高考英语二轮测试阅读理解词义猜测题（原卷版）- （北京专用）

这是一份高考英语二轮测试阅读理解词义猜测题（原卷版）- （北京专用），共17页。试卷主要包含了Mars等内容，欢迎下载使用。

2024 年北京高考英语阅读理解试题题材广泛，涵盖人与自我、人与社会和人与自然等多个主题语境，贴近时代、贴近社会、贴近生活、贴近学生。试题依托语篇，全面考查学生的阅读理解能力，突出高阶思维的考查，引导中学教学回归课标、回归课堂。阅读理解的选材注重价值引领，体现学科的育人功能。例如，有的文章讲述了作者在一次考试失败后，不断突破自我、锲而不舍追逐梦想的历程；有的文章指出人类应停止“宇宙是不是模拟”的争论，依托新的科技成果，创造性地探索未知世界；还有的文章从科学的视角探讨道德规范的根源。这些文章不仅有助于考生获取有效信息，正确认识世界和中国发展大势，还能培养考生的国际意识和文化素养。
阅读理解题型多样，包括细节理解题、推理判断题、主旨大意题等。试题考查考生对语篇内容、语篇结构的理解和把握，以及对语篇内容的分析、阐释和评价。
词义猜测题主要考查同学们在具体文章中，根据上下文理解某个词或某个短语的意义的能力。这类题型中所出现的单词，大多是同学们未曾见过的生词。
在做题时，大家可在该词出现的上下文中去寻找线索，通过上下文的语境，推断出该词的真正含义。最后，记得要将“释义”代入文中，进行检验、比较，直到得出该词的确切含义。
（1）通过因果关系猜词
如果生词附近出现了because，as，since，fr，s，thus，as a result，f curse，therefre等关联词，同学们可以通过找出生词与上下文之间的逻辑关系，推断生词的词义。例如：Yu shuldn't have blamed him fr that，fr it wasn't his fault.其中，通过fr引出的句子所表示的原因（那不是他的错），大家便可猜出blame的词义是“责备”。
（2）通过同义词和反义词的关系猜词
同义词猜词适用于两种情况。一种是由and或r连接的同义词词组，如。happy and gay，即使我们不认识gay这个词，也可以知道它是“愉快”的意思。另一种是在进一步解释的过程中使用的同义词，如，Man has knwn smething abut the planets Venus，Mars，and Jupiter with the help f spaceships.此句中的Venus(金星)、Mars(火星)、Jupiter(木星)均为生词，但只要知道planets就可猜出这几个词都属于“行星”这一义域。
反义词猜词，与因果关系猜词的方法类似。这类方法适用于句中有表转折关系的连词或副词，如but，while，hwever等，或是与nt搭配的或表示否定意义的词语。如，He is s hmely，nt at all as handsme as his brther.根据nt at ，我们不难推测出hmely的意思，即不英俊、不漂亮。
（3）通过构词法猜词
在阅读文章时，我们还会遇上这一类新的词汇，它们有时很难根据上下文来推断其词意，但其对文章的理解又有着举足轻重的作用。此时，我们可以利用一些常见的词根、前缀、后缀等语法知识，对其进行拆分、推测。
（4）通过定义或释义关系来推测词义
如，But smetimes，n rain falls fr a lng lng time. Then there is a dry perid，r drught.从drught所在句子的上文我们得知，“很久不下雨，于是便有一段干旱的时期，即drught，由此可见，drught意为“久旱、旱灾”。而a dry perid和drught是同义语。这种同义或释义关系常由is，r，that is，in ther wrds，be called或破折号等来表示。
（5）通过句法功能来推测词义
如，Bananas，ranges，pineapples，ccnuts and sme ther kind f fruit grw in warm areas.假如pineapples和ccnuts是生词，我们可以从这两个词在句中所处的位置来判断它们大致的意思。从句中不难看出，pineapples，ccnuts和bananas，ranges是同类关系，同属fruit类，因此，它们是两样水果，准确地说，是菠萝和椰子。
词义猜测题
词义猜测题常用解题方法：定义法、对比法、因果法、常识联想法、例举法、语境线索法、构词法等。猜词题可以使用以下口决：
1.指代词：出现指代往前找，单复人物要看好；
2.半熟悉词，利用构词法：半生不熟看构词，结合语境来把持；
3.纯生词，则利用逻辑关系、同义解释、上下文语境：同义语境和逻辑，上下求索寻真义。
题型01 构词法
【题型诠释】
构词法是通过词根、前缀、后缀等来猜测词义的方法。
【典例】
（23-24高二下·北京昌平·期末）Our planet has just seen its httest mnth n recrd, with many places n fire r flded. The likelihd f extreme weather keeps increasing—and peple are nticing. Hwever, nt everyne ntices r feels this threat t the same extent.
Based n a representative sample f 1,071 survey respndents frm acrss the UK, we fund that peple in rural areas shwed higher degrees f place attachment than peple living in cities, as we expected. Hwever, we were surprised t see that the perceived threat f climate change in: mst rural lcatins was lwer. We had nt expected that utcme, s we started t dig a little deeper fr pssible reasns.
