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1 well-defined problem
Большой англо-русский и русско-английский словарь > well-defined problem
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2 well-defined problem
1) Вычислительная техника: хорошо структурированная задача, хорошо структурированная проблема2) Робототехника: корректная задача, хорошо определённая задача3) Макаров: хорошо поставленная задача -
3 well-defined problem
хорошо структурированная задача; хорошо структурированная проблемаEnglish-Russian dictionary of computer science and programming > well-defined problem
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4 well-defined problem
хорошо определенная задача, корректная задача
Англо-русский словарь по робототехнике > well-defined problem
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5 well-defined problem
English-Russian scientific dictionary > well-defined problem
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6 well-defined
well-defined [-dɪ'faɪnd](a) (distinct → colour, contrasts, shape) bien défini, net(b) (precise → problem) bien défini, précis;∎ within well-defined limits dans des limites bien définiesUn panorama unique de l'anglais et du français > well-defined
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7 algorithm: A finite set of well-defined rules for the solution of a problem in a finite number of operations
Общая лексика: алгоритм: конечное множество точно определённых правил для решения конкретной задачи в определенное к (см. IEC 61499-1)Универсальный англо-русский словарь > algorithm: A finite set of well-defined rules for the solution of a problem in a finite number of operations
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8 problem
1) задача; проблема3) трудность, затруднение•- boundary value problem - card matching problem - central limit problem - decision problem under risk - decision problem under uncertainty - extremum problem - fair division problem - gambling problem - gasoline blending problem - incompletely structured problem - optimal path problem - optimal stopping problem - portfolio selection problem - precisely specified problem - recursively solvable problem - sequential decision programming problem - sequential occupancy problem - shortest path problem - shortest route problem - standard control problem - three houses and three wells problem -
9 problem
задача; проблема- accounting problem
- allocation problem
- assignment problem
- ballot problem
- benchmark problem
- blending problem
- bottleneck problem
- boundary-value problem
- boundary problem
- business problem
- Byzantine Generals problem
- center problem
- check problem
- chess problem
- commonly encountered problem
- computational problem
- continuum problem
- covering problem
- data problem
- data-set problem
- daunting problem
- decision problem
- deducibility problem
- design problem
- dining philosophers' problem
- dual problem
- eigenvalue assignment problem
- eigenvalue problem
- estimation problem
- EVA problem
- extremely ill-conditioned problem
- fault-location problem
- filtering problem
- findpath problem
- finger-pointing problem
- flow problem
- frame problem
- free-boundary problem
- game-theory problem
- game problem
- graph theoretic problem
- graphics problem
- ill-conditioned problem
- ill-defined problem
- ill-posed problem
- inference problem
- information retrieval problem
- initial value problem
- intractable problem
- job-shop problem
- knapsack problem
- Konigsberg bridge problem
- labyrinth problem
- location problem
- logical problem
- management problem
- market analysis problem
- marriage problem
- maximum flow problem
- maximum network flow problem
- mildly ill-posed problem
- minimal connector problem
- model problem
- multivariate problem
- newspaper-boy problem
- ninety percent complete problem
- nominal design problem
- off-by-one problem
- omelet problem
- one-sample problem
- postman problem
- programming problem
- projection problem
- pursuit problem
- quadratic assignment problem
- queuing problem
- race problem
- ramification problem
- real-time problem
- real-world problem
- reducibility problem
- resource allocation problem
- routing problem
- ruin problem
- satisfiability problem
- scheduling problem
- search problem
- severely ill-posed problem
- shortest route problem
- simulated problem
- software problem
- sparse problem
- stale data problem
- stochastic problem
- switchbox routing problem
- switchbox problem
- target assignment problem
- test problem
- three-dimensional problem
- time transportation problem
- trade-off problem
- traffic problem
- transport problem
- transportation problem
- traveling salesman problem
- trouble-location problem
- troubleshooting problem
- unconstrained problem
- undecidable problem
- underdetermined problem
- unsolvable problem
- unstructured problem
- variational problem
- vessel loading problem
- waiting line problem
- weak bridge problem
- well-behaved problem
- well-defined problem
- well-posed problemEnglish-Russian dictionary of computer science and programming > problem
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10 well
well [wel]1. noun(for water, oil) puits m3. adverba. ( = satisfactorily, skilfully) [behave, sleep, eat, treat, remember] bien• well done! bravo !• well played! bien joué !• you're well out of it! c'est une chance que tu n'aies plus rien à voir avec cela !b. (intensifying = very much, thoroughly) bien• well over 1,000 people bien plus de 1 000 personnesc. ( = with good reason, with equal reason) one might well ask why on pourrait à juste titre demander pourquoi• you might (just) as well say that... autant dire que...• and it rained as well! et par-dessus le marché il a plu !e. ( = positively) to think/speak well of penser/dire du bien de4. exclamation• he has won the election! -- well, well, well! il a été élu ! -- tiens, tiens !• well, what do you think of it? alors qu'en dites-vous ?• well, here we are at last! eh bien ! nous voilà enfin !• you know Paul? well, he's getting married vous connaissez Paul ? eh bien il se marie• are you coming? -- well... I've got a lot to do here vous venez ? -- c'est que... j'ai beaucoup à faire ici5. adjective(comparative, superlative best)a. bien, bon• that's all very well but... tout ça c'est bien joli mais... (PROV) all's well that ends well(PROV) tout est bien qui finit bienb. ( = healthy) how are you? -- very well, thank you comment allez-vous ? -- très bien, merci• get well soon! remets-toi vite !c. (cautious) it is as well to remember that... il ne faut pas oublier que...6. prefix• well-chosen/dressed bien choisi/habillé7. compounds• you would be well-advised to leave vous auriez (tout) intérêt à partir ► well-appointed adjective [house, room] bien aménagé► well-kept adjective [house, garden, hair] bien entretenu ; [hands, nails] soigné ; [secret] bien gardé► well-meaning adjective [person] bien intentionné ; [remark, action] fait avec les meilleures intentions• you don't know when you're well-off ( = fortunate) tu ne connais pas ton bonheur ► well-paid adjective bien payé• he got many letters from well-wishers il a reçu de nombreuses lettres d'encouragement ► well-woman clinic noun (British) centre prophylactique et thérapeutique pour femmes* * *I 1. [wel]1) ( in good health)are you well? — vous allez bien?, tu vas bien?
‘how is he?’ - ‘as well as can be expected’ — ‘comment va-t-il?’ - ‘pas trop mal étant donné les circonstances’
2) ( in satisfactory state) bienthat's all very well, but — tout ça c'est bien beau, mais
it's all very well for you to laugh, but — tu peux rire, mais
3) ( prudent)4) ( fortunate)it was just as well for him that the shops were still open — il a eu de la chance que les magasins aient été encore ouverts
2.the flight was delayed, which was just as well — le vol a été retardé, ce qui n'était pas plus mal
1) ( satisfactorily) bienI did well in the general knowledge questions — je me suis bien débrouillé pour les questions de culture générale
to do well at school — être bon/bonne élève
to do well by somebody — se montrer généreux/-euse avec quelqu'un
some businessmen did quite well out of the war — certains hommes d'affaires se sont enrichis pendant la guerre
she didn't come out of it very well — ( of situation) elle ne s'en est pas très bien sortie; (of article, programme etc) ce n'était pas très flatteur pour elle
2) ( used with modal verbs)I can well believe it — je veux bien le croire, je n'ai pas de mal à le croire
‘shall I shut the door?’ - ‘you might as well’ — ‘est-ce que je ferme la porte?’ - ‘pourquoi pas’
she looked shocked, as well she might — elle a eu l'air choquée, ce qui n'avait rien d'étonnant
3) ( intensifier) bien, largementthe weather remained fine well into September — le temps est resté au beau fixe pendant une bonne partie du mois de septembre
she was active well into her eighties — elle était toujours active même au-delà de ses quatre-vingts ans
4) ( approvingly)5)3.exclamation ( expressing astonishment) eh bien!; (expressing indignation, disgust) ça alors!; ( expressing disappointment) tant pis!; (after pause in conversation, account) bon; ( qualifying statement) enfinwell, you may be right — après tout, tu as peut-être raison
well, that's too bad — c'est vraiment dommage
well then, what's the problem? — alors, quel est le problème?
oh well, there's nothing I can do about it — ma foi, je n'y peux rien
4.well, well, well, so you're off to America? — alors comme ça, tu pars aux États-Unis!
as well adverbial phrase aussi5.as well as prepositional phrase aussi bien quethey have a house in the country as well as an apartment in Paris — ils ont à la fois une maison à la campagne et un appartement à Paris
••to be well in with somebody — (colloq) être bien avec quelqu'un (colloq)
to leave well alone GB ou well enough alone US — ne pas s'en mêler
II 1. [wel] 2.you're well out of it! — (colloq) heureusement que tu n'as plus rien à voir avec ça!
Phrasal Verbs:- well up -
11 well
I [wel]2) (in satisfactory state) benethat's all very well, but — è tutto molto bello, però
it's all very well for you to laugh, but — tu fai presto a ridere, ma
3) (prudent)it would be as well for you to... — faresti meglio a
4) (fortunate)it was just as well for him that... — gli è andata bene che...
II [wel]the flight was delayed, which was just as well — per fortuna il volo era in ritardo
1) (satisfactorily) [treat, behave, sleep etc.] beneto do oneself well — trattarsi bene, non farsi mancare nulla
to do well by sb. — mostrarsi gentile con qcn., comportarsi bene con qcn
I can well believe it — credo bene, ci credo
"shall I shut the door?" - "you might as well" — "chiudo la porta?" - "fai pure"
he looked shocked, as well he might — sembrava scioccato, e non c'è da stupirsi
3) (intensifier) bento speak well of sb. — parlare bene di qcn
5)to wish sb. well — augurare ogni bene a qcn
6)as well as — (in addition to) così come
••to be well in with sb. — colloq. stare bene con qcn.
to be well up in sth. — conoscere bene qcs.
to leave well alone — BE o
well enough alone — AE (not get involved) non metterci le mani
III [wel]you're well out of it! — colloq. per fortuna ne sei fuori!
interiezione (expressing astonishment) beh; (expressing indignation, disgust) insomma; (expressing disappointment) bene; (after pause in conversation, account) allorawell, you may be right — beh, forse hai ragione
well then, what's the problem? — allora, qual è il problema?
oh well, there's nothing I can do about it — beh, non posso farci niente
IV [wel]well, well, well, so you're off to America? — e così parti per l'America?
