對(duì)于外國(guó)的科技和文學(xué)藝術(shù),全盤接受和一概排斥都是錯(cuò)誤的,要神仙中人,這才是正確的態(tài)度。下面小編整理了有關(guān)未來(lái)科技的英語(yǔ)文章，希望大家喜歡!

　　有關(guān)未來(lái)科技的英語(yǔ)文章品析

　　美國(guó)試驗(yàn)讓無(wú)人駕駛汽車用表情包示意

　　A self-driving start-up in Silicon Valley is exploring emojis as a robotic response to the honks,nods, waves and other signals exchanged between human road users.

　　硅谷一家自動(dòng)駕駛初創(chuàng)公司正在探索利用表情符號(hào)自動(dòng)回應(yīng)鳴喇叭、點(diǎn)頭、揮手等人類道路使用者之間交換的信號(hào)。

　　Drive.ai is beginning a test near its Mountain View headquarters of autonomous cars fitted withdigital signage on their roofs.

　　Drive.ai公司正在位于山景城(Mountain View)的總部附近對(duì)車頂裝有數(shù)字顯示屏的自動(dòng)駕駛汽車進(jìn)行測(cè)試。

　　The display, which also incorporates an array of cameras and sensors for navigation, canshow text and pictures, as well as making sounds, to provide cues to human drivers of therobot’s intentions.

　　這種顯示屏還包含一組用于導(dǎo)航的攝像頭及傳感器，它能夠顯示文本和圖片，還可以發(fā)出聲音，以向人類司機(jī)提示無(wú)人車的意圖。

　　If you take the driver out of the equation, how do other human beings communicate with thiscar? A self-driving car needs to emote intention, understand what the other cars are doingand signal to them what it wants to do, said Carol Reiley, co-founder and president of theyear-old company.

　　這家成立僅一年的公司的聯(lián)合創(chuàng)始人、總裁卡蘿爾•賴?yán)?Carol Reiley)表示：如果你的車?yán)餂]有駕駛員，其他人該怎樣與這輛車溝通?自動(dòng)駕駛汽車需要表達(dá)意圖，領(lǐng)會(huì)其他車輛正在做什么并向它們發(fā)出信號(hào)，告知它想做什么。

　　Among the signs being tested are the smiley faces, winks and hand gestures of emoji that havebecome a popular addition to text messaging and social networking in recent years.

　　正在被測(cè)試的信號(hào)包括笑臉、眨眼、手勢(shì)等各種表情符號(hào)，這些表情包近年來(lái)已經(jīng)成為短信與社交網(wǎng)絡(luò)中很流行的附加符號(hào)。

　　We are anticipating that people’s behaviour will be very different around self-driving cars[compared] to normal cars, she said. We aren’t satisfied with the lights and sounds on acurrent car.

　　我們認(rèn)為，相對(duì)普通汽車，人類駕駛員在自動(dòng)駕駛汽車周圍時(shí)的行為將大為不同，她說(shuō)，我們并不滿足于現(xiàn)有汽車的燈光和聲音。

　　We need to design a new kind of robot that can communicate safely and interact with people.

　　我們需要設(shè)計(jì)一種能夠安全地與人類溝通和互動(dòng)的新型機(jī)器人。

　　While most robots in use are in factories, cordoned off behind warning notices, Ms Reiley saidthat a self-driving car would be the first social robot that will be released into the world.

　　雖然大多數(shù)在使用的機(jī)器人都位于工廠且被警戒線隔離在警示告示之后，但賴?yán)硎?，自?dòng)駕駛汽車將成為首個(gè)被投放到真實(shí)世界的社交型機(jī)器人。

　　Drive.ai, which has raised m from undisclosed investors, was founded last year by StanfordUniversity graduates.

　　由斯坦福大學(xué)(Stanford University)幾名畢業(yè)生去年創(chuàng)立的Drive.ai，已從未公開的投資人手中籌集了1200萬(wàn)美元。

　　They had been working to apply deep learning, a strand of artificial intelligence research, todriving.

　　他們一直在致力于將深度學(xué)習(xí)(人工智能研究的一個(gè)分支)應(yīng)用于駕駛。

　　In April, Drive.ai became the 13th company to be approved for autonomous testing in Californiaby the state’s Department of Motor Vehicles .

