計(jì)算機(jī)專業(yè)英語課件E1-Unit 12

Unit11SoftwareEngineeringContentsPart1ReadingandTranslatingSectionA:BenefitsandRisksofArtificialIntelligenceSectionB:DeepLearning,MachineLearning,andAIPart2SimulatedWriting:MeetingMinutesPart3ListeningandSpeakingDialogue:ArtificialIntelligenceListeningComprehension:SupervisedLearningDictation:UnsupervisedLearning1.1SectionA:BenefitsandRisksofArtificialIntelligenceWordsoutperform[?autp??f??m]v.（效益上）超過，勝過nuisance[?nju?sns]n.損害，麻煩事lethal[?li?θl]adj.致命的，致死的quest[kwest]n.追求，尋找recursive[ri?k??siv]adj.循環(huán)的intellect[?int?lekt]n.智力，才智benevolent[b??nev?l?nt]adj.仁慈的，慈善的Wordsmalevolent[m??lev?l?nt]adj.惡毒的，有惡意的casualty[?k??u?lti]n.（戰(zhàn)爭或事故的）傷員，遇難者，受害者inadvertently[?in?d?v??tntli]adv.無意地，不經(jīng)意地thwart[θw??t]v.挫敗，反對(duì)plausible[?pl??z?bl]adj.振振有詞的，似乎合理的，似是而非的，似乎可信的1.1SectionA:BenefitsandRisksofArtificialIntelligence1.1SectionA:BenefitsandRisksofArtificialIntelligenceWordsstrikingly[?straiki?li]adv.顯著地，突出地obedient[??bi?di?nt]adj.順從的，服從的cover[?k?v?(r)]v.行走（一段路程）vomit[?v?mit]n.嘔吐literally[?lit?r?li]adv.真正地，確實(shí)地，簡直task[tɑ?sk]v.派給某人（任務(wù)）pose[p?uz]v.造成，形成1.1SectionA:BenefitsandRisksofArtificialIntelligenceWordssurefire[?u?'fai?]adj.準(zhǔn)不會(huì)有錯(cuò)的，一定成功的wittingly[?witi?li]adv.有意地unwittingly[?n?witi?li]adv.不經(jīng)意地outsmart[?aut?smɑ?t]v.比…更聰明，用計(jì)謀打敗Phrasesinthenearterm在短期內(nèi)alignwith使一致wreakhavoc造成嚴(yán)重破壞，肆虐sideeffect副作用，意外的連帶后果stepon踩上…，踏上…outofmalice出于惡意bigname成功人士，知名人士thinkofas把…看作，被認(rèn)為是1.1SectionA:BenefitsandRisksofArtificialIntelligenceNotes[1]SIRI是SpeechInterpretation&RecognitionInterface的首字母縮寫，原義為語音識(shí)別接口，是蘋果公司在蘋果手機(jī)、iPad、iPodTouch、HomePod等產(chǎn)品上應(yīng)用的一個(gè)語音助手，利用SIRI用戶可以通過手機(jī)讀短信、介紹餐廳、詢問天氣、語音設(shè)置鬧鐘等。[2]IBM的沃森（Watson）誕生于世界上最大的科技公司之一的總部，是一款專門用來解決開放式問題回答這一有害問題的計(jì)算機(jī)。雖然計(jì)算機(jī)在基于關(guān)鍵字進(jìn)行閃電式快速搜索方面表現(xiàn)出色，但計(jì)算機(jī)開發(fā)人員長期以來對(duì)人工智能的無能為力感到沮喪。為了正確理解上下文識(shí)別以及人類交流和語言中的復(fù)雜關(guān)系，Watson專門設(shè)計(jì)了一種獨(dú)特的方法來嘗試和解決這個(gè)長期存在的問題：開發(fā)者可以通過讓它玩流行的美國游戲節(jié)目《危險(xiǎn)邊緣》（Jeopardy）來測試它的能力！1.1SectionA:BenefitsandRisksofArtificialIntelligenceNotes[3]Original:Whereasitmaybelittlemorethanaminornuisanceifyourlaptopcrashesorgetshacked,itbecomesallthemoreimportantthatanAIsystemdoeswhatyouwantittodoifitcontrolsyourcar,yourairplane,yourpacemaker,yourautomatedtradingsystemoryourpowergrid.Translation:如果你的筆記本電腦崩潰或被黑客入侵，那可能只是些小麻煩，但如果AI系統(tǒng)控制著你的汽車、飛機(jī)、起搏器、自動(dòng)交易系統(tǒng)或電網(wǎng)，那么它們就會(huì)變成大問題。1.1SectionA:BenefitsandRisksofArtificialIntelligenceExercisesI.Readthefollowingstatementscarefully,anddecidewhethertheyaretrue(T)orfalse(F)accordingtothetext.1.TheconcernaboutadvancedAIisn'tmalevolencebutbenevolent.2.Human-levelAIwouldhappenbefore2030.3.ArtificialintelligencetodayisproperlyknownasstrongAI.4.In1965BillGatespointoutthatdesigningsmarterAIsystemsisitselfacognitivetask.5.AI(orweakAI)isdesignedtoperformanarrowtasklikefacialrecognition.1.1SectionA:BenefitsandRisksofArtificialIntelligenceII.Choosethebestanswertoeachofthefollowingquestionsaccordingtothetext.1．