II m

1 extreme;

ir o

pasar de un extremo a otro go from one extreme to another;

los extremos se tocan opposites attract;

en extremo in the extreme

2 parte primera o

última end

3 ( punto) point;

llegar al extremo de reach the point of

III m/f

extremo derecho/izquierdo DEP right/left wing

* * *

extremo, -ma adj

1) : extreme, utmost

2) excesivo: excessive

en caso extremo : as a last resort

extremo nm

1) : extreme, end

al extremo de : to the point of

en extremo : in the extreme

* * *

extremo¹ adj extreme

extremo² n

1. (en general) end

2. (punto último) extreme / point

little, scanty (escaso), limited, small in quantity, small in extent (pequeño), not much, few, some.

De poco interés of small interest

Todas las medidas son pocas any measure will be inadequate

little (no mucho), in a small degree or quantity, in a scanty manner, shortly, briefly, in a short time.

Poco ante or poco después, a little before or after

Poco a poco gently, softly; stop

De poco tiempo acá latterly

Tener en poco to set little value on a thing

A poco por poco, en poco, to be very near a thing

Qué poco how little: indicating the difficulty or impossibility of anything

Ahora trabaja muy poco he only works a little now

Poco amable unkind

Por poco almost

* * *

* * *

(stœri or stœrri, stœrstr), a.

1) big, great, of size (stórr fiskr, stórt dýr);

stór veðr, rough weather, great gales;

stór sær, high sea;

gørði þá stórt á firðinum, the sea rose high;

2) great, potent (at hann skyldi varast at gøra Ólaf eigi of stóran);

3) great, important (tillagagóðr hinna stœrri mála);

4) proud (fann hann þat brátt á Sigríði, at hón var heldr stór).

* * *

adj., compar. stæri or stærri, superl. stærstr, i. e. stœri, stœrstr; [a word peculiar to the Northern languages, from which it has entered into the Finnish; A. S. stôr; Engl. sturdy; North. E. stordy]:—the original sense seems to be ‘stirred,’ ‘disturbed’ (cp. III), but it is only used in the sense big, great, of size; ein stærst, Fms. iii. 123; bein miklu stærri, Eg. 769; stórir járnrekendr, Sks. 457; stórir askar, Eg. 204; stór héruð, 275; stór veðr, [cp. Shetl. stoor], rough weather, great gales, Ld. 50; stórr sær, a high sea, Sks.; stór, stæri sár, Nj. 153; stærst hof hér á landi, Landn. 335 (Mantissa); í stórum töskum, Hkr. iii. 244.

II. metaph. great, potent; við alla ena stærri menn, Ld. 124; mæltu at hann skyldi göra Ólaf eigi of stóran, Fms. i. 99; at hann görisk eigi of stórr, Eg. 50; gör þik eigi stærra enn þú átt kyn til, Fms. xi. 236; hve marga (aura) ok hve stóra, Grág. i. 136.

2. great, important; enna stærri mála, Nj. 2.

3. proud; bændr vóru þar því stærri enn annarsstaðar, at engi vildi til koma, Fms. iv. 112: Sigríð kona hans var heldr stór, v. 30 (skap-stórr, Ó. H. l. c.)

III. neut., görði þá stórt á firðinum, the sea rose high, Eg. 60; tíðendi þau er honum lægi svá stórt við, Fms. xi. 102; höggva stórt, to strike hard, Nj. 53.

IV. adverbial phrases, stórum, very greatly, much; svá at ek finna stórum, Ísl. ii. 343; stórum stauplar nú yfir, Fs. 153; þat berr stórum, it amounts to much, Fms. ii. 37; ætla ek stærum bera hin laga-brotin, vii. 305; stórum ríkr, very mighty, Hkr. iii. 244; stórum vinsæll, Fms. vii. 102; stórum feginn, Eg. 567; stórum sköruligt, Ld. 106. 2. stærrum, more, in a greater degree; skjótara ok stærum, Sks. 71; gefit hefir þú mér stærum, Fms. vii. 56; eigi stærum né smærum, neither more nor less, Grág. i. 241. 3. stórs, adv.; ekki stórs of ökla upp, Bs. i. 349. 4. stóru-gi, adv. much, greatly, Ísl. ii. 384; see -gi.