1) (in ground) pozzo m.2) (pool) sorgente f., fonte f.3) ing. (for stairs, lift) vano m.4) BE (in law court) = spazio riservato ai difensoriV [wel]- well up* * *(to have a good, or bad, opinion of: She thought highly of him and his poetry.) (avere una buona/cattiva opinione di)* * *I [wɛl]1. n2. vi(tears, emotions) sgorgare•- well upII [wɛl] better comp best superl1. adv1) (gen) benewell done! — ben fatto!, bravo (-a)!
well over a thousand — molto or ben più di mille
all or only too well — anche troppo bene
he's well away — (fam: drunk) è completamente andato
2)(probably, reasonably)
we might just as well have... — tanto valeva...she cried, as well she might — piangeva a buon diritto
one might well ask why... — ci si potrebbe ben chiedere perché...
I might or may as well come — quasi quasi vengo
3)as well — (in addition) anche
she sings, as well as playing the piano — oltre a suonare il piano, canta
we worked hard, but we had some fun as well — abbiamo lavorato sodo, ma ci siamo anche divertiti
2. adj1)to be well — stare bene2) (acceptable, satisfactory) buono (-a)that's all very well, but... — va benissimo, ma..., d'accordo, ma...
3. excl(gen) bene, (resignation, hesitation) be'well, as I was saying... — dunque, come stavo dicendo...
well, well, well! — ma guarda un po'!
very well then — va bene, molto bene
very well, if that's the way you want it — (unenthusiastic) va bene, se questo è quello che vuoi
well I never! — ma no!, ma non mi dire!
well there you are then! — ecco, hai visto!
it's enormous! Well, quite big anyway — è gigantesco! Be', diciamo molto grande
4. nto wish sb well — augurare ogni bene a qn, (in exam, new job) augurare a qn di riuscire
* * *well (1) /wɛl/n.1 pozzo: artesian well, pozzo artesiano; oil wells, pozzi petroliferi; to sink a well, scavare un pozzo5 (naut.) pozzo delle pompe● (naut.) well boat, (barca) vivaio □ well borer, scavatore di pozzi; (ind. min.) sonda-trivella □ well-boring, che scava pozzi □ (ind. min.) well core, carota □ well-curb, vera (di pozzo) □ (naut.) well deck, ponte a pozzo (per es., di aliscafo) □ (ind. min.) well drilling, trivellazione; sondaggio □ well-hole, pozzo; (edil.) tromba (o pozzo) delle scale □ (metall.) the well of a blast furnace, il crogiolo di un altoforno □ well sinker, scavatore di pozzi □ well sweep, pertica del pozzo; shaduf, sciaduf □ well water, acqua di pozzo.♦ well (2) /wɛl/1 bene; attentamente; diligentemente; rettamente; con cura; a fondo; completamente: to sleep well, dormire bene; to speak well of sb., parlar bene di q.; Stir it well before you drink it, rimescolalo bene prima di berlo; Green and yellow go well together, il verde e il giallo stanno bene insieme; to treat sb. well, trattar bene q.; The work is well done, il lavoro è fatto bene; DIALOGO → - After an exam- I think I answered the questions quite well, credo di aver risposto abbastanza bene a tutte le domande; to know sb. well, conoscer bene q.; conoscere a fondo q.2 bene; a ragione: You may well say so, puoi ben dirlo; You did well to stay at home, hai fatto bene a restare a casa; You can't very well back out now, non puoi tirarti indietro adesso a ragione● (fam.) well and truly, del tutto; completamente □ (fam.) well and truly drunk, ubriaco fradicio □ well away, avanti (nel fare qc.); a buon punto; (pop.) bell'e che andato ( cioè ubriaco o addormentato) □ to be well on in life, essere avanti con gli anni □ It's well on midday, è quasi mezzogiorno □ to be well out of it, essersela cavata a buon mercato; esserne fuori □ to be well past forty [fifty, sixty], aver passato la quarantina [la cinquantina, la sessantina] da un pezzo □ to be well up in st., essere al corrente di qc.; conoscere bene qc. □ as well, anche; pure: I shall come as well, verrò io pure; DIALOGO → - Booking online- We might as well book now, potremmo anche (o tanto vale) prenotare adesso NOTA D'USO: - also / too- □ as well as, così come; tanto quanto; non solo ma anche; come pure: He gave me shelter as well as food, mi diede non solo asilo, ma anche da sfamarmi □ to come off well, ( di persona) cavarsela, uscirne bene; ( di cosa) riuscir bene; (fam.) fare una bella figura □ to do well, fare bene ( nella vita, ecc.): Your son will do well, tuo figlio farà bene (o si farà strada) □ to do oneself well, trattarsi bene; non farsi mancar nulla □ to do well out of the sale of one's car, vendere bene la propria automobile □ to examine st. well, esaminare qc. a fondo □ just as well = (That's) just as well ► sotto □ to live well, vivere nell'agiatezza; passarsela bene □ to look well, guardar bene; cercare attentamente; ( anche: di persona) stare bene, fare la propria figura; ( di cosa) stare bene: Jane looks well in green, Jane sta bene vestita di verde; Does this tie look well on me?, mi sta bene questa cravatta? □ perfectly well, alla perfezione; perfettamente □ pretty well finished, quasi finito □ to receive sb. well, fare buona accoglienza a q. □ (impers.) to speak well for sb., far onore a q.: It speaks well for him that he refused, gli fa onore l'aver rifiutato □ to stand well with sb., essere in buoni rapporti con q.; essere nelle buone grazie di q. □ very well, benissimo: You've done your homework very well, hai fatto benissimo i tuoi compiti □ DIALOGO → - Business trip 2- Well done!, ben fatto!; bravo! □ Well met!, proprio te!; che piacere incontrarti! □ Well run! hai fatto un'ottima corsa!; bravo! □ That boy will do well ( in life), quel ragazzo si farà strada (nella vita) □ Look well to yourself, bada a te!; sta' bene attento! □ You might ( just) as well throw your money away, tanto varrebbe che i tuoi soldi li buttassi via □ ( That's) just as well, poco male!; meglio così!; pazienza!; fa lo stesso! □ (prov.) Well begun is half done, chi ben comincia è a metà dell'opera □ (prov.) Let well ( enough) alone, il meglio è nemico del bene.♦ well (3) /wɛl/1 bene; in buona salute; in buone condizioni: Is he well or ill?, sta bene o è malato?; I am feeling well today, oggi mi sento bene; I am perfectly well, sto benissimo; DIALOGO → - Greetings and other useful phrases- I'm very well, thank you, sto molto bene, grazie; fairly (o reasonably) well, abbastanza bene2 bene; opportuno; consigliabile; utile; giusto; bello: It would be well to inquire, sarebbe bene indagareB a. attr.● well and good!, d'accordo!; sta bene!; alla buon'ora! □ well enough, abbastanza bene; benino; discretamente: I am well enough, sto abbastanza bene □ to be well off, passarsela bene; essere in buone condizioni finanziarie □ to be well up in Latin, essere forte in latino □ to get well ( again), guarire; ristabilirsi; DIALOGO → - Feeling ill- Get well soon!, guarisci presto! □ to look well (o to be looking well), avere una bella cera (o un bell'aspetto) □ (iron.) It's all very well … but, sta bene… ma □ All's well, tutto a posto!; tutto bene! □ (prov.) All's well that ends well, tutto è bene quel che finisce bene.well (4) /wɛl/n. [u]● It was well for her that you were present, fu una fortuna (fam.: un bene) per lei che tu fossi presente.♦ well (5) /wɛl/inter.beh; ebbene; dunque; allora: Well, what shall we do now?, beh, e ora che facciamo?; Well, what about it?, ebbene, che ne dici?; Well, as I was saying…, dunque, come stavo dicendo…; Well then?, e allora?, e poi?; e con ciò?● well, but, sì, ma: Well, but what about the others?, sì, ma gli altri? □ Very well!, benissimo!; benone!; d'accordo!; ( anche) fa pure!; staremo a vedere! □ Well, I see, bene, bene; capisco □ Well, to be sure!, ma certo!; questa sì che è bella!; ( con incredulità) ma no!; davvero? □ Well, I never!, chi l'avrebbe mai detto?; ma no!; impossibile!well (6) /wɛl/pref.(in numerosi composti, quali:) well-adjusted, ben inserito ( nel lavoro, nella società); well-advised, saggio; prudente: a well-advised decision, una decisione saggia; well-appointed, bene attrezzato; bene arredato; ben equipaggiato: a well-appointed office, un ufficio bene arredato; well-balanced, ben proporzionato; bilanciato; equilibrato: (med.) a well-balanced diet, una dieta bilanciata; a well-balanced mind, una mente equilibrata; ( boxe, lotta, ecc.) well-balanced stance, positura bene impostata; buona impostazione della posizione; well-behaved, educato, beneducato; well-beloved, beneamato; amatissimo; well-born, bennato, di buona famiglia; well-bred, ( di persona) educato, beneducato; ( di cavallo, ecc.) di razza; ( di un uomo) well-built, ben piantato; ben messo; well-chosen, scelto bene, appropriato; well-conditioned, onesto, retto; ( di animale) sano; well-conducted, bene costumato, che si comporta bene, disciplinato; ( di azienda, ecc.) gestito bene, bene organizzato; well-connected, di buon parentado; che ha buone relazioni sociali (o commerciali); ( del gioco) well-constructed, ben costruito; articolato; ( di un giocatore) well-coordinated, coordinato; che ha una buona coordinazione; well-defined, ben definito; ( di concetto) chiaro, esplicito; well-deserved, meritato; giusto: well-deserved win, vittoria meritata; well-disposed, bendisposto, benevolo, favorevole; well-doer, chi fa del bene; persona virtuosa; well-doing, l'agir bene; la virtù; well-done, ben fatto; ( di cibo) ben cotto; well-dressed, ben vestito; well-earned, meritato: a well-earned reward, una ricompensa meritata; well-endowed, ben dotato ( fisicamente); superdotato; well established, ( di organo, potere, ecc.) solido, saldo; ( di costume) inveterato, radicato; ( di professionista) affermato; (arc.) well-favoured, bello, di bell'aspetto; well-fed, ben nutrito; well-found, bene attrezzato, ben equipaggiato; well-founded, fondato: well-founded charges, accuse fondate; (arc.) well-graced, aggraziato; attraente; well-groomed, attillato, azzimato; well-grounded, fondato; bene informato, competente, esperto; (fig. fam.) well-heeled, ricco, facoltoso, agiato; ( anche) bene organizzato, ben strutturato; (fam.) well-hung, ( d'abito) che cade bene, che sta bene; ( d'uomo) ben messo ( fisicamente); ben piantato; ( di donna) prosperosa, popputa (pop.); well-informed, bene informato; al corrente; well-intentioned, ben intenzionato; (fatto) a fin di bene; well-judged, pieno di discernimento, assennato, saggio; ( sport) calcolato bene; calibrato; well-kept, ben tenuto; tenuto bene; well-knit, ( di persona) forte, robusto, ben piantato; ( di ragionamento, ecc.) coerente; ( di edificio, ecc.) solido; well-known, notorio, noto; rinomato; well-liked, popolare, amato; well-lined, ( dello stomaco) pieno; ( del