Whichofthefollowingdescriptionisnotright?A．StrongAIwouldoutperformhumansatnearlyeverycognitivetask.B．BecauseAIhasthepotentialtobecomemoreintelligentthananyhuman,wehavenosurefirewayofpredictinghowitwillbehave.C．Whilesomeexpertsstillguessthathuman-levelAIiscenturiesaway,someAIresearchersguessedthatitwouldhappenbefore2030.D．Inthelongterm,animportantquestioniswhatwillhappenifthequestforstrongAIsucceedsandanAIsystembecomesbetterthanhumansatallcognitivetasks.2．WhichofthefollowingisataskperformedbyweakAI?A．InternetsearchesB．Facialrecognition C．Drivingacar D．Alloftheabove1.1SectionA:BenefitsandRisksofArtificialIntelligence3．Whichofthefollowingdescriptionisright?A．AItodaycanexhibithumanemotionslikeloveorhate.B．AItodaycanexhibithumanmoralcharacterslikebenevolentormalevolent.C．StrongAImighthelpuseradicatewar,disease,andpoverty.D．Alloftheabove1.1SectionA:BenefitsandRisksofArtificialIntelligenceⅢ.Identifytheletterofthechoicethatbestmatchesthephraseordefinition.a.semanticnetworkb.artificialneuralnetworkc.roboticsd.Turingteste.expertsystems_____1.Acomputerattemptstomimictheactionsoftheneuralnetworksofthehumanbody_____2.Thestudyofrobots_____3.Onemeasuretodeterminewhetheramachinecanthinklikeahumanbymimickinghumanconversation_____4.Aknowledgerepresentationtechniquethatfocuses_____5.Computersystemsthatembodytheknowledgeofhumanexperts1.1SectionA:BenefitsandRisksofArtificialIntelligenceIV.TranslatethefollowingpassageintoChinesePhysicalAgentsAphysicalagent(robot)isaprogrammablesystemthatcanbeusedtoperformavarietyoftasks.Simplerobotscanbeusedinmanufacturingtodoroutinejobssuchasassembling,welding,orpainting.Someorganizationsusemobilerobotsthatdodeliveryjobssuchasdistributingmailorcorrespondencetodifferentrooms.Therearemobilerobotsthatareusedunderwaterforprospectingforoil.1.1SectionA:BenefitsandRisksofArtificialIntelligenceIV.TranslatethefollowingpassageintoChineseAhumanoidrobotisanautonomousmobilerobotthatissupposedtobehavelikeahuman.Althoughhumanoidrobotsareprevalentinsciencefiction,thereisstillalotofworktodobeforesuchrobotswillbeabletointeractproperlywiththeirsurroundingsandlearnfromeventsthatoccurthere.1.1SectionA:BenefitsandRisksofArtificialIntelligence1.2SectionB:DeepLearning,MachineLearning,andAIWordsfeaturization[fi:t??rai'zei??n]n.特征化，特性化schema[?ski?m?]n.模式，計(jì)劃caption[?k?p?n]n.標(biāo)題convolutional[?k?nv??lu???n(?)l]adj.卷積的recurrent[ri?k?r?nt]adj.循環(huán)的around[??raund]adv.大約，到處snippet[?snipit]n.