B. In COMPDS, and with nouns, stór-, like smár-, is chiefly prefixed to nouns in plur. or in a collective sense: stór-auðigr, adj. very wealthy, Landn. 68, Eg. 2, 23, Fms. xi. 293, Hdl. 39. stór-ár, f. pl. great waters, Stj. 87, Rb. 350. stór-beinóttr, adj. bony, coarse-faced, Eb. 30, Fas. i. 173. stór-blót, n. pl. great sacrifices, Fms. v. 164. stór-bokkar, m. pl. ‘big bucks,’ lordlings, mighty and overbearing men, Eb. 334, Fms. viii. 238 (spelt bukkar), xi. 260, Bs. i. 621. stór-borgir, f. pl. big towns, Róm. 264. stór-borinn, part. high-born, Hkr. i. 243, Bær. 14. stór-brögðóttr, adj. very sly, Hðm. 13. stór-burðigr, adj. = stórborinn, Fas. ii. 474, v. l. stór-bú, n. pl. great estates, Eg. 170, Fms. i. 13. stór-bygðir, f. pl. large counties, settlements, Ó. H. 174. stór-byssur, f. pl. big catapults, Fas. iii. 428, v. l.: big guns. stór-bæir, m. pl. great estates, Hkr. i. 20. stór-bændr, m. pl. great freeholders, Fms. ii. 40, Orkn. 136, Sturl. i. 37. stór-deildir, f. pl. great differences, quarrels, Sturl. i. 140, iii. 7. stór-deilur, f. pl. id., Sturl. i. 140 C. stór-draumar, m. pl. portentous dreams, Sturl. ii. 204 C. stór-efli, n., in stór-eflis-menn, m. pl. mighty men, Fms. xi. 7, 13, Gísl. 55, Háv. 50, Glúm. 37. stór-efni, n. pl. important cases, N. G. L. stór-eignir, f. pl. great landed estates, Hkr. iii. 19; stóreigna maðr, a great landowner, Ísl. ii. 202. stór-erviði, n. severe toil, hard work, Sturl. iii. 65. stór-eyjar, f. pl. great islands, Fms. vii. 85. stór-fé, n. great wealth, Nj. 178, Eg. 75, Fms. ix. 320; stórfjár ok dýrgripa, vii. 186. stór-feginn, adj. very fain or glad, Ver. 19, Bret. 46, Fms. xi. 29. stór-fengr, adj. gross, huge; hann var s. ok auðigr, Sturl. i. 8; föður átta ek heldr stórfengan, Brand. 62; stórfeng kýr, a good milch cow, Bs. i. 194. stór-fetaðr, part. long-striding, taking great steps, Fas. ii. 348; s. hestr, Edda 57. stór-fetr, adj. id., Greg. 17. stór-firðir, m. pl. big firths, Fb. iii. 446. stór-fiskar, m. pl. big fishes (whales). Fas. ii. 113. stór-fjaðrar, f. pl. big feathers, Sks. 114. stór-fjarri, adv. very far, Lex. Poët. stór-fjöllóttr, adj. with great fells, Eb. 8. stór-flokkar, m. pl. great ‘flocks,’ large detachments, Ó. H. 208. stór-frörar, m. pl. ice-fields, Grett. (in a verse). stór-fuglar, m. pl. big birds, El. 2. stór-fundir, m. pl. great meetings, great battles, Nj. 107. stór-föt, n. pl. big clothes, Glúm. 390. stór-geðr (- geðjaðr), adj. great-minded. Lex. Poët.: = stórgætr (?), Bs. i. 606. stór-gjafar, f. pl. great, lordly, rich gifts, Nj. 151, Fms. vii. 2. stór-gjöfull, adj. munificent, Hkr. i. 291, Fms. viii. 238, Bs. i. 81, Magn. 464. stór-gjöld, n. pl. heavy fines, Fms. i. 66. stór-glæpir, m. pl. great crimes, Fms. vii. 261, Stat. 260, Sks. 773. stórglæpa-maðr, m. a great criminal, Stj. 40. stór-glæpligr, adj. highly criminal, Sks. 773. stór-gnípur, f. pl. huge peaks, mountains, Fas. ii. 76. stór-góz, n. a great property, Bs. i. 853. stór-grýti, n. pl. big stones, rocks, Mag. stór-grýttr, adj. rocky, stony, Fms. xi. 239. stór-gættingar, m. pl. magnates, 623. 32, Al. 16. stór-görr, part. of great size, Lex. Poët. stór-hagr, adj. very skilled, handy, Fas. ii. 347. stór-heimsligr, adj. ‘big-foolish,’ grossly foolish, 625. 73. stór-heit, n. pl. great vows, Bs. i. 421, Fms. ix. 387. stór-héruð, n. pl. great districts, Stj. 83, MS. 655 xvi. A. 3, Ó. H. 125. stór-hlutir, m. pl. great things, Fms. vii. 136: in an evil sense, great sins, MS. 671. 16, N. G. L. i. 459. stór-hræddr, adj. much afraid, Fbr. 149. stór-huga, adj. aiming high, aspiring. stór-hugaðr, adj. high-minded, proud, Am. 72, Stj. stór-hvalir, m. pl. big whales, Sks. 122. stór-hveli, n. id., Fas. ii. 78. stór-höfðingjar, m. pl. great magnates, Fms. vii. 206, 209, Hkr. ii. 140, Barl. 127, Sks. 6. stór-höggr, adj. dealing heavy blows, Fms. xi. 131, Landn. 