Rural peple may be mre resilient t change. Rural peple may experience climate change like everyne else, but they may have better ways f cping with it than city residents because f their clser relatinship with nature. This may have taught them t be mre flexible in hw they deal with change. After all, nature changes a lt and that culd make them less wrried abut the majr changes happening arund them.
Peple in rural areas may nt be as aware f climate change as peple in cities. Lking mre clsely, the effect is mstly dwn t educatin rather than whether peple live in rural areas r nt. Research shws that general levels f climate awareness in the UK are quite high. But this des nt necessarily crrespnd t readiness fr actin r behaviural change. It is well dcumented, thugh, that rural inhabitants tend t have mre cnservative views, which culd affect the way climate change is interpreted. Cnservative views are ften assciated with less cncern abut the climate.
Peple in rural areas may nt experience climate change in the same wav as peple in cities. This is because rural areas have higher levels f green space than urban areas. Fr example, yu will feel the heat less when yu are surrunded by trees.
S, althugh we were surprised that the higher degree f place attachment in peple living rurally did nt necessarily lead t a higher perceptin f climate change threat, we can see there are gd reasns fr that.
24．What des the wrd “resilient” underlined in Paragraph 3 mst prbably mean?
A．Easy t adapt.B．Ready t illustrate.
C．Difficult t ntice.D．Willing t challenge.
题型02 定义词或标点符号
【题型诠释】
通过寻找定义、同位语、定语从句等来获取词义。
利用定义表达如同位语、定语从句或由…is, r, that is (t say), in ther wrds, be called，be knwn as，means等词汇或破折号来表示。
【典例】
（23-24高二下·北京海淀·期末）A theme at this year’s Wrld Ecnmic Frum (WEF) meeting was the perceived need t “accelerate breakthrughs in research and technlgy”. Sme f this framing was mtivated by the climate emergency, sme by the pprtunities and challenges presented by generative artificial intelligence. Yet in varius cnversatins, it seemed t be taken fr granted that t address the wrld’s prblems, scientific research needs t mve faster.
The WEF mindset resnates (产生共鸣) with the Silicn Valley dictate — usually credited t Mark Zuckerberg — t mve fast and break things. But what if the thing being brken is science? Or public trust?
The WEF meeting tk place just a frtnight after Harvard University President Claudine Cay stepped dwn after cmplaints were made abut her schlarship. Gay’s trubles came n the heels f the resignatin f Stanfrd University President Mare Tessier-Lavigne, after an internal investigatin cncluded that his neurscience research had “multiple prblems”. In respnse. Gay requested crrectins t several f her papers; Tessier-Lavigne requested retractin (撤回) f three f his. Althugh it may be impssible t determine just hw widespread such prblems really are, it’s hard t imagine that the spectacle f high-prfile schlars crrecting and retracting papers has nt had a negative impact n public trust in science and perhaps in experts bradly.
In recent years we’ve seen imprtant papers, written by prminent scientists and published in prestigius jurnals, retracted because f questinable data r methds. In ne interesting case, Frances H. Arnld f the Califrnia Institute f Technlgy, wh shared the 2018 Nbel Prize in Chemistry, vluntarily retracted a paper when her lab was unable t replicate her results — but after the paper had been published. In an pen aplgy, she stated that she was “a bit busy” when the paper was submitted and “did nt d my jb well”. Arnld’s hnesty is admirable, but it raises a questin: Are schlars at super cmpetitive places really taking the time t d their wrk right?
The prblem is nt unique t the U. S. In Eurpe, frmal research assessments — which are used t allcate future funding — have fr years judged academic departments largely n the quantity f their utput. Due t the fact that the existing system has created a cunterincentive t advancement in science, a refrm is underway urging an emphasis n quality ver quantity.
Gd science takes time. Nearly a century passed between bichemist Friedrich Miescher’s identificatin f the DNA mlecule and suggestin that it might be invlved in inheritance and the elucidatin f its duble-helix structure in the 1950s. And it tk just abut half a century fr gelgist and gephysicists t accept gephysicist Alfred Wegener’s idea f cntinental drift.
There’s plenty f circumstantial evidence that scientists and ther schlars are pushing results ut far faster than they used t. Sme f this grwth is driven by mre scientists and mre c-authrship (papers, but it als suggests that the research wrld has priritized quantity ver quality. Researched may need t slw dwn — nt speed up — if we are t prduce knwledge wrthy f trust.
11．The underlined wrd “cunterincentive” in Paragraph 5 refers t a (n) ______ factr.