　　今年4月，Drive.ai成為第13家獲得加州機(jī)動(dòng)車輛管理局(Department of Motor Vehicles)批準(zhǔn)進(jìn)行自動(dòng)駕駛測(cè)試的公司。

　　While others are focused on highway driving, Drive.ai is targeting more crowded and complexurban environments for its first deployments.

　　雖然其他一些公司正專注于高速公路駕駛測(cè)試，但Drive.ai首批測(cè)試的目標(biāo)是更擁擠、更復(fù)雜的城市環(huán)境。

　　經(jīng)典有關(guān)未來(lái)科技的英語(yǔ)文章

　　堵車時(shí) 如何減少車內(nèi)污染

　　The average American commuter spent 50hours in traffic last year.

　　去年，美國(guó)通勤者在路上等待的時(shí)間平均為50小時(shí)。

　　As a nation, we spent eight billion hourssitting in our cars, waiting for lights to change, for the driver ahead tosneak into that parking spot, for an accident to be cleared.

　　全體美國(guó)人總共花了80億小時(shí)坐在車?yán)铮却t燈變綠燈，等待前車司機(jī)駛?cè)胪＼囄唬却煌ㄊ鹿时惶幚怼?/p>

　　That’s not much more timethan many Europeans spend in cars.

　　這并不比許多歐洲人等在車?yán)锏臅r(shí)間多出多少。

　　According to Inrix, a roadway and trafficanalytics company, drivers and passengers in Belgium spent 44 hours in trafficlast year; in Germany, 39 hours.

　　交通路況分析公司Inrix稱，比利時(shí)的司機(jī)和乘客去年等在路上的平均時(shí)間為44小時(shí);德國(guó)人為39小時(shí)。

　　Wherever it happens, new research suggeststhat all that sitting and waiting is exposing us to more pollutants than we’d take in ifwere we cruising along.

　　新研究顯示，不論在什么地方，比起一路暢行無(wú)阻，坐在車?yán)锏却龝?huì)讓我們暴露于更多污染物之下。

　　According to a study published Thursday inEnvironmental Science: Processes & Impacts, pollution levels inside cars atred lights or in traffic jams are up to 40 percent higher than when traffic ismoving.

　　根據(jù)上周四發(fā)表在《環(huán)境科學(xué)：過(guò)程與影響》(Processes & Impacts)上的一項(xiàng)研究，等紅燈或者堵在路上之際，車內(nèi)污染物的含量比交通順暢時(shí)高出40%。

　　Air quality is already a problem outside ofcars: More than 80 percent of people living in cities where pollution istracked are exposed to air quality levels below World Health Organizationlimits.

　　車外的空氣質(zhì)量已經(jīng)成問(wèn)題了：污染水平受到追蹤的那些城市的居民，超過(guò)80%暴露在質(zhì)量未達(dá)世界衛(wèi)生組織(World Health Organization，簡(jiǎn)稱WHO)所設(shè)限值的大氣中。

　　The W.H.O. has estimated that poor air quality isresponsible for the deaths of 3.7 million people younger than 60 in 2012.

　　據(jù)WHO估計(jì)，2012年，糟糕的空氣質(zhì)量是導(dǎo)致370萬(wàn)不滿60歲的人死亡的原因。

　　Researchers at the University of Surrey inEngland took to the streets of Guildford, a typical English town, to look atthe effects of traffic on concentrations of polluting particles.

　　英國(guó)薩里大學(xué)(University of Surrey)的研究人員走上典型英式城鎮(zhèn)吉爾福德的街頭，研究交通堵塞對(duì)顆粒污染物濃度的影響。

　　They also analyzed how ventilation settingschanged those concentrations inside of cars.

　　他們還分析了通風(fēng)設(shè)置會(huì)如何改變車內(nèi)污染濃度。

　　The scientists took their measurementsinside a car as it traveled on a six-kilometer loop, passing through 10 trafficintersections.