portafogli) gonfio; well-made, ben fatto; di belle fattezze; well-managed, gestito bene; condotto bene; well-mannered, educato, cortese, beneducato; well-marked, chiaro, distinto, evidente; well-matched, bene assortito; bene accoppiato; ( sport: di un incontro) equilibrato; ( di due contendenti) di pari forza, dello stesso valore; well-meaning, ben intenzionato; well-meant, fatto (o detto) a fin di bene; (form.) well-nigh, quasi, pressoché; well-off, agiato, benestante, ricco; messo bene ( in fatto di attrezzature, servizi, ecc.); (fam.) fortunato; well-oiled, bene oliato; (fig.) complimentoso, untuoso; ( slang) sbronzo; well-ordered, bene ordinato; well-organised, ben organizzato; well-placed, ben piazzato; ‘Well played!’, ‘bella giocata!’; ‘bravo!’; well-prepared, ( di un atleta) preparato bene; ( di un piano di gioco, ecc.) studiato bene; well-preserved, conservato bene, in buono stato; ( di persona) che si conserva bene, benportante; well-proportioned, ben proporzionato; well-read, che ha letto molto, colto, istruito; well-regulated, bene ordinato, disciplinato; well-reputed, stimato, che gode di buona fama; well-rounded, (ben) finito; completo; ben tornito; (fig.) eclettico; well-seasoned, ( di legno, ecc.) ben stagionato; ( di cibo) ben condito; (fig.: di persona) di grande esperienza; well-set, compatto, saldo, solido; ( di persona) ben messo, ben piantato, robusto; well-set-up, ben fatto, ben piantato, robusto; agiato, facoltoso, ricco; well-spent, speso bene: a well-spent life, una vita spesa bene; well-spoken, facondo, eloquente, raffinato nel parlare; detto (o pronunciato) bene; che parla bene; (org. az.) well-staffed, ben fornito di personale; well-taken, tirato (o battuto) bene; bello; well-thought-of, che gode della considerazione generale; stimato (o benvoluto) da tutti; well-thought-out, ( di una decisione, di un passo) ponderato, ben meditato; ( di un progetto) pensato bene, ben progettato; ( di un libro) well-thumbed, pieno di ditate; (fig.) molto compulsato; well-timed, tempestivo, opportuno; well-to-do, agiato, benestante, ricco; well-tried, provato, sperimentato, sicuro: well-tried remedies, rimedi sicuri; well-trodden, assai frequentato; ( di frase, ecc.) well-turned, ben tornito; well-watered, ( di un giardino, ecc.) ben annaffiato; (agric.) ben irrigato; well-wisher, persona che vuol bene (o che è affezionata); fautore, sostenitore; well-wishing, benaugurante; well-worn, consunto, logoro, liso, frusto, sdrucito; (fig.) comune, trito, banale, vieto: a well-worn tale, una storiella trita.(to) well /wɛl/v. i.( di solito to well up, out, forth) scaturire; sgorgare; pullulare; zampillare: Bitter tears welled from her eyes ( o up in her eyes), amare lacrime le sono sgorgate dagli occhi; Suddenly water welled up, d'improvviso zampillò l'acqua.* * *I [wel]2) (in satisfactory state) benethat's all very well, but — è tutto molto bello, però
it's all very well for you to laugh, but — tu fai presto a ridere, ma
3) (prudent)it would be as well for you to... — faresti meglio a
4) (fortunate)it was just as well for him that... — gli è andata bene che...
II [wel]the flight was delayed, which was just as well — per fortuna il volo era in ritardo
1) (satisfactorily) [treat, behave, sleep etc.] beneto do oneself well — trattarsi bene, non farsi mancare nulla
to do well by sb. — mostrarsi gentile con qcn., comportarsi bene con qcn
I can well believe it — credo bene, ci credo
"shall I shut the door?" - "you might as well" — "chiudo la porta?" - "fai pure"
he looked shocked, as well he might — sembrava scioccato, e non c'è da stupirsi
3) (intensifier) bento speak well of sb. — parlare bene di qcn
5)to wish sb. well — augurare ogni bene a qcn
6)as well as — (in addition to) così come
••to be well in with sb. — colloq. stare bene con qcn.
to be well up in sth. — conoscere bene qcs.
to leave well alone — BE o
well enough alone — AE (not get involved) non metterci le mani
III [wel]you're well out of it! — colloq. per fortuna ne sei fuori!
interiezione (expressing astonishment) beh; (expressing indignation, disgust) insomma; (expressing disappointment) bene; (after pause in conversation, account) allorawell, you may be right — beh, forse hai ragione
well then, what's the problem? — allora, qual è il problema?
oh well, there's nothing I can do about it — beh, non posso farci niente
IV [wel]well, well, well, so you're off to America? — e così parti per l'America?
1) (in ground) pozzo m.2) (pool) sorgente f., fonte f.3) ing. (for stairs, lift) vano m.4) BE (in law court) = spazio riservato ai difensoriV [wel]- well up -
12 problem
[ˈprɔbləm]accounting problem бухгалтерская задача activity-analysis problem задача анализа операций algorithmic problem алгоритмическая проблема all integer problem вчт. полностью целочисленная задача allocation problem задача распределения approximating problem приближенная задача assignment problem задача о назначениях assignment problem задача о распределении auxiliary problem вспомогательная задача bargaining problem задача о торгах benchmark problem вчт. эталонная тестовая задача bottleneck problem вчт. проблема узких мест bottleneck problem проблема узких мест bounded-variable problem вчт. задача с ограниченными переменными bulk queueing problem задача о групповом обслуживании business problem коммерческая задача classical optimization problem классическая задача оптимизации congestion problem вчт. задача массового обслуживания convex programming problem задача выпуклого программирования cut problem задача о раскрое data-set problem задача обработки совокупности данных decision problem задача принятия решений define a problem сформулировать задачу define a problem формулировать задачу delivery problem задача о доставке drug problem проблема наркомании dual problem двойственная задача equilibrium problem задача о равновесии error minimization problem задача минимизации ошибок estimation problem задача оценивания extremal problem экстремальная задача finite horizon problem задача о конечном интервале forecasting problem задача прогнозирования game-theoretic problem задача теории игр general decision problem общая задача принятия решений general transportation problem общая транспортная задача harmonization problem эк. проблема согласования ill-defined problem плохо структурированная задача ill-posed problem некорректная задача inference problem проблема логического вывода infinite horizon problem задача о бесконечном интервале information retrieval problem информационно-поисковая задача intractable problem трудноразрешимая задача legal problem правовая проблема legal problem правовой вопрос linear programming problem задача линейного программирования longest-path problem задача о максимальном пути management problem управленческая задача market analysis problem вчт. задача анализа рынка maximization problem задача максимизации mental problem умственные трудности minimal path problem задача о минимальном пути minimization problem задача минимизации minimum problem задача на минимум multi-objective problem многоцелевая задача multifacility problem вчт. задача для многоканальной системы nonlinear programming problem задача нелинейного программирования optimal kit problem задача об оптимальном комплекте optimal path problem задача о выборе оптимального пути optimization problem задача оптимизации optimum problem задача оптимизации ordering problem задача упорядочения primal problem прямая задача probabilistic problem вероятностная задача problem вопрос problem мат., шахм. задача problem задача problem проблема; вопрос; задача problem проблема problem проблемный problem сложная ситуация problem трудный случай problem attr. проблемный; problem novel проблемный роман problem child трудный ребенок problem of waiting вчт. задача об обслуживании с ожиданием programming problem вчт. задача программирования programming problem вчт. проблема программирования psychiatric problem психиатрическая проблема queuing problem задача массового обслуживания real-time problem вчт. задача решаемая в реальном времени real-world problem практическая задача real-world problem реальная задача saddle-point problem задача нахождения седловой точки scaling problem проблема размерности scheduling problem задача планирования sequential decision problem задача последовательного принятия решений servicing problem задача массового обслуживания set the problem поставить задачу set the problem ставить задачу shortest path problem задача о кратчайшем пути shortest route problem задача о кратчайшем пути smoothing problem задача о сглаживании social problem социальная проблема software problem проблема программного обеспечения sojourn time problem задача о времени пребывания solder-ball problem проблема шарика припоя solvable problem разрешимая задача solve a problem решать проблему stale data problem проблема устаревших данных statistical problem статистическая задача symmetric problem симметричная задача symmetrical problem симметричная задача system analysis problem задача системного анализа test problem тестовая задача toy problem искусственная задача trade-off problem проблема компромиссных решений transportation problem транспортная задача transshipment problem транспортная задача промежуточных пунктов traveling salesman problem задача коммивояжера trim problem задача о раскрое trouble-shooting problem вчт. диагностическая задача unsymmetrical problem несимметричная задача urgent problem неотложная проблема waiting-line problem вчт. задача массового обслуживания waiting-line problem задача массового обслуживания waiting-time problem вчт. задача о времени ожидания warehouse problem задача о рациональном использовании склада warehouse storage problem задача о рациональном использовании склада weak bridge problem проблема слабой связки well-structured problem хорошо сформулированная задача -
13 problem
ˈprɔbləm
1. сущ.
1) проблема;
вопрос;
задача to bring up, cause, create, pose, present, raise a problem ≈ поставить задачу/проблему (перед кем-л.) to resolve, settle, solve a problem ≈ решить вопрос/проблему The main problem is unemployment. ≈ Основная проблема - это безработица. I do not have a simple solution to the drug problem. ≈ У меня нет простого решения проблемы наркотиков. Syn: puzzle
2) а) сложная ситуация;
трудный случай б) трудность, затруднение, осложнение a weight problem ≈ проблема с весом He has a drink problem. ≈ У него склонность к спиртному./У него проблема с пьянством.