A．unfairB．indecisiveC．discuragingD．irratinal
题型03 连接词
【题型诠释】
通过转折、因果、并列等连接词来推断词义。常见连接词有：
1. 表转折关系的词常有but, while, hwever, instead f , rather than , unlike, yet, thugh , t…t等；
2. 表因果的连接词: because, as, since, fr, s, as a result, s … that, such … that, therefre；
3. 表并列或选择的连接词: and，r。
【典例】
（23-24高一上·北京西城·期末）Bed rtting — the practice f spending lng perids f time just staying under the cvers with snacks, screens and ther creature cmfrts — is gaining ppularity n scial media. Sme Generatin Z trend fllwers are nw viewing it as a frm f self-care, but dctrs warn t much culd be “sign f depressin”. Are these extended breaks really wise fr ne’s mental health — r culd they be a cause fr cncern?
Dr. Ryan Sultan, a prfessr at Clumbia University in New Yrk, wh treats many yung peple, called the bed rtting trend attractive. “In ur culture tday, with t much t d, t many expectatins and t much prductivity, many yung individuals (个人) are feeling burned ut and ften aren’t getting enugh sleep. It’s easy t see why taking time ff t lie arund is attractive,” Sultan said. “In many ways, this is beneficial. It’s a chance t get away frm real-life prblems and clear yur head befre returning t life in a better state f mind, ” he added.
Fr the dwnside, hwever, he said a lng-term need r desire fr bed rtting culd d harm t ne’s physical health. Spending t many daytime hurs in bed — awake r nt — culd destry sleep schedules. Our brains are fine-tuned fr sleep in darkness and alertness in light. Lying in bed half-asleep during the day will wrsen sleep schedules — nce that happens, it is a challenge t fix. It culd als lead t bld pressure prblems and besity (肥胖).
Lng-term need r desire fr bed rtting culd als be a warning sign f depressin, accrding t a mental health expert. Dr. Marc Siegel, prfessr f medicine at NYU Langne Medical Center and a Fx News medical cntributr, agreed that while sme dwntime can be useful in terms f de-stressing and rejuvenatin (更新), t much bed rtting is a bad health practice. In additin t increasing the risk f depressin, it cntributes t decreased mtivatin (动力) as well.
Instead f bed rtting, Siegel recmmends regular exercise as a better frm f de-stressing. While the ccasinal lazy day can be beneficial, t much culd have the ppsite effect. If it happens every day, that’s a fairly sensitive test fr depressin. Thse wh lack the mtivatin t get ut f bed culd als try calling r texting a family member fr supprt, scializing with clse friends, finding a small task t cmplete, r reaching ut t a medical prfessinal fr help.
6．What des the wrd “fine-tuned” underlined in Paragraph 3 prbably mean?
A．Quickly-activated.B．Well-trained.C．Badly-needed.D．Ill-equipped.
题型04 常识和语境
【题型诠释】
在仅靠分析篇章内在逻辑关系和语境无法猜出词义时，我们可以借助生活经验和普通常识确定词义。阅读题文段题材丰富，涉及社会、科普、政治、文化、经济、历史、生活、风俗等多方面知识。
【典例】
（23-24高二上·北京朝阳·期末）If the great dinsaurs hadn’t gne extinct, wuld they have dminated Earth tday? There has been a debate abut this pssibility fr decades. Recently tw analyses have put the surprising cgnitive (认知) abilities f dinsaurs — and their ptential limitatins — in a new light.
In ne study, Suzana Herculan-Huzel at Vanderbilt University calculated the likely number f neurns (神经细胞) in dinsaurs’ pallium, a brain structure that is respnsible fr advanced cgnitive functins. Research suggests that it is the number f neurns in these areas, rather than the brain size, that indicates an animal’s cgnitive ptential. Fr example, despite having a very small head, birds have mre densely packed brain cells than many mammals (哺乳动物) and s can pssess rughly as many neurns as mnkeys. The result is that sme birds shw great cgnitive abilities, cmparable t the smartest nn-human mammals. And it is precisely birds, being the nly surviving lineage (宗系) f dinsaurs, that are Herculan-Huzel’s fundatin. By cmparing the relatinship between brain size, number f neurns and bdy size in numerus existing birds and available fssils f dinsaurs, Herculan-Huzel cncludes that a large dinsaur such as T. rex culd have hused tw billin t three billin neurns in its pallium. If s, dinsaurs culd have had the capacity fr tl use and planning fr the future.
But neurns’ number may nt be enugh. Fr intelligence, brain architecture als matters. And this culd be the weakness f dinsaurs, argues Antn Reiner frm the University f Tennessee. Over 350 millin years f separate evlutin, mammals and dinsaurs fund tw rather different ways t rganize cgnitive functins. The mammalian neurns are rganized in a relatively thin layer frmed by cmpact clumns. In each clumn, different parts can cmmunicate with ne anther ver shrt distances. In cntrast, in the dinsaurs that survive tday, namely birds, the rganizatin is less cmpact. Accrding t Reiner, expanding brain capabilities beynd a certain pint culd make the structure far mre cmplex and less efficient than it is in humans. If this were the case, an increase in brain size wuld crrespnd t a greater distance between different parts f the brain, slwing dwn their cmmunicatin.