片斷1.2SectionB:DeepLearning,MachineLearning,andAIWordstranscribe[tr?n?skraib]v.改編，轉(zhuǎn)錄，抄寫concise[k?n?sais]adj.簡明的，簡練的，簡潔的claim[kleim]n.（向公司等）索賠typology[tai?p?l?d?i]n.分類法，類型學(xué)feedforward['fi?df??w?d]n.前饋（控制）1.2SectionB:DeepLearning,MachineLearning,andAIPhrasesimproveat提升，改善excelat擅長于，擅長serveas充當(dāng)，用作imagecaptioning圖像標(biāo)注insidertrading內(nèi)線交易1.2SectionB:DeepLearning,MachineLearning,andAIAbbreviationsGPUGraphicsProcessingUnit圖形處理器1.2SectionB:DeepLearning,MachineLearning,andAIExercisesI.Readthefollowingstatementscarefully,anddecidewhethertheyaretrue(T)orfalse(F)accordingtothetext.1．AIisasubsetofmachinelearning2．Machinelearningisasubsetofdeeplearning.3．Objectdetectionconsistsoftwoparts:videoclassificationandthenvideolocalization.4．Recurrentneuralnetworksarewidelyusedforcomplextaskssuchastimeseriesforecasting,learninghandwritingandrecognizinglanguage.5．Deeplearningmodelsuseneuralnetworksthathavemanylayers.1.2SectionB:DeepLearning,MachineLearning,andAIII.Choosethebestanswertoeachofthefollowingquestionsaccordingtothetext.1．Whichofthefollowingisright?A．ArtificialIntelligence(AI)includesmachinelearning. B．Machinelearningisasubsetofartificialintelligence. C．Deeplearningisasubsetofmachinelearning. D．Alloftheabove2．Whichofthefollowingbelongstoartificialneuralnetwork?A．Convolutionalneuralnetwork B．Recurrentneuralnetwork C．Feedforwardneuralnetwork D．Alloftheabove1.2SectionB:DeepLearning,MachineLearning,andAI3．Howmanykindsofartificialneuralnetworksarementionedinthistext?A．OneB．TwoC．Three D．FourⅢ.Identifytheletterofthechoicethatbestmatchesthephraseordefinition.a.propositionallogicb.computervisionc.perceptrond.AIe.deeplearning_____1.Atechniquethatenablescomputerstomimichumanintelligence_____2.Anartificialneuronsimilartoasinglebiologicalneuron_____3.Alanguagemadeupfromasetofsentencesthatcanbeusedtocarryoutlogicalreasoningabouttheworld_____4.AnareaofAIthatdealswiththeperceptionofobjectsthroughtheartificialeyesofanagent,suchasacamera_____5.Asubsetofmachinelearningthat'sbasedonartificialneuralnetworks1.2SectionB:DeepLearning,MachineLearning,andAI1.2SectionB:DeepLearning,MachineLearning,andAIIV.TranslatethefollowingpassageintoChinese.LSTMNetworksLongShortTermMemorynetworks–usuallyjustcalled"LSTMs"–areaspecialkindofRNN,capableoflearninglong-termdependencies.TheywereintroducedbyHochreiter&Schmidhuber(1997),andwererefinedandpopularizedbymanypeopleinfollowingwork.Theyworktremendouslywellonalargevarietyofproblems,andarenowwidelyused.1.2SectionB:DeepLearning,MachineLearning,andAIIV.TranslatethefollowingpassageintoChinese.LSTMsareexplicitlydesignedtoavoidthelong-termdependencyproblem.Rememberinginformationforlongperiodsoftimeispracticallytheirdefaultbehavior,notsomethingtheystruggletolearn!2.SimulatedWriting:MeetingMinutesProfessionalLetters1.