　　這些科學(xué)家讓車輛沿一條六公里長(zhǎng)的環(huán)路行駛，途經(jīng)10個(gè)交通路口，同時(shí)在車內(nèi)進(jìn)行測(cè)量。

　　They tracked the concentrations ofdifferent-size particles of air pollution —ranging from courseto fine —at each intersection.

　　他們?cè)诿恳粋€(gè)路口追蹤了從粗到細(xì)不同尺寸的顆粒污染物的濃度。

　　In a car stuck in traffic, shutting all thewindows and turning off the fan or heat reduced concentration doses of thesmallest, most hazardous particles by up to 76 percent.

　　塞車時(shí)，關(guān)閉所有車窗、關(guān)掉風(fēng)扇或暖氣，會(huì)讓車內(nèi)危害性最強(qiáng)的最小顆粒物的濃度降低至多76%。

　　The researchers also found an increase insmaller particles inside the vehicle compared with larger ones when the heatwas off and fans were on full blast, drawing in air from outside.

　　研究人員還發(fā)現(xiàn)，當(dāng)關(guān)閉暖氣并把風(fēng)扇開到最大檔來(lái)吸入外部空氣的時(shí)候，車內(nèi)較小顆粒物的濃度與較大顆粒物相比有所增加。

　　Those findings suggest that the ventilationsystem was more effective at filtering out larger particles than smaller oneswhile stopped at intersections, reducing the concentration doses of thoseparticles up to 68 percent, they said.

　　他們說(shuō)，這些結(jié)果表明，車輛停在路口之際，通風(fēng)系統(tǒng)能夠更有效地過(guò)濾較大顆粒物而非較小顆粒物，讓前者的濃度下降至多68%。

　　And while they were only at trafficintersections for about 7 percent of total commuting time on average, the timeaccounted for as much as 10 percent of their exposure to harmful particles.

　　盡管在路口停留的時(shí)間平均只占總通勤時(shí)間的大約7%，但研究人員在這段時(shí)間里接觸到的有害顆粒物，卻相當(dāng)于總接觸量的10%。

　　The exposure was more than six timesgreater in cars with open windows than for pedestrians at three- or four-wayintersections.

　　在丁字路口或十字路，在窗戶打開的車?yán)锝佑|到的有害顆粒物濃度比行人高六倍多。

　　So when you’re stopped at anintersection, roll up the windows, and breathe easier.

　　因此，停在路口時(shí)，請(qǐng)把窗戶關(guān)上，呼吸也要更輕一點(diǎn)。

　　關(guān)于有關(guān)未來(lái)科技的英語(yǔ)文章

　　《賴以生存的算法》 助你提高效率

　　Can computer scientists — the people who think about the foundations of computing and programming — help us to solve human problems such as having too many things to do, and not enough time in which to do them?

　　計(jì)算機(jī)科學(xué)家們——那些研究計(jì)算機(jī)和編程的原理的人，能否幫助我們解決人類的問(wèn)題，例如，要做的事太多，可用的時(shí)間卻不夠?

　　That’s the premise of Algorithms to Live By, a book by Brian Christian and Tom Griffiths.

　　這是布賴恩•克里斯蒂安(Brian Christian)和湯姆•格里菲思(Tom Griffiths)合著的新書《賴以生存的算法》(Algorithms to Live By)中提出的主張。

　　It’s an appealing idea to any economist.

　　這是對(duì)任何經(jīng)濟(jì)學(xué)家都有吸引力的想法。

　　We tend to think of everyday decisions as a branch of applied mathematics, which is what computer science is.

　　我們傾向于認(rèn)為日常決策是應(yīng)用數(shù)學(xué)的一個(gè)分支，而計(jì)算機(jī)科學(xué)亦是如此。

　　To be clear, using computer science is not the same as using computers.

　　準(zhǔn)確來(lái)說(shuō)，利用計(jì)算機(jī)科學(xué)和使用計(jì)算機(jī)不是一回事。

　　Computer scientists have devoted decades to problems such as sorting information, setting priorities and networking.

　　計(jì)算科學(xué)家傾注了數(shù)十年時(shí)間來(lái)解決各種問(wèn)題，如整理信息、排定優(yōu)先順序和聯(lián)網(wǎng)。

　　Many of the algorithms they have developed for computers can also work for human beings.