The issue remains pen t debate. Herculan-Huzel and Reiner each published a paper with rejectins t the ther’s argument. Meanwhile, ther scientists have entered the fight. Fr example, neurbilgist Girgi Vallrtigara assumes that speed in transmitting infrmatin between netwrks f neurns is prbably ne f dinsaurs’ strengths.
Whatever the truth is, understanding hw and if brain architecture impses limits n the develpment f cgnitin culd reveal much abut the evlutin f abilities and behavirs f varius animals. Als, this debate may tell us mre abut ur wn species than abut dinsaurs.
2．What des the wrd “cmpact” underlined in Paragraph 3 mst prbably mean?
A．Tight.B．Light.C．Large.D．Wide.
题型05 指代
【题型诠释】
通过寻找指代词的前后文来确定词义。如在句子“Despite the celebratins, thugh, in the US, the jazz audience cntinues t shrink and grw lder, and the music has failed t cnnect with yunger generatins. It's Jasn Mran's jb t help change that... ”中，“that”指代的是前文提到的“jazz being less ppular with the yung”。
题型 06 例子
【题型诠释】
通过一些例子说明生词的词义, 用such as, fr example, like, fr instance等来引出。在特定的情况下，作者通过一连串同一类型或范畴的词语来表达其思想，如果有一生词就在一系列同范畴的词语中，可以通过这些词的特征和语义范围来推断出生词的词义范围。
【典例】
（23-24高二下·北京东城·期末）When climate activists glued themselves t the frame f a cpy f The Last Supper at Lndn’s Ryal Academy f Arts, they received a fairly sympathetic hearing. “N painting is wrth mre than my six-mnth-ld nephew’s life,” said a prtester, criticizing the British gvernment’s supprt f the fssil fuel industry during the urgent climate crisis. But when prtesters threw tmat sup at Van Ggh’s Sunflwers, and mashed ptates at Haystacks by Mnet — the censure rse.
“Abslutely absurd,” said the culture minister f France. “We have been deeply shaken by their risky endangerment,” read a statement frm the Internatinal Cuncil f Museums.
The prtesters are targeting wrks that are prtected behind glass — at least fr nw — s actual damage has been minimal. And perhaps the anger greeting their acts prves their pint: that peple care mre abut the threatened destructin f a painting than the actual destructin f the planet. But as the attacks wear n, and their impact decreases, they risk changing int a jke.
What’s especially misguided abut the prtests is their binary nature. “What is wrth mre, art r life?” a prtester asked. Why chse? “It’s pssible t blame bth envirnmental vandalism (蓄意破坏) and cultural vandalism at the same time,” Mark Pasnik, chair f the Bstn Art Cmmissin, said.
Art is nt the prblem here. In fact, cntemprary artists are making quite effective wrks abut the climate crisis, precisely using art as activism. Maya Lin’s Ghst Frest, a climate change memrial she created in a New Yrk City park, is nly ne example. “I believe that art can help us imagine and map sustainable future scenaris (设想), and, in ding s, give peple a way t see and hpe fr a different future,” Lin said.
The climate activists are surely crrect that the pace f refrm is far t slw, as the planet burns and deadly strms intensify. But they casually dismiss the sincere effrts f millins f peple wrking n the issue. It wuld be easier t respect the yung prtesters at Just Stp Oil, Last Generatin, and the rest f the splash grups if they were t spend their time and energy n the unexciting but essential plitical wrk arund climate change: legislatin, regulatin, and winning hearts and minds.
Perhaps predictably, the debates caused by the prtests have nt been abut climate change, but abut the prtests themselves. Given hw little they’ve dne t generate serius discussin r engage peple t the cause, the art attacks seem less like vital acts f lawbreaking than mere theatre.
20．What des the underlined wrd “censure” in Paragraph 1 prbably mean?
A．Apprval.B．Criticism.C．Stress.D．Spirits.
【高考真题】
【2024北京卷】
The ntin that we live in smene else’s vide game is irresistible t many. Searching the term “simulatin hypthesis” (模拟假说) returns numerus results that debate whether the universe is a cmputer simulatin —— a cncept that sme scientists actually take seriusly. Unfrtunately, this is nt a scientific questin. We will prbably never knw whether it’s true. We can, instead, use this idea t advance scientific knwledge.
The 18th-century philspher Kant argued that the universe ultimately cnsists f things-in-themselves that are unknwable. While he held the ntin that bjective reality exists, he said ur mind plays a necessary rle in structuring and shaping ur perceptins. Mdern sciences have revealed that ur perceptual experience f the wrld is the result f many stages f prcessing by sensry systems and cgnitive (认知的) functins in the brain. N ne knws exactly what happens within this black bx. If empirical (实证的) experience fails t reveal reality, reasning wn’t reveal reality either since it relies n cncepts and wrds that are cntingent n ur scial, cultural and psychlgical histries. Again, a black bx.