簡介會(huì)議記錄是作為一組會(huì)議的準(zhǔn)確記錄的書面材料。會(huì)議記錄記錄會(huì)議的決定，會(huì)議中通過決議的行動(dòng)，更重要的是提供了一個(gè)用于在下次會(huì)議上評(píng)估進(jìn)展的回顧文檔。這個(gè)過程對(duì)通過決議行動(dòng)的個(gè)人執(zhí)行和非執(zhí)行的情況一目了然，使其成為一種有用的維持紀(jì)律的方法。會(huì)議記錄還可以告知沒有參加會(huì)議的人們會(huì)上講了什么。2.SimulatedWriting:MeetingMinutesProfessionalLetters2.內(nèi)容每次會(huì)議前都應(yīng)該制定一個(gè)會(huì)議日程，詳細(xì)列出在會(huì)議上應(yīng)該討論的問題。會(huì)議記錄應(yīng)該包括以下的信息：（1）會(huì)議的時(shí)間、日期以及地點(diǎn)；（2）出席會(huì)議人員的名單，以及缺席人員的名單；（3）以前會(huì)議記錄中通過的部分，以及起因于這些會(huì)議記錄的任一問題；（4）對(duì)議事日程中的每一項(xiàng)，記錄所討論的主要觀點(diǎn)以及做出的決定；2.SimulatedWriting:MeetingMinutesProfessionalLetters2.內(nèi)容（5）一致通過的行動(dòng)的列表；（6）對(duì)于行動(dòng)中的每一項(xiàng)，要有負(fù)責(zé)人以及期限列表；（7）下一次會(huì)議的時(shí)間、日期以及地點(diǎn)；（8）會(huì)議記錄的人員姓名。2.SimulatedWriting:MeetingMinutesProfessionalLetters3.書寫技巧可以使用許多技巧來書寫有效的會(huì)議記錄：（1）在會(huì)議前分發(fā)會(huì)議日程（通過電子郵件），這樣可以使會(huì)議的參與成員有機(jī)會(huì)來做準(zhǔn)備。（2）在會(huì)議議程的最后部分寫入“其他事宜”項(xiàng)作為書寫最后項(xiàng)的地方。（3）使會(huì)議記錄簡潔而且突出重點(diǎn)，不要廢話連篇。如果想要記錄會(huì)議中的每一句話，最好考慮用錄音來補(bǔ)充會(huì)議記錄。（4）當(dāng)要求某個(gè)團(tuán)隊(duì)成員去執(zhí)行某個(gè)任務(wù)時(shí)，就記錄一個(gè)“行動(dòng)”標(biāo)記，這樣使得在下次會(huì)議時(shí)能夠很容易地閱讀之前的會(huì)議記錄，并且鉤上“行動(dòng)”標(biāo)記。（5）不論是在會(huì)議過程中書寫會(huì)議記錄（如果會(huì)議記錄員是一個(gè)快速打字員），還是在會(huì)議之后馬上書寫，都要遵循越早完成、準(zhǔn)確率越高的原則。（6）書寫記錄時(shí)要用過去式，所書寫的是已經(jīng)發(fā)生過的討論。從筆記打成會(huì)議記錄的過程，是在記錄一個(gè)過去的事件。2.SimulatedWriting:MeetingMinutesProfessionalLetters4.格式組織的名稱年月日時(shí)間和地點(diǎn)出席名單：出席會(huì)議的成員姓名缺席名單：缺席會(huì)議的成員姓名2.SimulatedWriting:MeetingMinutesProfessionalLetters4.格式會(huì)議進(jìn)程：會(huì)議（時(shí)間）由（某個(gè)人，通常是主席）宣布開始開會(huì)會(huì)議記錄（之前的會(huì)議日期）的修正和認(rèn)可提出和討論的焦點(diǎn)問題采取的行動(dòng)會(huì)議中止于（時(shí)間）2.SimulatedWriting:MeetingMinutesProfessionalLetters4.格式將來的業(yè)務(wù)：這里用來提醒人們以下幾項(xiàng)：在下次會(huì)議之前將被提交的談話內(nèi)容為即將舉行的會(huì)議提供可能的會(huì)議日程團(tuán)隊(duì)成員已經(jīng)承擔(dān)的任務(wù)會(huì)議記錄由（姓名）提交2.SimulatedWriting:MeetingMinutesProfessionalLetters5.范例Go3DGameMinutesofthe6thGroupMeeting

Date:October9,2020Time:9:30a.m.—10:00a.m.Duration:0.5hourVenue:Prof.Smith’sofficePresent:Prof.Smith,ChauChunTing(Charles),ChangKinFung(Tony)Minutesrecorder:ChangKinFung(Tony)Absent:LamSheungYan(Michael)AuKwokWang(Chris)(1)ApprovalofMinutesoftheLastMeetingMinutesofthelastmeetingwereapprovedasanaccuraterecord.2.SimulatedWriting:MeetingMinutesProfessionalLetters5.