3) мат.;
шахм. задача to address, tackle a problem ≈ взяться за решение задачи complicated problem ≈ запутанная задача difficult problem ≈ трудная задача easy, simple problem ≈ простая/несложная задача
2. прил.
1) проблемный( о проблемах поведения и взаимоотношения людей) problem novel ≈ проблемный роман
2) трудный, вызывающий трудности, проблемы и т. п. problem child ≈ трудный ребенок problem person ≈ человек с трудным характером проблема, вопрос;
задача - *s of common interest вопросы, представляющий общий интерес - * of unemployment проблема безработицы - to solve a * разрешить проблему проблема, сложное дело;
трудный случай - housing * жилищная проблема - start-up * проблема, возникающая на начальном этапе (чего-л.) - it is a * how to make both ends meet не так-то просто свести концы с концами (специальное) задача - trouble-shooting * диагностическая задача - * book задачник трудный, вызывающий трудности, проблемы и т. п. - * child трудный ребенок - * bank (финансовое) банк, испытывающий финансовые затруднения преим. (театроведение) проблемный - * play проблемная пьеса( компьютерное) прикладной - * programmer прикладной программист accounting ~ бухгалтерская задача activity-analysis ~ задача анализа операций algorithmic ~ алгоритмическая проблема all integer ~ вчт. полностью целочисленная задача allocation ~ задача распределения approximating ~ приближенная задача assignment ~ задача о назначениях assignment ~ задача о распределении auxiliary ~ вспомогательная задача bargaining ~ задача о торгах benchmark ~ вчт. эталонная тестовая задача bottleneck ~ вчт. проблема узких мест bottleneck ~ проблема узких мест bounded-variable ~ вчт. задача с ограниченными переменными bulk queueing ~ задача о групповом обслуживании business ~ коммерческая задача classical optimization ~ классическая задача оптимизации congestion ~ вчт. задача массового обслуживания convex programming ~ задача выпуклого программирования cut ~ задача о раскрое data-set ~ задача обработки совокупности данных decision ~ задача принятия решений define a ~ сформулировать задачу define a ~ формулировать задачу delivery ~ задача о доставке drug ~ проблема наркомании dual ~ двойственная задача equilibrium ~ задача о равновесии error minimization ~ задача минимизации ошибок estimation ~ задача оценивания extremal ~ экстремальная задача finite horizon ~ задача о конечном интервале forecasting ~ задача прогнозирования game-theoretic ~ задача теории игр general decision ~ общая задача принятия решений general transportation ~ общая транспортная задача harmonization ~ эк. проблема согласования ill-defined ~ плохо структурированная задача ill-posed ~ некорректная задача inference ~ проблема логического вывода infinite horizon ~ задача о бесконечном интервале information retrieval ~ информационно-поисковая задача intractable ~ трудноразрешимая задача legal ~ правовая проблема legal ~ правовой вопрос linear programming ~ задача линейного программирования longest-path ~ задача о максимальном пути management ~ управленческая задача market analysis ~ вчт. задача анализа рынка maximization ~ задача максимизации mental ~ умственные трудности minimal path ~ задача о минимальном пути minimization ~ задача минимизации minimum ~ задача на минимум multi-objective ~ многоцелевая задача multifacility ~ вчт. задача для многоканальной системы nonlinear programming ~ задача нелинейного программирования optimal kit ~ задача об оптимальном комплекте optimal path ~ задача о выборе оптимального пути optimization ~ задача оптимизации optimum ~ задача оптимизации ordering ~ задача упорядочения primal ~ прямая задача probabilistic ~ вероятностная задача problem вопрос ~ мат., шахм. задача ~ задача ~ проблема;
вопрос;
задача ~ проблема ~ проблемный ~ сложная ситуация ~ трудный случай ~ attr. проблемный;
problem novel проблемный роман ~ child трудный ребенок ~ of waiting вчт. задача об обслуживании с ожиданием programming ~ вчт. задача программирования programming ~ вчт. проблема программирования psychiatric ~ психиатрическая проблема queuing ~ задача массового обслуживания real-time ~ вчт. задача решаемая в реальном времени real-world ~ практическая задача real-world ~ реальная задача saddle-point ~ задача нахождения седловой точки scaling ~ проблема размерности scheduling ~ задача планирования sequential decision ~ задача последовательного принятия решений servicing ~ задача массового обслуживания set the ~ поставить задачу set the ~ ставить задачу shortest path ~ задача о кратчайшем пути shortest route ~ задача о кратчайшем пути smoothing ~ задача о сглаживании social ~ социальная проблема software ~ проблема программного обеспечения sojourn time ~ задача о времени пребывания solder-ball ~ проблема шарика припоя solvable ~ разрешимая задача solve a ~ решать проблему stale data ~ проблема устаревших данных statistical ~ статистическая задача symmetric ~ симметричная задача symmetrical ~ симметричная задача system analysis ~ задача системного анализа test ~ тестовая задача toy ~ искусственная задача trade-off ~ проблема компромиссных решений transportation ~ транспортная задача transshipment ~ транспортная задача промежуточных пунктов traveling salesman ~ задача коммивояжера trim ~ задача о раскрое trouble-shooting ~ вчт. диагностическая задача unsymmetrical ~ несимметричная задача urgent ~ неотложная проблема waiting-line ~ вчт. задача массового обслуживания waiting-line ~ задача массового обслуживания waiting-time ~ вчт. задача о времени ожидания warehouse ~ задача о рациональном использовании склада warehouse storage ~ задача о рациональном использовании склада weak bridge ~ проблема слабой связки well-structured ~ хорошо сформулированная задача -
14 хорошо структурированная задача
Большой англо-русский и русско-английский словарь > хорошо структурированная задача
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15 хорошо структурированная проблема
Большой англо-русский и русско-английский словарь > хорошо структурированная проблема
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16 sharp
sharp [∫α:p]1. adjectivea. ( = good for cutting) [knife, razor, blade] (bien) aiguisé ; [piece of glass, edge] coupantb. ( = pointed) [pencil] bien taillé ; [needle, pin] très pointu ; [teeth, fingernails, beak, chin] pointu ; [fang, point] acéré ; [features] anguleuxc. ( = well-defined) [contrast, TV picture, difference] net ; [division] fort• to bring into sharp focus [+ problem, issue] faire ressortir nettementd. ( = acute) [person] malin (- igne f) ; [intelligence, wit] vif ; [awareness] aigu (- guë f) ; [eyesight] perçant ; [hearing] fin• to keep a sharp look-out for sb/sth guetter qn/qchf. ( = intense) [pain, sensation, wind, cold] vif ; [frost] fort ; [blow] sec ( sèche f) ; [cry] aigu (- guë f)g. ( = severe) [criticism, attack] incisif ; [retort, words] cinglant ; [rebuke] vif ; [order, tone, voice] cassanth. (pejorative) [business practices] déloyall. [musical note] trop haut2. adverba. [stop] brusquement• to turn sharp left/right prendre un virage serré à gauche/à droiteb. [sing, play] trop hautc. ( = precisely) at 8 o'clock sharp à 8 heures pile3. noun4. compounds* * *[ʃɑːp] 1.noun Music dièse m2.1) [razor] tranchant; [edge] coupant; [blade, scissors, knife] bien aiguisé; [saw] bien affûté2) ( pointed) [tooth, fingernail, end, needle] pointu; [pencil] bien taillé; [features] anguleux/-euse; [nose] pointu3) ( abrupt) [angle] aigu/-uë; [bend, reflex] brusque; [drop, incline] fort; [fall, rise] brusque, brutal4) ( acidic) [taste, smell] âcre; [fruit] acide5) ( piercing) [pain, cold] vif/vive; [cry] aigu/-uë; [blow] sévère; [frost] fort, intense6) fig ( aggressive) [tongue] acéré; [tone] acerbe7) ( alert) [person, mind] vif/vive; [eyesight] perçant; [hearing] finto have a sharp eye for something — fig avoir l'œil pour quelque chose
sharp operator — filou m
9) ( clearly defined) [image, sound, distinction] net/nette; [contrast] prononcéto bring something into sharp focus — lit cadrer quelque chose avec netteté; fig faire passer quelque chose au premier plan
10) (colloq) GB [suit] tape-à-l'œil inv pej11) (colloq) US ( stylish) chic inv3.1) ( abruptly) [stop] net2) (colloq) ( promptly)at 9 o'clock sharp — à neuf heures pile (colloq)
3) Music [sing, play] trop haut••to look sharp — (colloq) se dépêcher
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17 modular data center
модульный центр обработки данных (ЦОД)
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[Интент]Параллельные тексты EN-RU
[ http://dcnt.ru/?p=9299#more-9299]
Data Centers are a hot topic these days. No matter where you look, this once obscure aspect of infrastructure is getting a lot of attention. For years, there have been cost pressures on IT operations and this, when the need for modern capacity is greater than ever, has thrust data centers into the spotlight. Server and rack density continues to rise, placing DC professionals and businesses in tighter and tougher situations while they struggle to manage their IT environments. And now hyper-scale cloud infrastructure is taking traditional technologies to limits never explored before and focusing the imagination of the IT industry on new possibilities.
В настоящее время центры обработки данных являются широко обсуждаемой темой. Куда ни посмотришь, этот некогда малоизвестный аспект инфраструктуры привлекает все больше внимания. Годами ИТ-отделы испытывали нехватку средств и это выдвинуло ЦОДы в центр внимания, в то время, когда необходимость в современных ЦОДах стала как никогда высокой. Плотность серверов и стоек продолжают расти, все больше усложняя ситуацию для специалистов в области охлаждения и организаций в их попытках управлять своими ИТ-средами. И теперь гипермасштабируемая облачная инфраструктура подвергает традиционные технологии невиданным ранее нагрузкам, и заставляет ИТ-индустрию искать новые возможности.
At Microsoft, we have focused a lot of thought and research around how to best operate and maintain our global infrastructure and we want to share those learnings. While obviously there are some aspects that we keep to ourselves, we have shared how we operate facilities daily, our technologies and methodologies, and, most importantly, how we monitor and manage our facilities. Whether it’s speaking at industry events, inviting customers to our “Microsoft data center conferences” held in our data centers, or through other media like blogging and white papers, we believe sharing best practices is paramount and will drive the industry forward. So in that vein, we have some interesting news to share.