69, Fb. ii. 128. stór-ílla, adv. very badly, Grett. 120, Fms. i. 12, Fb. i. 411. stór-íllr, adj. very bad, Fms. ix. 393, Lv. 68. stór-jarteinir, f. pl. great wonders, Stj. 289. stór-kappar, m. pl. great champions, Fas. ii. 481. stór-katlar, m. pl. big kettles, Fms. x. 29. stór-kaup, n. pl. wholesale buying. stórkaup-maðr, m. a wholesale dealer, Fb. ii. 75. stór-keralda, að, in a pun, Krók. 63, 64. stór-kerti, n. pl. geat tapers, Flóv. 35. stór-keröld, n. pl. large vats, Dipl. v. 18. stór-klæki, n. pl. great wickedness, Band. 38 new Ed., Ó. H. 217. stór-kostliga, adv. in grand style, Bs. i. 645. stór-kostligr, adj. grand; bær s., Ó. H. 66; s. gjafir, Sturl. i. 48: colossal, Fb. i. 522. stór-kvikendi, n. pl. great beasts, Stj. 70. stór-kvæði, n. pl. great poems, Skálda 205. stór-langr, adj. very long, Eb. 24. stór-látr, adj. proud, haughty, Fms. i. 2: munificent, Fs. 51, Al. 70: not content with a little (opp. to smá-látr), Eg. 17, Fms. vi. 368. stór-leiði, n. a long way, Bs. i. 458. stór-leikr, m. presumption, pride, Fms. iv. 206, Ölk. 34, Stj. 537. stór-leitr, adj. big-faced, Sturl. ii. 99. stór-lendur, f. pl. great lands, Bs. i. 226. stór-liga, adv. greatly, very, Bret. 24, Eg. 57: proudly, Edda. 30; svara s., Fms. i. 3; mæla s., vi. 246, x. 194. stór-ligana, adv. = stórliga, Stj., MS. 227, passim. stór-ligr, adj. great, Eg. 46. stór-ljótr, adj. very ugly, Glúm. 387. stór-lokkar, m. pl. long locks, Fas. i. 173. stór-lyndi, f. magnanimity, Fms. vii. 198, Hkr. iii. 245; sína s., Fms. vii. 96. stór-lyndr, adj. magnanimous, Fms. vii. 98; high-spirited, Nj. 18, Fs. 129, Grett. 158. stór-læti, n. liberality, Ld. 30, Fms. x. 235: pride, v. 71, Ölk. 34. stór-lönd, n. pl. great counties, Fms. iv. 140. stór-mannliga, adv. (-ligr, adj.), like a grand man, munificently, Fs. 15, Ísl. ii. 337, Eg. 62, Fms. xi. 244. stór-mannligr, adj. magnificent, Fs. 11, 30, Fms. ii. 133, vi. 13, xi. 321. stór-margr, adj. very many, Eg. 219. stór-mál, n. pl. great suits; standa í stórmálum, Nj. 227, Fs. 29, Vápn. 22. stór-mein, n. pl. great evils, Fs. 44. stór-meizl, n. pl. great injuries, Sturl. ii. 49. stór-menni, n. great men, men of rank, Eg. 30, Fs. 11, Fms. i. 31, vi. 19, Ó. H. 71: great folk, Bárð. 172; frá Birni bunu er komit nær allt s. á Íslandi, Landn. 39: a liberal man, Sturl. i. 4, 9, Eg. 38, 198: a big man, giant, Edda 33. stór-mennska, u, f. greatness, munificence, Fms. xi. 19, 293, Fs. 15, passim; meir af stór-mennsku enu forsjá, Bs. i. 83. stórmennsku-fullr, adj. munificent. stór-merki, n. pl. wonderful things, great wonders; Guðs s., Edda (pref.), Fms. i. 133, Magn. 534, Symb. 29; hvat er fleira stórmerkja frá askinum, Edda. stór-merkiliga, adv. wonderfully, Mar. stór-merkiligr, adj. wonderful, Mar. stór-mikill, adj. huge, immense, Lv. 68, Eg. 59, Fms. i. 63, vii. 79, 278. stór-mjök, adv. very much, immensely, Fms. vii. 110, Fb. 1. 411, Bret. 54. stór-mæli, n. pl. great affairs; standa í stórmælum, Nj. 224: grave affairs, þau s. er ek hefi mót yðrum vilja brotið, Orkn. 118; eccl. the greater excommunication, hafði biskup í stórmælum ( in ban) tvá höfðingja, Sturl. ii. 2; lýsa stórmælum yfir, to excommunicate, iii. 201; biskup vildi ekki með hann tala, þvíat hann var í stórmælum, Bs. i. 286, 490, Stat. 260, Anecd. 8, 26. stór-nauðsynjar, f. pl. hard necessity, Gþl. 27, 352. stór-nær, adv. very nigh, Bs. i. 21. stór-orðr, adj. using big words, Fms. i. 75, xi. 94; stórort kvæði ok úfagrt, a big-worded, high-sounding poem, Ísl. ii. 237. stór-ráð, n. pl. great undertakings, Fms. i. 83. stór-ráða-samr, adj. daring, venturesome, Grett. 