　　他們?yōu)橛?jì)算機(jī)開發(fā)的許多算法也適用于人類。

　　An algorithm, after all, is not a computer program. It’s a structured procedure, a kind of recipe.

　　畢竟，算法并非計(jì)算機(jī)程序，而是一種結(jié)構(gòu)化的步驟方法，類似于菜譜。

　　(Algorithms are named after a 9th-century Persian mathematician, Al-Khwārizmī, but they predate his work by thousands of years.)

　　(算法一詞因9世紀(jì)波斯數(shù)學(xué)家花拉子密(Al-Khwārizmī)而得名，但在其研究工作的數(shù)千年前就已存在。)

　　So, what is the optimal recipe for working through the to-do list? Perhaps it is simpler than you think: do all the jobs on the list in any order, as it will take the same amount of time in the end.

　　那么，什么是完成待辦事項(xiàng)列表的最佳配方呢?也許比你以為的更簡(jiǎn)單：以任意順序來(lái)做列表上的事，因?yàn)樽詈蠛馁M(fèi)的總時(shí)長(zhǎng)一樣。

　　There is a touch of brilliance in this advice but it also seems to show that computer science will never shed light on the stress and wheel-spinning that we feel when we have too much to do.

　　這是個(gè)帶有一點(diǎn)兒天才的建議，但似乎表明，當(dāng)我們有太多事情要做而感到壓力和手忙腳亂時(shí)，計(jì)算機(jī)科學(xué)永遠(yuǎn)不能給我們帶來(lái)啟示。

　　Or so I thought.

　　或者說(shuō)我以前是這么認(rèn)為的。

　　Then I read a 1970 paper by the computer scientist Peter Denning, which describes a problem that computers can have when multitasking.

　　接著我讀到計(jì)算機(jī)科學(xué)家彼得•丹寧(Peter Denning)在1970年發(fā)表的一篇論文，文中描述了計(jì)算機(jī)在多線程工作時(shí)可能遇到的一個(gè)問(wèn)題。

　　Most computers do not literally multitask; instead, like humans, they switch rapidly between one thing and another.

　　大多數(shù)計(jì)算機(jī)實(shí)際上無(wú)法真的多線程工作;而是像人類一樣，會(huì)迅速?gòu)囊患虑袚Q到另一件事。

　　A computer will flit between updating your screen with a Pokémon, downloading more videos from the internet, and checking to see if you have clicked the keyboard or moved the mouse, among many other processes.

　　計(jì)算機(jī)會(huì)在以下任務(wù)中快速切換：在你的屏幕上更新口袋妖怪(Pokémon)游戲、從網(wǎng)絡(luò)下載更多視頻、檢查你是否敲擊了鍵盤或挪動(dòng)了鼠標(biāo)，以及其它許多進(jìn)程。

　　But even a computer cannot do an unlimited number of tasks and, at a certain point, disaster can strike.

　　但即使是計(jì)算機(jī)，也不能同時(shí)做無(wú)限量的工作，一旦達(dá)到某一限度，災(zāi)難就會(huì)發(fā)生。

　　The problem stems from the use of readily accessible caches to store data.

　　這一問(wèn)題源于使用易存取的高速緩存(caches)來(lái)儲(chǔ)存數(shù)據(jù)。

　　To understand caches, imagine a pianist playing from two or three sheets of music in front of her.

　　可以這么理解高速緩存：想象有一名鋼琴家在演奏她面前的兩三頁(yè)樂(lè)譜。

　　Those sheets are in the fastest cache.

　　這些樂(lè)譜都是儲(chǔ)存在最高速的緩存中。

　　There are other sheets behind them, accessible in a few moments.

　　樂(lè)譜背后還有其他樂(lè)譜，一會(huì)兒就能讀取。

　　Then there are larger but slower caches: music in the piano stool; more up in the attic, and yet more in a music shop.

　　此外還有容量更大但速度更慢些的緩存：放在琴凳里的樂(lè)譜;閣樓上還有更多樂(lè)譜，再有更多是存放在音樂(lè)商店里。

　　There is a trade-off between the volume of information and the speed with which it can be accessed.