В компании MicroSoft уделяют большое внимание изучению наилучших методов эксплуатации и технического обслуживания своей глобальной инфраструктуры и делятся результатами своих исследований. И хотя мы, конечно, не раскрываем некоторые аспекты своих исследований, мы делимся повседневным опытом эксплуатации дата-центров, своими технологиями и методологиями и, что важнее всего, методами контроля и управления своими объектами. Будь то доклады на отраслевых событиях, приглашение клиентов на наши конференции, которые посвящены центрам обработки данных MicroSoft, и проводятся в этих самых дата-центрах, или использование других средств, например, блоги и спецификации, мы уверены, что обмен передовым опытом имеет первостепенное значение и будет продвигать отрасль вперед.
Today we are sharing our Generation 4 Modular Data Center plan. This is our vision and will be the foundation of our cloud data center infrastructure in the next five years. We believe it is one of the most revolutionary changes to happen to data centers in the last 30 years. Joining me, in writing this blog are Daniel Costello, my director of Data Center Research and Engineering and Christian Belady, principal power and cooling architect. I feel their voices will add significant value to driving understanding around the many benefits included in this new design paradigm.
Сейчас мы хотим поделиться своим планом модульного дата-центра четвертого поколения. Это наше видение и оно будет основанием для инфраструктуры наших облачных дата-центров в ближайшие пять лет. Мы считаем, что это одно из самых революционных изменений в дата-центрах за последние 30 лет. Вместе со мной в написании этого блога участвовали Дэниел Костелло, директор по исследованиям и инжинирингу дата-центров, и Кристиан Белади, главный архитектор систем энергоснабжения и охлаждения. Мне кажется, что их авторитет придаст больше веса большому количеству преимуществ, включенных в эту новую парадигму проектирования.
Our “Gen 4” modular data centers will take the flexibility of containerized servers—like those in our Chicago data center—and apply it across the entire facility. So what do we mean by modular? Think of it like “building blocks”, where the data center will be composed of modular units of prefabricated mechanical, electrical, security components, etc., in addition to containerized servers.
Was there a key driver for the Generation 4 Data Center?Наши модульные дата-центры “Gen 4” будут гибкими с контейнерами серверов – как серверы в нашем чикагском дата-центре. И гибкость будет применяться ко всему ЦОД. Итак, что мы подразумеваем под модульностью? Мы думаем о ней как о “строительных блоках”, где дата-центр будет состоять из модульных блоков изготовленных в заводских условиях электрических систем и систем охлаждения, а также систем безопасности и т.п., в дополнение к контейнеризованным серверам.
Был ли ключевой стимул для разработки дата-центра четвертого поколения?
If we were to summarize the promise of our Gen 4 design into a single sentence it would be something like this: “A highly modular, scalable, efficient, just-in-time data center capacity program that can be delivered anywhere in the world very quickly and cheaply, while allowing for continued growth as required.” Sounds too good to be true, doesn’t it? Well, keep in mind that these concepts have been in initial development and prototyping for over a year and are based on cumulative knowledge of previous facility generations and the advances we have made since we began our investments in earnest on this new design.Если бы нам нужно было обобщить достоинства нашего проекта Gen 4 в одном предложении, это выглядело бы следующим образом: “Центр обработки данных с высоким уровнем модульности, расширяемости, и энергетической эффективности, а также возможностью постоянного расширения, в случае необходимости, который можно очень быстро и дешево развертывать в любом месте мира”. Звучит слишком хорошо для того чтобы быть правдой, не так ли? Ну, не забывайте, что эти концепции находились в процессе начальной разработки и создания опытного образца в течение более одного года и основываются на опыте, накопленном в ходе развития предыдущих поколений ЦОД, а также успехах, сделанных нами со времени, когда мы начали вкладывать серьезные средства в этот новый проект.
One of the biggest challenges we’ve had at Microsoft is something Mike likes to call the ‘Goldilock’s Problem’. In a nutshell, the problem can be stated as:
The worst thing we can do in delivering facilities for the business is not have enough capacity online, thus limiting the growth of our products and services.Одну из самых больших проблем, с которыми приходилось сталкиваться Майкрософт, Майк любит называть ‘Проблемой Лютика’. Вкратце, эту проблему можно выразить следующим образом:
Самое худшее, что может быть при строительстве ЦОД для бизнеса, это не располагать достаточными производственными мощностями, и тем самым ограничивать рост наших продуктов и сервисов.The second worst thing we can do in delivering facilities for the business is to have too much capacity online.
А вторым самым худшим моментом в этой сфере может слишком большое количество производственных мощностей.
This has led to a focus on smart, intelligent growth for the business — refining our overall demand picture. It can’t be too hot. It can’t be too cold. It has to be ‘Just Right!’ The capital dollars of investment are too large to make without long term planning. As we struggled to master these interesting challenges, we had to ensure that our technological plan also included solutions for the business and operational challenges we faced as well.
So let’s take a high level look at our Generation 4 designЭто заставило нас сосредоточиваться на интеллектуальном росте для бизнеса — refining our overall demand picture. Это не должно быть слишком горячим. И это не должно быть слишком холодным. Это должно быть ‘как раз, таким как надо!’ Нельзя делать такие большие капиталовложения без долгосрочного планирования. Пока мы старались решить эти интересные проблемы, мы должны были гарантировать, что наш технологический план будет также включать решения для коммерческих и эксплуатационных проблем, с которыми нам также приходилось сталкиваться.
Давайте рассмотрим наш проект дата-центра четвертого поколенияAre you ready for some great visuals? Check out this video at Soapbox. Click here for the Microsoft 4th Gen Video.
It’s a concept video that came out of my Data Center Research and Engineering team, under Daniel Costello, that will give you a view into what we think is the future.
From a configuration, construct-ability and time to market perspective, our primary goals and objectives are to modularize the whole data center. Not just the server side (like the Chicago facility), but the mechanical and electrical space as well. This means using the same kind of parts in pre-manufactured modules, the ability to use containers, skids, or rack-based deployments and the ability to tailor the Redundancy and Reliability requirements to the application at a very specific level.
Посмотрите это видео, перейдите по ссылке для просмотра видео о Microsoft 4th Gen:
Это концептуальное видео, созданное командой отдела Data Center Research and Engineering, возглавляемого Дэниелом Костелло, которое даст вам наше представление о будущем.
С точки зрения конфигурации, строительной технологичности и времени вывода на рынок, нашими главными целями и задачами агрегатирование всего дата-центра. Не только серверную часть, как дата-центр в Чикаго, но также системы охлаждения и электрические системы. Это означает применение деталей одного типа в сборных модулях, возможность использования контейнеров, салазок, или стоечных систем, а также возможность подстраивать требования избыточности и надежности для данного приложения на очень специфичном уровне.Our goals from a cost perspective were simple in concept but tough to deliver. First and foremost, we had to reduce the capital cost per critical Mega Watt by the class of use. Some applications can run with N-level redundancy in the infrastructure, others require a little more infrastructure for support. These different classes of infrastructure requirements meant that optimizing for all cost classes was paramount. At Microsoft, we are not a one trick pony and have many Online products and services (240+) that require different levels of operational support. We understand that and ensured that we addressed it in our design which will allow us to reduce capital costs by 20%-40% or greater depending upon class.
Нашими целями в области затрат были концептуально простыми, но трудно реализуемыми. В первую очередь мы должны были снизить капитальные затраты в пересчете на один мегаватт, в зависимости от класса резервирования. Некоторые приложения могут вполне работать на базе инфраструктуры с резервированием на уровне N, то есть без резервирования, а для работы других приложений требуется больше инфраструктуры. Эти разные классы требований инфраструктуры подразумевали, что оптимизация всех классов затрат имеет преобладающее значение. В Майкрософт мы не ограничиваемся одним решением и располагаем большим количеством интерактивных продуктов и сервисов (240+), которым требуются разные уровни эксплуатационной поддержки. Мы понимаем это, и учитываем это в своем проекте, который позволит нам сокращать капитальные затраты на 20%-40% или более в зависимости от класса.For example, non-critical or geo redundant applications have low hardware reliability requirements on a location basis. As a result, Gen 4 can be configured to provide stripped down, low-cost infrastructure with little or no redundancy and/or temperature control. Let’s say an Online service team decides that due to the dramatically lower cost, they will simply use uncontrolled outside air with temperatures ranging 10-35 C and 20-80% RH. The reality is we are already spec-ing this for all of our servers today and working with server vendors to broaden that range even further as Gen 4 becomes a reality. For this class of infrastructure, we eliminate generators, chillers, UPSs, and possibly lower costs relative to traditional infrastructure.
Например, некритичные или гео-избыточные системы имеют низкие требования к аппаратной надежности на основе местоположения. В результате этого, Gen 4 можно конфигурировать для упрощенной, недорогой инфраструктуры с низким уровнем (или вообще без резервирования) резервирования и / или температурного контроля. Скажем, команда интерактивного сервиса решает, что, в связи с намного меньшими затратами, они будут просто использовать некондиционированный наружный воздух с температурой 10-35°C и влажностью 20-80% RH. В реальности мы уже сегодня предъявляем эти требования к своим серверам и работаем с поставщиками серверов над еще большим расширением диапазона температур, так как наш модуль и подход Gen 4 становится реальностью. Для подобного класса инфраструктуры мы удаляем генераторы, чиллеры, ИБП, и, возможно, будем предлагать более низкие затраты, по сравнению с традиционной инфраструктурой.
Applications that demand higher level of redundancy or temperature control will use configurations of Gen 4 to meet those needs, however, they will also cost more (but still less than traditional data centers). We see this cost difference driving engineering behavioral change in that we predict more applications will drive towards Geo redundancy to lower costs.
Системы, которым требуется более высокий уровень резервирования или температурного контроля, будут использовать конфигурации Gen 4, отвечающие этим требованиям, однако, они будут также стоить больше. Но все равно они будут стоить меньше, чем традиционные дата-центры. Мы предвидим, что эти различия в затратах будут вызывать изменения в методах инжиниринга, и по нашим прогнозам, это будет выражаться в переходе все большего числа систем на гео-избыточность и меньшие затраты.
Another cool thing about Gen 4 is that it allows us to deploy capacity when our demand dictates it. Once finalized, we will no longer need to make large upfront investments. Imagine driving capital costs more closely in-line with actual demand, thus greatly reducing time-to-market and adding the capacity Online inherent in the design. Also reduced is the amount of construction labor required to put these “building blocks” together. Since the entire platform requires pre-manufacture of its core components, on-site construction costs are lowered. This allows us to maximize our return on invested capital.