158. stór-ráðr, adj. ambitious; stórráð ok ráðgjörn, Fms. x. 220; s. ok ágjarn, vii. 28, Orkn. 144; a nickname, Sigríðr stórráða, cp. Lat. superbus. stór-ref-singar, f. pl. severe punishment. Fms. vii. 36. stór-regn, n. pl. heavy rains. Fms. viii. 202. stór-reki, m. ‘big-wreck’ big pieces of jetsum; allan stórreka, opp. to smáreki, Vm. 129. stór-riðinn, part. with big meshes, of a net. stór-ritaðr, part. written in large letters, Pm. 125. stór-ríki, n. pl. great empires, Bs. ii. 43. stór-ríkr, adj. very powerful, Ísl. ii. 202, v. l. stór-ræði, n. pl. daring, dangerous, great undertakings, Gþl. (pref. vi), Nj. 66, Fms. i. 83, vi. 10, 37, viii. 120, Sks. 746. stórræða-maðr, m. a man of great aims. Fms. ix. 283. stór-rök, n. pl. mighty events, Hom. 55. stór-sakar, f. pl. great offences. Fms. ii. 4, 33, Ld. 172. stór-samligr, adj. severe, Sks. 49. stór-sár, n. pl. grievous wounds, Fms. iii. 118. stór-skaðar, m. pl. great damage, Bs. i. 144. stór-skip, n. pl. great ships. Fms. vii. 259. stór-skorinn, part. huge, gaunt, Fb. i. 566; mikill vexti ok s., Bárð. 175; s. í andliti, Fb. i. 258; s. sem Goliath, Stj. 464; stórskorit höfuð, Grett. 83 new Ed. stór-skriptir, f. pl. heavy penances, K. Á. 192, H. E. i. 509; stórskripta-maðr, ii. 78. stór-skuldir, f. pl. great debts, Grág. i. 500. stór-slög, n. pl. great visitations, plagues, Stj. 268. stór-smiðr, m. a notable workman, Eg. 4. stór-smíði, n. pl. a huge, bulky work, Edda 19. stór-staðir, m. pl. great towns, Stj. 68; in Icel. or Norway of great church-prebends, Fms. vi. 157. stór-stígr, adj. long-striding. stór-straumr, m. a spring tide. stór-streymt, n. adj. = stórstraumr. stór-sveitir, f. pl. a large detachment., Fms. ix. 429. stór-syndir, f. pl. great sins, H. E. i. 521. stór-sæmdir, f. pl. great honours, Nj. 134, Fms. xi. 331. stór-sæti, n. pl. large ricks, Eb. 150, 224, Brandkr. 30. stór-tákn, n. pl. great wonders. Fms. i. 29, Stj. 261; sing., Bs. i. 42. stór-tignir, f. pl. high dignity, 625. 98. stór-tíðindi, n. pl. great tidings, great events, Fms. iii. 15, vi. 230, Nj. 195, Rb. 394, Sturl. i. 107 C; wonders, Edda 14, Fms. xi. 38. stór-tré, n. pl. huge beams, Karl. 448, Fms. x. 358, Krók. stóru-gi, see stórr (A. IV. 4). stór-úðigr, adj. high-minded, Hbl. 15, Valla L. stór-vandi, a, m. a great difficulty, Sturl. ii. 79. stór-vandræði, n. pl. id., Fms. vii. 25. stór-vegir, m. pl. broad roads, highways, Barl. 190. stór-vegligr, adj. very honourable, Hkr. ii. 100. stór-veizlur, f. pl. great banquets, Fms. i. 291. stór-vel, adv. right well, Eg. 60, 423, Ísl. ii. 382. stór-verk, n. pl. great deeds, Fms. v. 345. stór-viðaðr, adj. large timbered, Fms. ii. 218. stór-viðir, m. pl. great timbers, big beams, Fms. ii. 328, x. 361. Nj. 201, Bs. i. 81. stór-viðri, n. a great tempest, Fms. vii. 310, Grett. 153. stór-virki, n. pl. great feats, Fms. i. 287, ii. 109, vi. 55, Nj. 193, Ld. 40, Eg. 686, Korm. 242, Al. 160. stór-virkr, adj. working mightily; sterkr ok s., working like a giant, Bárð. 163; stórvirkr, opp. to góðvirkr, Nj. 55: as the name of a giant, Edda (Gl.), Fas. i. (Hervar. S. begin.) stór-vitr, adj. very wise, Nj. 22, Fms. i. 31, vi. 10, xi. 13, 205. stór-víða, adv. very widely, Fbr. 41. stór-yrði, n. pl. big words, Eg. 258, Nj. 261, Fms. ix. 419, x. 71, xi. 256, Al. 18. stór-ýðigr, adj. = stórúðigr, Valla L. 208. stór-þing, n. a ‘storthing,’ great council (oecumenical), Karl. 548, Pr. 104, Rb. stór-þorp, n. pl. great villages, Fagrsk. ch. 193. stór-þungt, n. adj. very heavy, Eb. 284. stór-þurftir, f. pl. great need, Bs. i. 525. stór-ættaðr, adj. high-born, Eg. 16, Nj. 178, Fms. i. 186, vi. 246. stór-ættir, f. pl. great families.