S, if we accept that the universe is unknwable, we als accept we will never knw if we live in a cmputer simulatin. And then, we can shift ur inquiry frm “Is the universe a cmputer simulatin?” t “Can we mdel the universe as a cmputer simulatin? ” Mdelling reality is what we d. T facilitate ur cmprehensin f the wrld, we build mdels based n cnceptual metaphrs (隐喻) that are familiar t us. In Newtn’s era, we imagined the universe as a clck. In Einstein’s, we uncvered the standard mdel f particle (粒子) physics.
Nw that we are in the infrmatin age, we have new cncepts such as the cmputer, infrmatin prcessing, virtual reality, and simulatin. Unsurprisingly, these new cncepts inspire us t build new mdels f the universe. Mdels are nt the reality, hwever. There is n pint in arguing if the universe is a clck, a set f particles r an utput f cmputatin. All these mdels are tls t deal with the unknwn and t make discveries. And the mre tls we have, the mre effective and insightful we can becme.
It can be imagined that cmparable t the prcess f building previus scientific mdels, develping the “cmputer simulatin” metaphr-based mdel will als be a hugely rewarding exercise.
29. What des the phrase “cntingent n” underlined in Paragraph 2 prbably mean?
A. Accepted by.B. Determined by.C. Awakened by.D. Discvered by.
词句猜测题。根据第二段“If e.mpirical (实证的) experience fails t reveal reality, reasning wn’t reveal reality either since it relies n cncepts and wrds that are cntingent n ur scial, cultural and psychlgical histries. Again, a black bx.(如果经验不能揭示现实，推理也不会揭示现实，因为它依赖于cntingent n我们的社会、文化和心理历史的概念和词语)”可知，句中that引导限制性定语从句，指代先行词cncepts and wrds，且结合常识，概念和词语取决于我们的社会、文化和心理历史，推测划线短语表示“取决于”，与determined by意义相近。故选B项。
【2023北京卷】
What is life? Like mst great questins, this ne is easy t ask but difficult t answer. The reasn is simple: we knw f just ne type f life and it’s challenging t d science with a sample size f ne. The field f artificial life-called ALife fr shrt — is the systematic attempt t spell ut life’s fundamental principles. Many f these practitiners, s-called ALifers, think that smehw making life is the surest way t really understand what life is.
S far n ne has cnvincingly made artificial life. This track recrd makes ALife a ripe target fr criticism, such as declaratins f the field’s dubtful scientific value. Alan Smith, a cmplexity scientist, is tired f such cmplaints. Asking abut “the pint” f ALife might be, well, missing the pint entirely, he says. “The existence f a living system is nt abut the use f anything.” Alan says. “Sme peple ask me, ‘S what’s the wrth f artificial life?’ D yu ever think, ‘What is the wrth f yur grandmther?’”
As much as many ALifers hate emphasizing their research’s applicatins, the attempts t create artificial life culd have practical payffs. Artificial intelligence may be cnsidered ALife’s cusin in that researchers in bth fields are enamred by a cncept called pen-ended evlutin (演化). This is the capacity fr a system t create essentially endless cmplexity, t be a srt f “nvelty generatr”. The nly system knwn t exhibit this is Earth’s bisphere. If the field f ALife manages t reprduce life’s endless “creativity” in sme virtual mdel, thse same principles culd give rise t truly inventive machines.
Cmpared with the develpments f Al, advances in ALife are harder t recgnize. One reasn is that ALife is a field in which the central cncept — life itself — is undefined. The lack f agreement amng ALifers desn’t help either. The result is a diverse line f prjects that each advance alng their unique paths. Fr better r wrse, ALife mirrrs the very subject it studies. Its muddled (混乱的) prgressin is a striking parallel (平行线) t the evlutinary struggles that have shaped Earth bisphere.
Undefined and uncntrlled, ALife drives its fllwers t repurpse ld ideas and generated nvelty. It may be, f curse, that these characteristics aren’t in any way surprising r singular. They may apply universally t all acts f evlutin. Ultimately ALife may be nthing special. But even this dismissal suggests smething：perhaps, just like life itself thrughut the universe, the rise f ALife will prve unavidable.
31．Regarding Alan Smith’s defence f ALife, the authr is .
A．supprtiveB．puzzledC．uncncernedD．dubtful
32．What des the wrd “enamred” underlined in Paragraph 3 mst prbably mean?
A．Shcked.B．Prtected.C．Attracted.D．Challenged.
33．What can we learn frm this passage?
A．ALife hlds the key t human future.B．ALife and AI share a cmmn feature.
C．AI mirrrs the develpments f ALife.D．AI speeds up the prcess f human evlutin.
34．Which wuld be the best title fr the passage?
A．Life Is Undefined. Can AI Be a Way Out?
B．Life Evlves. Can AI Help ALife Evlve, T?
C．Life Is Undefined. Can ALife Be Defined One Day?
D．Life Evlves. Can Attempts t Create ALife Evlve, T?