Еще одно достоинство Gen 4 состоит в том, что он позволяет нам разворачивать дополнительные мощности, когда нам это необходимо. Как только мы закончим проект, нам больше не нужно будет делать большие начальные капиталовложения. Представьте себе возможность более точного согласования капитальных затрат с реальными требованиями, и тем самым значительного снижения времени вывода на рынок и интерактивного добавления мощностей, предусматриваемого проектом. Также снижен объем строительных работ, требуемых для сборки этих “строительных блоков”. Поскольку вся платформа требует предварительного изготовления ее базовых компонентов, затраты на сборку также снижены. Это позволит нам увеличить до максимума окупаемость своих капиталовложений.
Мы все подвергаем сомнениюIn our design process, we questioned everything. You may notice there is no roof and some might be uncomfortable with this. We explored the need of one and throughout our research we got some surprising (positive) results that showed one wasn’t needed.
В своем процессе проектирования мы все подвергаем сомнению. Вы, наверное, обратили внимание на отсутствие крыши, и некоторым специалистам это могло не понравиться. Мы изучили необходимость в крыше и в ходе своих исследований получили удивительные результаты, которые показали, что крыша не нужна.
Серийное производство дата центров
In short, we are striving to bring Henry Ford’s Model T factory to the data center. http://en.wikipedia.org/wiki/Henry_Ford#Model_T. Gen 4 will move data centers from a custom design and build model to a commoditized manufacturing approach. We intend to have our components built in factories and then assemble them in one location (the data center site) very quickly. Think about how a computer, car or plane is built today. Components are manufactured by different companies all over the world to a predefined spec and then integrated in one location based on demands and feature requirements. And just like Henry Ford’s assembly line drove the cost of building and the time-to-market down dramatically for the automobile industry, we expect Gen 4 to do the same for data centers. Everything will be pre-manufactured and assembled on the pad.Мы хотим применить модель автомобильной фабрики Генри Форда к дата-центру. Проект Gen 4 будет способствовать переходу от модели специализированного проектирования и строительства к товарно-производственному, серийному подходу. Мы намерены изготавливать свои компоненты на заводах, а затем очень быстро собирать их в одном месте, в месте строительства дата-центра. Подумайте о том, как сегодня изготавливается компьютер, автомобиль или самолет. Компоненты изготавливаются по заранее определенным спецификациям разными компаниями во всем мире, затем собираются в одном месте на основе спроса и требуемых характеристик. И точно так же как сборочный конвейер Генри Форда привел к значительному уменьшению затрат на производство и времени вывода на рынок в автомобильной промышленности, мы надеемся, что Gen 4 сделает то же самое для дата-центров. Все будет предварительно изготавливаться и собираться на месте.
Невероятно энергоэффективный ЦОД
And did we mention that this platform will be, overall, incredibly energy efficient? From a total energy perspective not only will we have remarkable PUE values, but the total cost of energy going into the facility will be greatly reduced as well. How much energy goes into making concrete? Will we need as much of it? How much energy goes into the fuel of the construction vehicles? This will also be greatly reduced! A key driver is our goal to achieve an average PUE at or below 1.125 by 2012 across our data centers. More than that, we are on a mission to reduce the overall amount of copper and water used in these facilities. We believe these will be the next areas of industry attention when and if the energy problem is solved. So we are asking today…“how can we build a data center with less building”?А мы упоминали, что эта платформа будет, в общем, невероятно энергоэффективной? С точки зрения общей энергии, мы получим не только поразительные значения PUE, но общая стоимость энергии, затраченной на объект будет также значительно снижена. Сколько энергии идет на производство бетона? Нам нужно будет столько энергии? Сколько энергии идет на питание инженерных строительных машин? Это тоже будет значительно снижено! Главным стимулом является достижение среднего PUE не больше 1.125 для всех наших дата-центров к 2012 году. Более того, у нас есть задача сокращения общего количества меди и воды в дата-центрах. Мы думаем, что эти задачи станут следующей заботой отрасли после того как будет решена энергетическая проблема. Итак, сегодня мы спрашиваем себя…“как можно построить дата-центр с меньшим объемом строительных работ”?
Строительство дата центров без чиллеровWe have talked openly and publicly about building chiller-less data centers and running our facilities using aggressive outside economization. Our sincerest hope is that Gen 4 will completely eliminate the use of water. Today’s data centers use massive amounts of water and we see water as the next scarce resource and have decided to take a proactive stance on making water conservation part of our plan.
Мы открыто и публично говорили о строительстве дата-центров без чиллеров и активном использовании в наших центрах обработки данных технологий свободного охлаждения или фрикулинга. Мы искренне надеемся, что Gen 4 позволит полностью отказаться от использования воды. Современные дата-центры расходуют большие объемы воды и так как мы считаем воду следующим редким ресурсом, мы решили принять упреждающие меры и включить экономию воды в свой план.
By sharing this with the industry, we believe everyone can benefit from our methodology. While this concept and approach may be intimidating (or downright frightening) to some in the industry, disclosure ultimately is better for all of us.
Делясь этим опытом с отраслью, мы считаем, что каждый сможет извлечь выгоду из нашей методологией. Хотя эта концепция и подход могут показаться пугающими (или откровенно страшными) для некоторых отраслевых специалистов, раскрывая свои планы мы, в конечном счете, делаем лучше для всех нас.
Gen 4 design (even more than just containers), could reduce the ‘religious’ debates in our industry. With the central spine infrastructure in place, containers or pre-manufactured server halls can be either AC or DC, air-side economized or water-side economized, or not economized at all (though the sanity of that might be questioned). Gen 4 will allow us to decommission, repair and upgrade quickly because everything is modular. No longer will we be governed by the initial decisions made when constructing the facility. We will have almost unlimited use and re-use of the facility and site. We will also be able to use power in an ultra-fluid fashion moving load from critical to non-critical as use and capacity requirements dictate.
Проект Gen 4 позволит уменьшить ‘религиозные’ споры в нашей отрасли. Располагая базовой инфраструктурой, контейнеры или сборные серверные могут оборудоваться системами переменного или постоянного тока, воздушными или водяными экономайзерами, или вообще не использовать экономайзеры. Хотя можно подвергать сомнению разумность такого решения. Gen 4 позволит нам быстро выполнять работы по выводу из эксплуатации, ремонту и модернизации, поскольку все будет модульным. Мы больше не будем руководствоваться начальными решениями, принятыми во время строительства дата-центра. Мы сможем использовать этот дата-центр и инфраструктуру в течение почти неограниченного периода времени. Мы также сможем применять сверхгибкие методы использования электрической энергии, переводя оборудование в режимы критической или некритической нагрузки в соответствии с требуемой мощностью.
Gen 4 – это стандартная платформаFinally, we believe this is a big game changer. Gen 4 will provide a standard platform that our industry can innovate around. For example, all modules in our Gen 4 will have common interfaces clearly defined by our specs and any vendor that meets these specifications will be able to plug into our infrastructure. Whether you are a computer vendor, UPS vendor, generator vendor, etc., you will be able to plug and play into our infrastructure. This means we can also source anyone, anywhere on the globe to minimize costs and maximize performance. We want to help motivate the industry to further innovate—with innovations from which everyone can reap the benefits.
Наконец, мы уверены, что это будет фактором, который значительно изменит ситуацию. Gen 4 будет представлять собой стандартную платформу, которую отрасль сможет обновлять. Например, все модули в нашем Gen 4 будут иметь общепринятые интерфейсы, четко определяемые нашими спецификациями, и оборудование любого поставщика, которое отвечает этим спецификациям можно будет включать в нашу инфраструктуру. Независимо от того производите вы компьютеры, ИБП, генераторы и т.п., вы сможете включать свое оборудование нашу инфраструктуру. Это означает, что мы также сможем обеспечивать всех, в любом месте земного шара, тем самым сводя до минимума затраты и максимальной увеличивая производительность. Мы хотим создать в отрасли мотивацию для дальнейших инноваций – инноваций, от которых каждый сможет получать выгоду.
Главные характеристики дата-центров четвертого поколения Gen4To summarize, the key characteristics of our Generation 4 data centers are:
Scalable
Plug-and-play spine infrastructure
Factory pre-assembled: Pre-Assembled Containers (PACs) & Pre-Manufactured Buildings (PMBs)
Rapid deployment
De-mountable
Reduce TTM
Reduced construction
Sustainable measuresНиже приведены главные характеристики дата-центров четвертого поколения Gen 4:
Расширяемость;
Готовая к использованию базовая инфраструктура;
Изготовление в заводских условиях: сборные контейнеры (PAC) и сборные здания (PMB);
Быстрота развертывания;
Возможность демонтажа;
Снижение времени вывода на рынок (TTM);
Сокращение сроков строительства;
Экологичность;Map applications to DC Class
We hope you join us on this incredible journey of change and innovation!
Long hours of research and engineering time are invested into this process. There are still some long days and nights ahead, but the vision is clear. Rest assured however, that we as refine Generation 4, the team will soon be looking to Generation 5 (even if it is a bit farther out). There is always room to get better.
Использование систем электропитания постоянного тока.
Мы надеемся, что вы присоединитесь к нам в этом невероятном путешествии по миру изменений и инноваций!
На этот проект уже потрачены долгие часы исследований и проектирования. И еще предстоит потратить много дней и ночей, но мы имеем четкое представление о конечной цели. Однако будьте уверены, что как только мы доведем до конца проект модульного дата-центра четвертого поколения, мы вскоре начнем думать о проекте дата-центра пятого поколения. Всегда есть возможность для улучшений.So if you happen to come across Goldilocks in the forest, and you are curious as to why she is smiling you will know that she feels very good about getting very close to ‘JUST RIGHT’.
Generations of Evolution – some background on our data center designsТак что, если вы встретите в лесу девочку по имени Лютик, и вам станет любопытно, почему она улыбается, вы будете знать, что она очень довольна тем, что очень близко подошла к ‘ОПИМАЛЬНОМУ РЕШЕНИЮ’.
Поколения эволюции – история развития наших дата-центровWe thought you might be interested in understanding what happened in the first three generations of our data center designs. When Ray Ozzie wrote his Software plus Services memo it posed a very interesting challenge to us. The winds of change were at ‘tornado’ proportions. That “plus Services” tag had some significant (and unstated) challenges inherent to it. The first was that Microsoft was going to evolve even further into an operations company. While we had been running large scale Internet services since 1995, this development lead us to an entirely new level. Additionally, these “services” would span across both Internet and Enterprise businesses. To those of you who have to operate “stuff”, you know that these are two very different worlds in operational models and challenges. It also meant that, to achieve the same level of reliability and performance required our infrastructure was going to have to scale globally and in a significant way.