m. a breaker, destroyer MBh. ;

1. adjective

2. pronoun

3. adverb

1) (by) a great deal; (by) far:

2) to a great extent or degree:

SUBJECT AREA: Electronics and information technology

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Kurtz took his first degree in mathematics at the University of California in Los Angeles (UCLA), where he also gained experience in numerical methods as a result of working in the National Bureau of Standards Institute for Numerical Analysis located on the campus. In 1956 he obtained a PhD in statistics at Princeton, after which he took up a post as an instructor at Dartmouth College in Hanover, New Hampshire. There he found a considerable interest in computing was already in existence, and he was soon acting as the Dartmouth contact with the New England Regional Computer Center at Massachusetts Institute of Technology, an initiative partly supported by IBM. With Kemeny, he learned the Share Assembly Language then in use, but they were concerned about the difficulty of programming computers in assembly language and of teaching it to students and colleagues at Dartmouth. In 1959 the college obtained an LGP-30 computer and Kurtz became the first Director of the Dartmouth Computer Center. However, the small memory (4 k) of this 30-bit machine precluded its use with the recently available high-level language Algol 58. Therefore, with Kemeny, he set about developing a simple language and operating system that would use simple English commands and be easy to learn and use. This they called the Beginners All-purpose Symbolic Instruction Code (BASIC). At the same time they jointly supervised the design and development of a time-sharing system suitable for college use, so that by 1964, when Kurtz became an associate professor of mathematics, they had a fully operational BASIC system; by 1969 a sixth version was already in existence. In 1966 Kurtz left Dartmouth to become a Director of the Kiewit Computer Center, and then, in 1975, he became a Director of the Office of Academic Computing; in 1978 he returned to Dartmouth as Professor of Mathematics. He also served on various national committees.