【2022年北京卷】
Quantum ( 量子 ) cmputers have been n my mind a lt lately. A friend has been sending me articles n hw quantum cmputers might help slve sme f the biggest challenges we face as humans. I’ve als had exchanges with tw quantum-cmputing experts. One is cmputer scientist Chris Jhnsn wh I see as smene wh helps keep the field hnest. The ther is physicist Philip Taylr.
Fr decades, quantum cmputing has been little mre than a labratry curisity. Nw, big tech cmpanies have invested in quantum cmputing, as have many smaller nes. Accrding t Business Weekly, quantum machines culd help us “cure cancer, and even take steps t turn climate change in the ppsite directin.” This is the srt f hype ( 炒作 ) that annys Jhnsn. He wrries that researchers are making prmises they can’t keep. “What’s new,” Jhnsn wrte, “is that millins f dllars are nw ptentially available t quantum cmputing researchers.”
As quantum cmputing attracts mre attentin and funding, researchers may mislead investrs, jurnalists, the public and, wrst f all, themselves abut their wrk’s ptential. If researchers can’t keep their prmises, excitement might give way t dubt, disappintment and anger, Jhnsn warns. Lts f ther technlgies have gne thrugh stages f excitement. But smething abut quantum cmputing makes it especially prne t hype, Jhnsn suggests, perhaps because “‘quantum’ stands fr smething cl yu shuldn’t be able t understand.” And that brings me back t Taylr, wh suggested that I read his bk Q fr Quantum.
After I read the bk, Taylr patiently answered my questins abut it. He als answered my questins abut PyQuantum, the firm he c-funded in 2016. Taylr shares Jhnsn’s cncerns abut hype, but he says thse cncerns d nt apply t PyQuantum.
The cmpany, he says, is clser than any ther firm “by a very large margin ( 幅度 )” t building a “useful” quantum cmputer, ne that “slves an impactful prblem that we wuld nt have been able t slve therwise.” He adds, “Peple will naturally discunt my pinins, but I have spent a lt f time quantitatively cmparing what we are ding with thers.”
Culd PyQuantum really be leading all the cmpetitin “by a wide margin”, as Taylr claims? I dn’t knw. I’m certainly nt ging t advise my friend r anyne else t invest in quantum cmputers. But I trust Taylr, just as I trust Jhnsn.
33. What des the underlined wrd “prne” in Paragraph 3 mst prbably mean?
A. Open.B. Cl.C. Useful.D. Resistant.
【2021北京卷】
Hundreds f scientists, writers and academics sunded a warning t humanity in an pen letter published last December: Plicymakers and the rest f us must engage penly with the risk f glbal cllapse. Researchers in many areas have prjected the widespread cllapse as “a credible scenari(情景) this century”.
A survey f scientists fund that extreme weather events, fd insecurity, and freshwater shrtages might create glbal cllapse. Of curse, if yu are a nn-human species, cllapse is well underway.
The call fr public engagement with the unthinkable is especially germane in this mment f still-uncntrlled pandemic and ecnmic crises in the wrld's mst technlgically advanced natins. Nt very lng ag, it was als unthinkable that a virus wuld shut dwn natins and that safety nets wuld be prven s disastrusly lacking in flexibility.
The internatinal schlars’ warning letter desn't say exactly what cllapse will lk like r when it might happen. Cllapselgy, the study f cllapse, is mre cncerned with identifying trends and with them the dangers f everyday civilizatin. Amng the signatries(签署者) f the warning was Bb Jhnsn, the riginatr f the “eclgical ftprint” cncept, which measures the ttal amunt f envirnmental input needed t maintain a given lifestyle. With the current ftprint f humanity, “it seems that glbal cllapse is certain t happen in sme frm, pssibly within a decade, certainly within this century,” Jhnsn said in an email.
“Only if we discuss the cnsequences f ur biphysical limits,” the December warning letter says, “can we have the hpe t reduce their speed, severity and harm”. And yet messengers f the cming disturbance are likely t be ignred. We all want t hpe things will turn ut fine. As a pet wrte,
Man is a victim f dpe(麻醉品)
In the incurable frm f hpe.
The hundreds f schlars wh signed the letter are intent(执着) n quieting hpe that ignres preparedness. “Let's lk directly int the issue f cllapse,” they say, “and deal with the terrible pssibilities f what we see there t make the best f a trubling future.”
28. What des the underlined wrd “germane” in Paragraph 3 prbably mean?
A. Scientific.B. Credible.
C. Original.D. Relevant.
【2020年北京卷】
Certain frms f AI are indeed becming ubiquitus. Fr example, algrithms (算法) carry ut huge vlumes f trading n ur financial markets, self-driving cars are appearing n city streets, and ur smartphnes are translating frm ne language int anther. These systems are smetimes faster and mre perceptive than we humans are. But s far that is nly true fr the specific tasks fr which the systems have been designed. That is smething that sme AI develpers are nw eager t change.