范例(2)DiscussionofProjectDevelopment?Charlesraisedthequestionaboutthecamera:ifthecameraisabovethecharacteratsomeparticularangle,thenweareunabletoseeveryfartothefrontandmaynotseetheenemies.?ProfessorSmithsaidthattherewasnoso-called“good”viewangle.Ifthecameraviewisthatofthecharacter,thenwecanseethevirtualworld,butweareunabletoseethecharacter.Theplayermaylosehisorientationsincehehasnosenseaboutwherethecharacteris.?Tonyaskedwhetheritwasaproblemforthecharactertoturnaroundbecausethescenewouldchangeveryquicklyandthusmaketheplayerfeeluncomfortable.?Prof.Smithsaidthatlimitingthespeedofturnaroundcouldsolvetheproblem.Hesaidthatthemainpointwastomakethegameinterestingandexciting.Theviewanglewasnotthatimportant.?ProfessorSmithsuggestedthatweshoulddesignamaptodisplaythelocationofthecharactersothattheplayerscanbeawareoftheprogressandtheplaceofthecharacter.2.SimulatedWriting:MeetingMinutesProfessionalLetters5.范例(3)MeetingArrangementsProfessorSmithaskedeachgrouptogiveasimpledemooftheirGOinthenextgroupmeeting.Forthedemo,eachgroupshouldbeabletoimplementa3Denvironmentwiththecharacter’smovements,forinstance,forwardandbackwardmovements.Thepurposeofthedemoistomakesureeachgrouphassomebasicideasofhowtoimplement3Dobjectsandcontrolthem.(4)AdjournmentofMeetingThemeetingwasadjournedat10:00a.m.(5)NextMeetingDate:October16,2020Time:2:00p.m.—3:00p.m.Place:GOLab2.SimulatedWriting:MeetingMinutesProfessionalLetters5.范例(6)ActionsAgreedUponWrittenbyTonyonOctober10,2014Actionlist,dated9October2020Itemno.ActionByDeadlineStatusaGiveasimpledemoofa3Dskyenvironmentwiththecharacter’smovementsCharlesOct.16,2020

bGiveasimpledemoofa3Dwaterenvironmentwiththecharacter’smovementsTonyOct.16,2020

cGiveasimpledemoofa3Dlandenvironmentwiththecharacter’smovementsPatrickOct.16,2020

dGiveasimpledemoofacharacterChrisOct.16,2020

3.1Dialogue:ArtificialIntelligenceWordscoin[k?in]v.創(chuàng)造（新詞，短語），杜撰 mimic[mimik]v.模仿household[?haush?uld]adj.家喻戶曉的complement['k?mplim(?)nt]v.補(bǔ)足，補(bǔ)助augment[??g?ment]v.增加，增大scary[?ske?ri]adj.（事物）可怕的，引起驚慌的3.1Dialogue:ArtificialIntelligenceWordsfatigue[f??ti?g]n.疲勞，疲乏bot[b?t]n.網(wǎng)上機(jī)器人，自動(dòng)程序radiologist[?reidi??l?d?ist]n.放射科醫(yī)生，放射線研究者3.1Dialogue:ArtificialIntelligenceAbbreviationsMRIMagneticResonanceImaging核磁共振成像Notes①見本章SectionA中的[1]。②Alexa是一家專門發(fā)布網(wǎng)站世界排名的網(wǎng)站。Alexa每天在網(wǎng)上搜集超過1,000GB的信息，不僅給出多達(dá)幾十億的網(wǎng)址鏈接，而且為其中的每一個(gè)網(wǎng)站進(jìn)行了排名。可以說，Alexa是當(dāng)前擁有URL數(shù)量最龐大，排名信息發(fā)布最詳盡的網(wǎng)站。③微軟小娜（Cortana）是微軟公司發(fā)布的全球第一款個(gè)人智能助理。它“能夠了解用戶的喜好和習(xí)慣”，“幫助用戶進(jìn)行日程安排、問題回答等”。3.1Dialogue:ArtificialIntelligence3.2ListeningComprehension:SupervisedLearningListentothearticleandanswerthefollowing3questionsbasedonit.Afteryouhearaquestion,therewillbeabreakof15seconds.Duringthebreak,youwilldecidewhichoneisthebestansweramongthefourchoicesmarked(A),(B),(C)and(D).Questions1． Whichofthefollowingisright?(A)Supervisedlearningisthemachinelearningtaskoflearningafunctionthatmapsaninputtoanoutputbasedonexampleinput-outputpairs. (B)Supervisedlearninginfersafunctionfromlabeledtrainingdataconsistingofasetoftrainingexamples.(C)Asupervisedlearninga