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SUBJECT AREA: Architecture and building

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Born into a High Church and Royalist family, the young Wren early showed outstanding intellectual ability and at Oxford in 1654 was described as "that miracle of a youth". Educated at Westminster School, he went up to Oxford, where he graduated at the age of 19 and obtained his master's degree two years later. From this time onwards his interests were in science, primarily astronomy but also physics, engineering and meteorology. While still at college he developed theories about and experimentally solved some fifty varied problems. At the age of 25 Wren was appointed to the Chair of Astronomy at Gresham College in London, but he soon returned to Oxford as Savilian Professor of Astronomy there. At the same time he became one of the founder members of the Society of Experimental Philosophy at Oxford, which was awarded its Royal Charter soon after the Restoration of 1660; Wren, together with such men as Isaac Newton, Robert Hooke, John Evelyn and Robert Boyle, then found himself a member of the Royal Society.

Wren's architectural career began with the classical chapel that he built, at the request of his uncle, the Bishop of Ely, for Pembroke College, Cambridge (1663). From this time onwards, until he died at the age of 91, he was fully occupied with a wide and taxing variety of architectural problems which he faced in the execution of all the great building schemes of the day. His scientific background and inventive mind stood him in good stead in solving such difficulties with an often unusual approach and concept. Nowhere was this more apparent than in his rebuilding of fifty-one churches in the City of London after the Great Fire, in the construction of the new St Paul's Cathedral and in the grand layout of the Royal Hospital at Greenwich.

The first instance of Wren's approach to constructional problems was in his building of the Sheldonian Theatre in Oxford (1664–9). He based his design upon that of the Roman Theatre of Marcellus (13–11 BC), which he had studied from drawings in Serlio's book of architecture. Wren's reputation as an architect was greatly enhanced by his solution to the roofing problem here. The original theatre in Rome, like all Roman-theatres, was a circular building open to the sky; this would be unsuitable in the climate of Oxford and Wren wished to cover the English counterpart without using supporting columns, which would have obscured the view of the stage. He solved this difficulty mathematically, with the aid of his colleague Dr Wallis, the Professor of Geometry, by means of a timber-trussed roof supporting a painted ceiling which represented the open sky.

The City of London's churches were rebuilt over a period of nearly fifty years; the first to be completed and reopened was St Mary-at-Hill in 1676, and the last St Michael Cornhill in 1722, when Wren was 89. They had to be rebuilt upon the original medieval sites and they illustrate, perhaps more clearly than any other examples of Wren's work, the fertility of his imagination and his ability to solve the most intractable problems of site, limitation of space and variation in style and material. None of the churches is like any other. Of the varied sites, few are level or possess right-angled corners or parallel sides of equal length, and nearly all were hedged in by other, often larger, buildings. Nowhere is his versatility and inventiveness shown more clearly than in his designs for the steeples. There was no English precedent for a classical steeple, though he did draw upon the Dutch examples of the 1630s, because the London examples had been medieval, therefore Roman Catholic and Gothic, churches. Many of Wren's steeples are, therefore, Gothic steeples in classical dress, but many were of the greatest originality and delicate beauty: for example, St Mary-le-Bow in Cheapside; the "wedding cake" St Bride in Fleet Street; and the temple diminuendo concept of Christ Church in Newgate Street.

In St Paul's Cathedral Wren showed his ingenuity in adapting the incongruous Royal Warrant Design of 1675. Among his gradual and successful amendments were the intriguing upper lighting of his two-storey choir and the supporting of the lantern by a brick cone inserted between the inner and outer dome shells. The layout of the Royal Hospital at Greenwich illustrates Wren's qualities as an overall large-scale planner and designer. His terms of reference insisted upon the incorporation of the earlier existing Queen's House, erected by Inigo Jones, and of John Webb's King Charles II block. The Queen's House, in particular, created a difficult problem as its smaller size rendered it out of scale with the newer structures. Wren's solution was to make it the focal centre of a great vista between the main flanking larger buildings; this was a masterstroke.