Sme f tday’s AI pineers want t mve n frm tday’s wrld f “weak” r “narrw” AI, t create “strng” r “full” AI, r what is ften called artificial general intelligence (AGI). In sme respects, tday’s pwerful cmputing machines already make ur brains lk weak. A GI culd, its advcates say, wrk fr us arund the clck, and drawing n all available data, culd suggest slutins t many prblems. DM, a cmpany fcused n the develpment f AGI, has an ambitin t “slve intelligence”. “If we’re successful,” their missin statement reads, “we believe this will be ne f the mst imprtant and widely beneficial scientific advances ever made.”
Since the early days f AI, imaginatin has utpaced what is pssible r even prbable. In 1965, an imaginative mathematician called Irving Gd predicted the eventual creatin f an “ultra-intelligent machine…that can far surpass all the intellectual (智力的) activities f any man, hwever clever.” Gd went n t suggest that “the first ultra-intelligent machine” culd be “the last inventin that man need ever make.”
Fears abut the appearance f bad, pwerful, man-made intelligent machines have been reinfrced (强化) by many wrks f fictin — Mary Shelley’s Frankenstein and the Terminatr film series, fr example. But if AI des eventually prve t be ur dwnfall, it is unlikely t be at the hands f human-shaped frms like these, with recgnisably human mtivatins such as aggressin (敌对行为). Instead, I agree with Oxfrd University philspher Nick Bstrm, wh believes that the heaviest risks frm A GI d nt cme frm a decisin t turn against mankind but rather frm a dgged pursuit f set bjectives at the expense f everything else.
The prmise and danger f true A GI are great. But all f tday’s excited discussin abut these pssibilities presuppses the fact that we will be able t build these systems. And, having spken t many f the wrld’s fremst AI researchers, I believe there is gd reasn t dubt that we will see A GI any time sn, if ever.
42. What des the underlined wrd “ubiquitus” in Paragraph I prbably mean?
A. Enrmus in quantity.B. Changeable daily.
C. Stable in quality.D. Present everywhere.
【最新模考】
【2024·北京海淀·二模】
The idea that aging reduces adults’ ability t imagine, a cmmn theme in children’s literature, is cntradicted by psychlgical research. While children are ften prtrayed as mre imaginative, research indicates that adults nt nly keep this ability but smetimes surpass children in imaginative thinking.
Children are frequently celebrated fr bundless imaginatin. Yet, research reveals that their make-believe games ften center arund realistic scenaris, such as cking and cleaning, as demnstrated in a 2020 study published in Jurnal f Cgnitin and Develpment. Anther study, lasting fr fur decades, als suggests that children are nt naturally mre imaginative than adults; their limitatins result frm a lack f knwledge and expertise t effectively use their imaginative capacity as adults.
Imaginatin may have evlved fr cnsidering alternatives t reality, but we use it mst naturally t explre clse alternatives, like preparing a different meal, rather than far alternatives, like riding n cluds. When we use imaginatin t envisin far alternatives — t innvate r invent — we’re nt digging int an inbrn appreciatin f the extrardinary; we’re using a tl designed t explre the rdinary. When cnsidering alternatives t reality, we fix ur attentin n pssibilities that are physically reasnable, statistically prbable, scially cnventinal and mrally permissible. When tld abut pssibilities that vilate such regularities, we usually deny they culd happen. Generally speaking, ur ideas abut what culd happen are firmly rted in what we expect t happen.
This mindset is als particularly apparent in yung children. In a 2018 study I c-designed with psychlgist Jnathan Phillips, 4-year-lds were asked t help a distressed girl wh disliked ging t schl due t missing her mther. Amng all the slutins given, they perceived the nly pssible slutin was fr her mther t d smething special after schl t ease her cncerns. Unexpected alternatives, such as snapping fingers and making it Saturday, wearing pajamas t schl r lying abut schl being clsed, were all regarded impssible. Frm this, we can cnclude that children’s earliest intuitins (直觉力) abut pssibility cnfuse what culd happen with what shuld happen.
Histrically, the imprbable event f traveling faster than a hrse was cnsidered impssible, as was traveling by air r traveling int space. Befre the arrival f trains and planes, there were gd reasns t think that peple culd travel nly s far and nly s fast. But these reasns were empirical (经验主义的), nt lgical. Imaginatin, n its wn, lumps the imprbable with the impssible, but we can cmbine imaginatin with ther abilities — namely, knwledge and reflectin — t separate the tw. While imaginatin in children ften subjects t expectatin, adults can cntrl their imaginative capacity fr innvatin by integrating it with accumulated knwledge and reflective thinking.
56．The underlined wrd “lumps” in the last paragraph prbably means _________.
A．mixB．matchC．cmpareD．replace
【2024·北京昌平·二模】
In 1992, Edward de Bn argued that “creativity is the mst imprtant human resurce f all.” But might cmputers have the capacity t be creative? Culd artificial intelligence utperfrm us in even the mst human f phenmena? These questins have mved t the frefrnt f sciety with the launch f ChatGPT and DALL-E, tw pwerful deep learning mdels capable f creating art.