Мы подумали, что может быть вам будет интересно узнать историю первых трех поколений наших центров обработки данных. Когда Рэй Оззи написал свою памятную записку Software plus Services, он поставил перед нами очень интересную задачу. Ветра перемен двигались с ураганной скоростью. Это окончание “plus Services” скрывало в себе какие-то значительные и неопределенные задачи. Первая заключалась в том, что Майкрософт собиралась в еще большей степени стать операционной компанией. Несмотря на то, что мы управляли большими интернет-сервисами, начиная с 1995 г., эта разработка подняла нас на абсолютно новый уровень. Кроме того, эти “сервисы” охватывали интернет-компании и корпорации. Тем, кому приходится всем этим управлять, известно, что есть два очень разных мира в области операционных моделей и задач. Это также означало, что для достижения такого же уровня надежности и производительности требовалось, чтобы наша инфраструктура располагала значительными возможностями расширения в глобальных масштабах.
It was that intense atmosphere of change that we first started re-evaluating data center technology and processes in general and our ideas began to reach farther than what was accepted by the industry at large. This was the era of Generation 1. As we look at where most of the world’s data centers are today (and where our facilities were), it represented all the known learning and design requirements that had been in place since IBM built the first purpose-built computer room. These facilities focused more around uptime, reliability and redundancy. Big infrastructure was held accountable to solve all potential environmental shortfalls. This is where the majority of infrastructure in the industry still is today.
Именно в этой атмосфере серьезных изменений мы впервые начали переоценку ЦОД-технологий и технологий вообще, и наши идеи начали выходить за пределы общепринятых в отрасли представлений. Это была эпоха ЦОД первого поколения. Когда мы узнали, где сегодня располагается большинство мировых дата-центров и где находятся наши предприятия, это представляло весь опыт и навыки проектирования, накопленные со времени, когда IBM построила первую серверную. В этих ЦОД больше внимания уделялось бесперебойной работе, надежности и резервированию. Большая инфраструктура была призвана решать все потенциальные экологические проблемы. Сегодня большая часть инфраструктуры все еще находится на этом этапе своего развития.
We soon realized that traditional data centers were quickly becoming outdated. They were not keeping up with the demands of what was happening technologically and environmentally. That’s when we kicked off our Generation 2 design. Gen 2 facilities started taking into account sustainability, energy efficiency, and really looking at the total cost of energy and operations.
Очень быстро мы поняли, что стандартные дата-центры очень быстро становятся устаревшими. Они не поспевали за темпами изменений технологических и экологических требований. Именно тогда мы стали разрабатывать ЦОД второго поколения. В этих дата-центрах Gen 2 стали принимать во внимание такие факторы как устойчивое развитие, энергетическая эффективность, а также общие энергетические и эксплуатационные.
No longer did we view data centers just for the upfront capital costs, but we took a hard look at the facility over the course of its life. Our Quincy, Washington and San Antonio, Texas facilities are examples of our Gen 2 data centers where we explored and implemented new ways to lessen the impact on the environment. These facilities are considered two leading industry examples, based on their energy efficiency and ability to run and operate at new levels of scale and performance by leveraging clean hydro power (Quincy) and recycled waste water (San Antonio) to cool the facility during peak cooling months.
Мы больше не рассматривали дата-центры только с точки зрения начальных капитальных затрат, а внимательно следили за работой ЦОД на протяжении его срока службы. Наши объекты в Куинси, Вашингтоне, и Сан-Антонио, Техас, являются образцами наших ЦОД второго поколения, в которых мы изучали и применяли на практике новые способы снижения воздействия на окружающую среду. Эти объекты считаются двумя ведущими отраслевыми примерами, исходя из их энергетической эффективности и способности работать на новых уровнях производительности, основанных на использовании чистой энергии воды (Куинси) и рециклирования отработанной воды (Сан-Антонио) для охлаждения объекта в самых жарких месяцах.
As we were delivering our Gen 2 facilities into steel and concrete, our Generation 3 facilities were rapidly driving the evolution of the program. The key concepts for our Gen 3 design are increased modularity and greater concentration around energy efficiency and scale. The Gen 3 facility will be best represented by the Chicago, Illinois facility currently under construction. This facility will seem very foreign compared to the traditional data center concepts most of the industry is comfortable with. In fact, if you ever sit around in our container hanger in Chicago it will look incredibly different from a traditional raised-floor data center. We anticipate this modularization will drive huge efficiencies in terms of cost and operations for our business. We will also introduce significant changes in the environmental systems used to run our facilities. These concepts and processes (where applicable) will help us gain even greater efficiencies in our existing footprint, allowing us to further maximize infrastructure investments.
Так как наши ЦОД второго поколения строились из стали и бетона, наши центры обработки данных третьего поколения начали их быстро вытеснять. Главными концептуальными особенностями ЦОД третьего поколения Gen 3 являются повышенная модульность и большее внимание к энергетической эффективности и масштабированию. Дата-центры третьего поколения лучше всего представлены объектом, который в настоящее время строится в Чикаго, Иллинойс. Этот ЦОД будет выглядеть очень необычно, по сравнению с общепринятыми в отрасли представлениями о дата-центре. Действительно, если вам когда-либо удастся побывать в нашем контейнерном ангаре в Чикаго, он покажется вам совершенно непохожим на обычный дата-центр с фальшполом. Мы предполагаем, что этот модульный подход будет способствовать значительному повышению эффективности нашего бизнеса в отношении затрат и операций. Мы также внесем существенные изменения в климатические системы, используемые в наших ЦОД. Эти концепции и технологии, если применимо, позволят нам добиться еще большей эффективности наших существующих дата-центров, и тем самым еще больше увеличивать капиталовложения в инфраструктуру.
This is definitely a journey, not a destination industry. In fact, our Generation 4 design has been under heavy engineering for viability and cost for over a year. While the demand of our commercial growth required us to make investments as we grew, we treated each step in the learning as a process for further innovation in data centers. The design for our future Gen 4 facilities enabled us to make visionary advances that addressed the challenges of building, running, and operating facilities all in one concerted effort.
Это определенно путешествие, а не конечный пункт назначения. На самом деле, наш проект ЦОД четвертого поколения подвергался серьезным испытаниям на жизнеспособность и затраты на протяжении целого года. Хотя необходимость в коммерческом росте требовала от нас постоянных капиталовложений, мы рассматривали каждый этап своего развития как шаг к будущим инновациям в области дата-центров. Проект наших будущих ЦОД четвертого поколения Gen 4 позволил нам делать фантастические предположения, которые касались задач строительства, управления и эксплуатации объектов как единого упорядоченного процесса.
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Англо-русский словарь нормативно-технической терминологии > modular data center
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18 Creativity
Put in this bald way, these aims sound utopian. How utopian they areor rather, how imminent their realization-depends on how broadly or narrowly we interpret the term "creative." If we are willing to regard all human complex problem solving as creative, then-as we will point out-successful programs for problem solving mechanisms that simulate human problem solvers already exist, and a number of their general characteristics are known. If we reserve the term "creative" for activities like discovery of the special theory of relativity or the composition of Beethoven's Seventh Symphony, then no example of a creative mechanism exists at the present time. (Simon, 1979, pp. 144-145)Among the questions that can now be given preliminary answers in computational terms are the following: how can ideas from very different sources be spontaneously thought of together? how can two ideas be merged to produce a new structure, which shows the influence of both ancestor ideas without being a mere "cut-and-paste" combination? how can the mind be "primed," so that one will more easily notice serendipitous ideas? why may someone notice-and remember-something fairly uninteresting, if it occurs in an interesting context? how can a brief phrase conjure up an entire melody from memory? and how can we accept two ideas as similar ("love" and "prove" as rhyming, for instance) in respect of a feature not identical in both? The features of connectionist AI models that suggest answers to these questions are their powers of pattern completion, graceful degradation, sensitization, multiple constraint satisfaction, and "best-fit" equilibration.... Here, the important point is that the unconscious, "insightful," associative aspects of creativity can be explained-in outline, at least-by AI methods. (Boden, 1996, p. 273)There thus appears to be an underlying similarity in the process involved in creative innovation and social independence, with common traits and postures required for expression of both behaviors. The difference is one of product-literary, musical, artistic, theoretical products on the one hand, opinions on the other-rather than one of process. In both instances the individual must believe that his perceptions are meaningful and valid and be willing to rely upon his own interpretations. He must trust himself sufficiently that even when persons express opinions counter to his own he can proceed on the basis of his own perceptions and convictions. (Coopersmith, 1967, p. 58)he average level of ego strength and emotional stability is noticeably higher among creative geniuses than among the general population, though it is possibly lower than among men of comparable intelligence and education who go into administrative and similar positions. High anxiety and excitability appear common (e.g. Priestley, Darwin, Kepler) but full-blown neurosis is quite rare. (Cattell & Butcher, 1970, p. 315)he insight that is supposed to be required for such work as discovery turns out to be synonymous with the familiar process of recognition; and other terms commonly used in the discussion of creative work-such terms as "judgment," "creativity," or even "genius"-appear to be wholly dispensable or to be definable, as insight is, in terms of mundane and well-understood concepts. (Simon, 1989, p. 376)From the sketch material still in existence, from the condition of the fragments, and from the autographs themselves we can draw definite conclusions about Mozart's creative process. To invent musical ideas he did not need any stimulation; they came to his mind "ready-made" and in polished form. In contrast to Beethoven, who made numerous attempts at shaping his musical ideas until he found the definitive formulation of a theme, Mozart's first inspiration has the stamp of finality. Any Mozart theme has completeness and unity; as a phenomenon it is a Gestalt. (Herzmann, 1964, p. 28)Great artists enlarge the limits of one's perception. Looking at the world through the eyes of Rembrandt or Tolstoy makes one able to perceive aspects of truth about the world which one could not have achieved without their aid. Freud believed that science was adaptive because it facilitated mastery of the external world; but was it not the case that many scientific theories, like works of art, also originated in phantasy? Certainly, reading accounts of scientific discovery by men of the calibre of Einstein compelled me to conclude that phantasy was not merely