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   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)

   1) There Are Ideas That Have Their Own True and Immutable Nature

   And what I believe to be more important here is that I find in myself an infinity of ideas of certain things which cannot be assumed to be pure nothingness, even though they may have perhaps no existence outside of my thought. These things are not figments of my imagination, even though it is within my power to think of them or not to think of them; on the contrary, they have their own true and immutable natures. Thus, for example, when I imagine a triangle, even though there may perhaps be no such figure anywhere in the world outside of my thought, nor ever have been, nevertheless the figure cannot help having a certain determinate nature... or essence, which is immutable and eternal, which I have not invented and which does not in any way depend upon my mind. (Descartes, 1951, p. 61)

   2) Examine What Is within Our Reach

   Let us console ourselves for not knowing the possible connections between a spider and the rings of Saturn, and continue to examine what is within our reach. (Voltaire, 1961, p. 144)

   3) Modern Philosophy Starts with the Cartesian Catastrophe

   As modern physics started with the Newtonian revolution, so modern philosophy starts with what one might call the Cartesian Catastrophe. The catastrophe consisted in the splitting up of the world into the realms of matter and mind, and the identification of "mind" with conscious thinking. The result of this identification was the shallow rationalism of l'esprit Cartesien, and an impoverishment of psychology which it took three centuries to remedy even in part. (Koestler, 1964, p. 148)

   4) The Rightful Claims of Philosophy

   It has been made of late a reproach against natural philosophy that it has struck out on a path of its own, and has separated itself more and more widely from the other sciences which are united by common philological and historical studies. The opposition has, in fact, been long apparent, and seems to me to have grown up mainly under the influence of the Hegelian philosophy, or, at any rate, to have been brought out into more distinct relief by that philosophy.... The sole object of Kant's "Critical Philosophy" was to test the sources and the authority of our knowledge, and to fix a definite scope and standard for the researches of philosophy, as compared with other sciences.... [But Hegel's] "Philosophy of Identity" was bolder. It started with the hypothesis that not only spiritual phenomena, but even the actual world-nature, that is, and man-were the result of an act of thought on the part of a creative mind, similar, it was supposed, in kind to the human mind.... The philosophers accused the scientific men of narrowness; the scientific men retorted that the philosophers were crazy. And so it came about that men of science began to lay some stress on the banishment of all philosophic influences from their work; while some of them, including men of the greatest acuteness, went so far as to condemn philosophy altogether, not merely as useless, but as mischievous dreaming. Thus, it must be confessed, not only were the illegitimate pretensions of the Hegelian system to subordinate to itself all other studies rejected, but no regard was paid to the rightful claims of philosophy, that is, the criticism of the sources of cognition, and the definition of the functions of the intellect. (Helmholz, quoted in Dampier, 1966, pp. 291-292)

   5) The Philosophy of Philosophy

   Philosophy remains true to its classical tradition by renouncing it. (Habermas, 1972, p. 317)

   6) Philosophy Is a Field Which Has Certain Central Questions

   I have not attempted... to put forward any grand view of the nature of philosophy; nor do I have any such grand view to put forth if I would. It will be obvious that I do not agree with those who see philosophy as the history of "howlers" and progress in philosophy as the debunking of howlers. It will also be obvious that I do not agree with those who see philosophy as the enterprise of putting forward a priori truths about the world.... I see philosophy as a field which has certain central questions, for example, the relation between thought and reality.... It seems obvious that in dealing with these questions philosophers have formulated rival research programs, that they have put forward general hypotheses, and that philosophers within each major research program have modified their hypotheses by trial and error, even if they sometimes refuse to admit that that is what they are doing. To that extent philosophy is a "science." To argue about whether philosophy is a science in any more serious sense seems to me to be hardly a useful occupation.... It does not seem to me important to decide whether science is philosophy or philosophy is science as long as one has a conception of both that makes both essential to a responsible view of the world and of man's place in it. (Putnam, 1975, p. xvii)

   7) The Central Task of Philosophy

   What can philosophy contribute to solving the problem of the relation [of] mind to body? Twenty years ago, many English-speaking philosophers would have answered: "Nothing beyond an analysis of the various mental concepts." If we seek knowledge of things, they thought, it is to science that we must turn. Philosophy can only cast light upon our concepts of those things.