Where human creativity cmes frm is a cmplex and heavily-debated tpic. One thery suppses that creativity emerges frm slving prblems in new ways. The game designer Mark Rsewater explains that “if yu use the same neural pathways, yu get t the same answers, and with creativity, that’s nt yur gal.” But studies frm the University f Virginia suggest humans mst default (默认) t slving prblems by building n knwn slutins, restricting riginality. Sme neurscientists prpse anther thery regarding creativity. Research frm the University f Calgary reveals that when being creative, humans dn’t use the same brain regins assciated with thught and prblem-slving, implying that creativity is primarily an uncnscius prcess. Accrding t this thery, the brain slves prblems best when nt directly fcusing n them using the frntal lbe (前额叶) , instead letting the ther parts f the brain take ver.
A．I. cannt currently emulate (仿真) the full cmplexity f the human mind. D these deep learning netwrks even have the required cmpnents that we use when we are creative? Duglas Hfstadter explains hw “emergent phenmena,” such as creativity, crrespnd t cnnectins between levels within mental systems. Similar cnnectins culd exist in artificial neural netwrks, even if the mechanics differ. Fr example, mdern artificial intelligence emplys attentin circuits that may cause it t behave similarly t the frntal lbe where mst f the brain’s fcusing tendencies cme frm.
The emergent nature f creativity pens the dr fr similar tendencies in machines, but they are tuned s carefully t cpy existing ideas that it may nt be enugh fr true riginality. Mr. Rsewater’s thery n creativity suggests that fr A．I. t be creative, it shuld be able t slve prblems in new ways, which is difficult because A．I. is based s heavily n already existing ideas. Alternatively, if creativity is an uncnscius prcess as the University f Calgary research suggests, then it ccurs mstly utside the frntal lbe and may nt exist in machine learning netwrks. Either way, current A．I. prbably lacks the capacity fr genuine creativity and riginality, but it can cmbine existing ideas in interesting ways.
The questin f machine creativity has repercussins in many areas, such as develping law regarding A．I. wrks, cnsidering A．I. submissins in art cntests, and determining the use f ChatGPT as a tl fr schl assignments. Creativity may be, at least fr nw, a unique human quality. Cmputers are nt yet starting revlutinary artistic mvements, but they are already cmbining what exists int smething new, challenging us t lk deeper int ur wn creativity.
67．What des the underlined wrd “repercussins” in Paragraph 5 prbably mean?
A．Influences.B．Objectins.C．Dubts.D．Causes.
【2024·北京西城·二模】
When peple hear “artificial intelligence,” many envisin “big data.” There’s a reasn fr that: sme f the mst imprtant AI breakthrughs in the past decade have relied n enrmus data sets. But AI is nt nly abut large data sets, and research in “small data” appraches has grwn extensively ver the past decade—with s-called transfer learning as an especially prmising example. Als knwn as “fine-tuning,” transfer learning is helpful in settings where yu have little data n the task f interest but abundant data n a related prblem. The way it wrks is that yu first train a mdel using a big data set and then retrain slightly using a smaller data set related t yur specific prblem.
Research in transfer learning appraches has grwn impressively ver the past 10 years. In a new reprt fr Gergetwn University’s Center fr Security and Emerging Technlgy (CSET), we examined current and prjected prgress in scientific research acrss “small data” appraches. Our analysis fund that transfer learning stands ut as a categry that has experienced the mst cnsistent and highest research grwth n average since 2010. This grwth has even utpaced the larger and mre established field f reinfrcement learning, which in recent years has attracted widespread attentin.
Small data appraches such as transfer learning ffer numerus advantages ver mre data-intensive methds. By enabling the use f AI with less data, they can blster prgress in areas where little r n data exist, such as in frecasting natural disasters that ccur relatively rarely r in predicting the risk f disease fr a ppulatin set that des nt have digital health recrds.
Anther way f thinking abut the value f transfer learning is in terms f generalizatin. A recurring challenge in the use f AI is that mdels need t “generalize” beynd their training data. Because transfer learning mdels wrk by transferring knwledge frm ne task t anther, they are very helpful in imprving generalizatin in the new task, even if nly limited data were available.
Mrever, by using pretrained mdels, transfer learning can speed up training time and culd als reduce the amunt f cmputatinal resurces needed t train algrithms (算法). This efficiency is significant, cnsidering that the prcess f training ne large neural (神经系统的) netwrk requires cnsiderable energy.
Despite the grwth in research, transfer learning has received relatively little visibility. The existence f techniques such as transfer learning des nt seem t have reached the awareness f the brader space f plicy makers and business leaders in psitins f making imprtant decisins abut AI funding and adptin. By acknwledging the success f small data techniques like transfer learning—and distributing resurces t supprt their widespread use—we can help vercme sme f the cmmn miscnceptins regarding the rle f data in AI and facilitate innvatin in new directins.
69．What des the underlined wrd “blster” in Paragraph 3 prbably mean?
A．Prmte.B．Seek.
C．Track.D．Mnitr.