escapist, but a way of reaching new insights concerning the nature of reality. Scientific hypotheses require proof; works of art do not. Both are concerned with creating order, with making sense out of the world and our experience of it. (Storr, 1993, p. xii)The importance of self-esteem for creative expression appears to be almost beyond disproof. Without a high regard for himself the individual who is working in the frontiers of his field cannot trust himself to discriminate between the trivial and the significant. Without trust in his own powers the person seeking improved solutions or alternative theories has no basis for distinguishing the significant and profound innovation from the one that is merely different.... An essential component of the creative process, whether it be analysis, synthesis, or the development of a new perspective or more comprehensive theory, is the conviction that one's judgment in interpreting the events is to be trusted. (Coopersmith, 1967, p. 59)In the daily stream of thought these four different stages [preparation; incubation; illumination or inspiration; and verification] constantly overlap each other as we explore different problems. An economist reading a Blue Book, a physiologist watching an experiment, or a business man going through his morning's letters, may at the same time be "incubating" on a problem which he proposed to himself a few days ago, be accumulating knowledge in "preparation" for a second problem, and be "verifying" his conclusions to a third problem. Even in exploring the same problem, the mind may be unconsciously incubating on one aspect of it, while it is consciously employed in preparing for or verifying another aspect. (Wallas, 1926, p. 81)he basic, bisociative pattern of the creative synthesis [is] the sudden interlocking of two previously unrelated skills, or matrices of thought. (Koestler, 1964, p. 121)11) The Earliest Stages in the Creative Process Involve a Commerce with DisorderEven to the creator himself, the earliest effort may seem to involve a commerce with disorder. For the creative order, which is an extension of life, is not an elaboration of the established, but a movement beyond the established, or at least a reorganization of it and often of elements not included in it. The first need is therefore to transcend the old order. Before any new order can be defined, the absolute power of the established, the hold upon us of what we know and are, must be broken. New life comes always from outside our world, as we commonly conceive that world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." (Ghiselin, 1985, p. 4)New life comes always from outside our world, as we commonly conceive our world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." Chaos and disorder are perhaps the wrong terms for that indeterminate fullness and activity of the inner life. For it is organic, dynamic, full of tension and tendency. What is absent from it, except in the decisive act of creation, is determination, fixity, and commitment to one resolution or another of the whole complex of its tensions. (Ghiselin, 1952, p. 13)[P]sychoanalysts have principally been concerned with the content of creative products, and with explaining content in terms of the artist's infantile past. They have paid less attention to examining why the artist chooses his particular activity to express, abreact or sublimate his emotions. In short, they have not made much distinction between art and neurosis; and, since the former is one of the blessings of mankind, whereas the latter is one of the curses, it seems a pity that they should not be better differentiated....Psychoanalysis, being fundamentally concerned with drive and motive, might have been expected to throw more light upon what impels the creative person that in fact it has. (Storr, 1993, pp. xvii, 3)A number of theoretical approaches were considered. Associative theory, as developed by Mednick (1962), gained some empirical support from the apparent validity of the Remote Associates Test, which was constructed on the basis of the theory.... Koestler's (1964) bisociative theory allows more complexity to mental organization than Mednick's associative theory, and postulates "associative contexts" or "frames of reference." He proposed that normal, non-creative, thought proceeds within particular contexts or frames and that the creative act involves linking together previously unconnected frames.... Simonton (1988) has developed associative notions further and explored the mathematical consequences of chance permutation of ideas....Like Koestler, Gruber (1980; Gruber and Davis, 1988) has based his analysis on case studies. He has focused especially on Darwin's development of the theory of evolution. Using piagetian notions, such as assimilation and accommodation, Gruber shows how Darwin's system of ideas changed very slowly over a period of many years. "Moments of insight," in Gruber's analysis, were the culminations of slow long-term processes.... Finally, the information-processing approach, as represented by Simon (1966) and Langley et al. (1987), was considered.... [Simon] points out the importance of good problem representations, both to ensure search is in an appropriate problem space and to aid in developing heuristic evaluations of possible research directions.... The work of Langley et al. (1987) demonstrates how such search processes, realized in computer programs, can indeed discover many basic laws of science from tables of raw data.... Boden (1990a, 1994) has stressed the importance of restructuring the problem space in creative work to develop new genres and paradigms in the arts and sciences. (Gilhooly, 1996, pp. 243-244; emphasis in original)Historical dictionary of quotations in cognitive science > Creativity
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19 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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20 something
1) (a thing not known or not stated: Would you like something to eat?; I've got something to tell you.) algo2) (a thing of importance: There's something in what you say.) algo importantesomething pron algotr['sʌmɵɪŋ]1 algo■ can I ask you something? ¿puedo preguntarte una cosa?■ would you like something to drink? ¿quieres tomar algo?2 (a thing of value) algo■ at least they didn't take much, that's something al menos no se llevaron mucho, algo es algo■ something like that algo así, algo por el estilo■ do you want a sandwich or something? ¿quieres un bocadillo o algo así?■ are you drunk or something? ¿estás borracho o qué?1\SMALLIDIOMATIC EXPRESSION/SMALLsomething else otra cosato be something else (special) ser algo extraordinario,-asomething ['sʌmɵɪŋ] pron: algoI want something else: quiero otra cosashe's writing a novel or something: está escribiendo una novela o no sé quéadv.• algo adv.• un poco adv.n.• algo s.m.• alguna cosa s.f.pron.• algo pron.
I 'sʌmθɪŋ1) algohave something to eat/drink — come/bebe algo
do you know something? I think we're lost — ¿sabes una cosa or sabes qué? creo que nos hemos perdido
is it something I said? — ¿qué pasa? ¿qué he dicho?
it's not much, but it's something — no es mucho, pero algo es
2)have you gone mad or something? — ¿te has vuelto loco o qué?, ¿es que te has vuelto loco?
b)something like: something like 200 spectators unos 200 espectadores; he looks something like his brother — se parece algo a su hermano
c)something of — ( rather)
it came as something of a surprise — me (or nos etc) sorprendió un poco
3) ( something special)it was quite something for a woman to reach that position — era todo un logro or (fam) no era moco de pavo que una mujer alcanzara esa posición
that party was something else! — (colloq) la fiesta estuvo genial or fue demasiado! (fam)
she's quite something, isn't she? — ( in looks) está bien ¿eh?; ( in general) qué mujer (or chica etc)! ¿no?
to have (got) something — ( be talented) tener* algo; ( perceive something significant)
I think you might have something there — puede que tengas razón
II
noun (no pl)won't you have a little something (to eat/drink)? — ¿no quieres comer/beber algo?
III
adverb (colloq)['sʌmθɪŋ]my back's playing me up something chronic — la espalda me tiene...!
1. PRON1) algo•
there's something about him I don't like — hay algo que no me gusta de él•
let me ask you something — déjame hacerte una pregunta, deja que te pregunte algo•
it's come to something when you get the sack for that — ¡a lo que hemos llegado! ¡que te echen por eso!•
that has something to do with accountancy — eso tiene que ver or está relacionado con la contabilidadhe's got something to do with it — está metido or involucrado en eso
•
here's something for your trouble — † aquí tiene, por la molestia•
I think you may have something there — puede que tengas razón, puede que estés en lo cierto•
there's something in what you say — hay algo de verdad en lo que diceshe's something in the City — trabaja de algo or de no sé qué en la City
•
do you want to make something of it? — ¿quieres hacer un problema de esto?•
it's not something I approve of — no es algo que yo apruebe•
there's something odd here — aquí hay or pasa algo (raro)•
it's something of a problem — es de algún modo or en cierto modo un problema, en cierto sentido representa un problemahe's something of a musician — tiene algo de músico, tiene cierto talento para la música
I hope to see something of you — espero que nos seguiremos viendo, nos estaremos viendo, espero (LAm)
•
did you say something? — ¿dijiste algo?•
well, that's something — eso ya es algo•
will you have something to drink? — ¿quieres tomar algo?2) * (=something special or unusual)•
their win was quite something — su victoria fue extraordinaria•
that's really something! — ¡eso sí que es fenomenal or estupendo!3) (in guesses, approximations)he's called John something — se llama John no sé qué, se llama John algo
•
are you mad or something? — ¿estás loco o qué?, ¿estás loco o algo así?her name is Camilla or something — se llama Camilla o algo así, se llama algo así como Camilla, se llama Camilla o algo por el estilo
•
something or other — algo, alguna cosa2. ADV1) (=a little, somewhat)a)• there were something like 80 people there — había algo así como 80 personas allí, había como unas 80 personas allí
it's something like ten o'clock — son algo así como las diez, son las diez más o menos
it cost £100, or something like that — costó 100 libras, o algo así
he looks something like me — se parece algo or un poco a mí
now that's something like a rose! — ¡eso es lo que se llama una rosa!
now that's something like it! — ¡así es como debe ser!
b)• something over 200 — algo más de 200, un poco más de 200
2) *they pull her leg something chronic — le toman el pelo una barbaridad *, le toman el pelo que es una cosa mala *
3.N•
she has a certain something — tiene un algo, tiene un no sé qué•
it's just a little something I picked up in a sale — es una tontería que compré en las rebajaswould you like a little something before dinner? — ¿quieres tomar or picar algo antes de la cena?
* * *
I ['sʌmθɪŋ]1) algohave something to eat/drink — come/bebe algo
do you know something? I think we're lost — ¿sabes una cosa or sabes qué? creo que nos hemos perdido
is it something I said? — ¿qué pasa? ¿qué he dicho?
it's not much, but it's something — no es mucho, pero algo es
2)have you gone mad or something? — ¿te has vuelto loco o qué?, ¿es que te has vuelto loco?
b)something like: something like 200 spectators unos 200 espectadores; he looks something like his brother — se parece algo a su hermano
c)something of — ( rather)
it came as something of a surprise — me (or nos etc) sorprendió un poco
3) ( something special)it was quite something for a woman to reach that position — era todo un logro or (fam) no era moco de pavo que una mujer alcanzara esa posición
that party was something else! — (colloq) la fiesta estuvo genial or fue demasiado! (fam)
she's quite something, isn't she? — ( in looks) está bien ¿eh?; ( in general) qué mujer (or chica etc)! ¿no?
to have (got) something — ( be talented) tener* algo; ( perceive something significant)
I think you might have something there — puede que tengas razón
II
noun (no pl)won't you have a little something (to eat/drink)? — ¿no quieres comer/beber algo?
III
adverb (colloq)my back's playing me up something chronic — la espalda me tiene...!
- 1
- 2
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