   This retreat from things to concepts was not undertaken lightly. Ever since the seventeenth century, the great intellectual fact of our culture has been the incredible expansion of knowledge both in the natural and in the rational sciences (mathematics, logic).

   The success of science created a crisis in philosophy. What was there for philosophy to do? Hume had already perceived the problem in some degree, and so surely did Kant, but it was not until the twentieth century, with the Vienna Circle and with Wittgenstein, that the difficulty began to weigh heavily. Wittgenstein took the view that philosophy could do no more than strive to undo the intellectual knots it itself had tied, so achieving intellectual release, and even a certain illumination, but no knowledge. A little later, and more optimistically, Ryle saw a positive, if reduced role, for philosophy in mapping the "logical geography" of our concepts: how they stood to each other and how they were to be analyzed....

   Since that time, however, philosophers in the "analytic" tradition have swung back from Wittgensteinian and even Rylean pessimism to a more traditional conception of the proper role and tasks of philosophy. Many analytic philosophers now would accept the view that the central task of philosophy is to give an account, or at least play a part in giving an account, of the most general nature of things and of man. (Armstrong, 1990, pp. 37-38)

   8) Philosophy's Evolving Engagement with Artificial Intelligence and Cognitive Science

   In the beginning, the nature of philosophy's engagement with artificial intelligence and cognitive science was clear enough. The new sciences of the mind were to provide the long-awaited vindication of the most potent dreams of naturalism and materialism. Mind would at last be located firmly within the natural order. We would see in detail how the most perplexing features of the mental realm could be supported by the operations of solely physical laws upon solely physical stuff. Mental causation (the power of, e.g., a belief to cause an action) would emerge as just another species of physical causation. Reasoning would be understood as a kind of automated theorem proving. And the key to both was to be the depiction of the brain as the implementation of multiple higher level programs whose task was to manipulate and transform symbols or representations: inner items with one foot in the physical (they were realized as brain states) and one in the mental (they were bearers of contents, and their physical gymnastics were cleverly designed to respect semantic relationships such as truth preservation). (A. Clark, 1996, p. 1)

   9) The Enduring Value of Philosophy

   Socrates of Athens famously declared that "the unexamined life is not worth living," and his motto aptly explains the impulse to philosophize. Taking nothing for granted, philosophy probes and questions the fundamental presuppositions of every area of human inquiry.... [P]art of the job of the philosopher is to keep at a certain critical distance from current doctrines, whether in the sciences or the arts, and to examine instead how the various elements in our world-view clash, or fit together. Some philosophers have tried to incorporate the results of these inquiries into a grand synoptic view of the nature of reality and our human relationship to it. Others have mistrusted system-building, and seen their primary role as one of clarifications, or the removal of obstacles along the road to truth. But all have shared the Socratic vision of using the human intellect to challenge comfortable preconceptions, insisting that every aspect of human theory and practice be subjected to continuing critical scrutiny....

   Philosophy is, of course, part of a continuing tradition, and there is much to be gained from seeing how that tradition originated and developed. But the principal object of studying the materials in this book is not to pay homage to past genius, but to enrich one's understanding of central problems that are as pressing today as they have always been-problems about knowledge, truth and reality, the nature of the mind, the basis of right action, and the best way to live. These questions help to mark out the territory of philosophy as an academic discipline, but in a wider sense they define the human predicament itself; they will surely continue to be with us for as long as humanity endures. (Cottingham, 1996, pp. xxi-xxii)

    10) The Distinction between Dionysian Man and Apollonian Man, between Art and Creativity and Reason and Self- Control

   In his study of ancient Greek culture, The Birth of Tragedy, Nietzsche drew what would become a famous distinction, between the Dionysian spirit, the untamed spirit of art and creativity, and the Apollonian, that of reason and self-control. The story of Greek civilization, and all civilizations, Nietzsche implied, was the gradual victory of Apollonian man, with his desire for control over nature and himself, over Dionysian man, who survives only in myth, poetry, music, and drama. Socrates and Plato had attacked the illusions of art as unreal, and had overturned the delicate cultural balance by valuing only man's critical, rational, and controlling consciousness while denigrating his vital life instincts as irrational and base. The result of this division is "Alexandrian man," the civilized and accomplished Greek citizen of the later ancient world, who is "equipped with the greatest forces of knowledge" but in whom the wellsprings of creativity have dried up. (Herman, 1997, pp. 95-96)