　　在信息儲(chǔ)存量和讀取速度之間存在一種取舍。

　　This set-up is no problem if the pianist only plays one complete piece at a time.

　　如果鋼琴家一次只演奏一首完整的樂(lè)曲，那么這樣的設(shè)置是沒有問(wèn)題的。

　　But if she is asked to switch every minute or so, then some of her time will be taken retrieving a piece of music from the piano stool.

　　但是，如果要求她每隔1分鐘左右換一首曲子，那么她就要花一些時(shí)間來(lái)取出琴凳里樂(lè)譜。

　　If she must change every few seconds, then she will be unable to play a note; all her time will be taken switching sheet music between the stand and the piano stool.

　　如果她必須每隔幾秒就換一首曲子，那她就沒法演奏了;她所有的時(shí)間都會(huì)被用來(lái)調(diào)換譜架上和琴凳里的樂(lè)譜。

　　It is the same with a computer cache: there will be a hierarchy — from super-fast memory in the microprocessor itself all the way down to a hard drive (slow) and offsite back-up (very slow).

　　這跟計(jì)算機(jī)的高速緩存一樣：存在一個(gè)等級(jí)制度——從微處理器自身的超高速內(nèi)存，向下一直到硬盤(慢速)和異地備份(非常慢)。

　　To speed things up, the computer will copy the data it needs for the current task into a fast cache.

　　要想提高速度，計(jì)算機(jī)必須把當(dāng)前任務(wù)所需的數(shù)據(jù)復(fù)制到快速緩存。

　　If the tasks need to be switched too often, the machine will spend all its time copying data for one task into the cache, only to switch tasks, wipe the cache and fill it with something new.

　　如果任務(wù)切換太頻繁，機(jī)器會(huì)把所有時(shí)間用來(lái)將一個(gè)任務(wù)的數(shù)據(jù)復(fù)制到緩存，然后切換任務(wù)、清除緩存并存入新的內(nèi)容。

　　At the limit, nothing will ever be achieved.

　　在極限狀態(tài)下，什么事都完成不了。

　　Denning described this regrettable state of affairs as thrashing.

　　丹寧將這種令人遺憾的狀態(tài)形容為系統(tǒng)崩潰(thrashing)。

　　We’ve all had days filled with nothing but thrashing, constantly switching focus from one task to another but never actually doing anything.

　　我們都有過(guò)除了崩潰以外一事無(wú)成的日子，不斷從一項(xiàng)任務(wù)切換到另一項(xiàng)，實(shí)際上卻什么都做不了。

　　Can we borrow a solution from the computers? The most straightforward solution is to get a bigger cache; that is easier for a computer than for a human, alas.

　　我們能否從計(jì)算機(jī)借鑒解決方案?最直截了當(dāng)?shù)姆椒ㄊ菗Q個(gè)更大的緩存;可惜，這對(duì)計(jì)算機(jī)來(lái)說(shuō)比人類更容易。

　　The obvious alternative is to switch tasks less often.

　　顯而易見的替代方法是減少任務(wù)切換。

　　Computers practice interrupt coalescing, or lumping little tasks together.

　　計(jì)算機(jī)采用中斷合并(interrupt coalescing)技術(shù)，即把多個(gè)小任務(wù)合并到一起處理。

　　A shopping list helps prevent unnecessary return trips to the shop.

　　一份購(gòu)物清單有助于避免多次往返商店的不必要旅程。

　　You can put your bills in a pile and deal with them once a month.

　　你還可以把賬單放在一塊兒，每月一并處理。

　　But we often find it difficult not to flit from one task to another.

　　但我們往往發(fā)現(xiàn)很難不從一個(gè)任務(wù)切換到另一個(gè)。

　　Computer science says there’s a reason for the pain: there is a trade-off between being swiftly responsive and marking out chunks of time to be productive.

　　計(jì)算機(jī)科學(xué)認(rèn)為這種痛苦有一個(gè)原因：即在迅速響應(yīng)和劃出大塊時(shí)間以提高生產(chǎn)率之間存在取舍。

　　If you want to respond to your boss’s emails within five minutes, you must check email at least once every five minutes.

　　如果你想在5分鐘之內(nèi)回復(fù)你老板的郵件，你必須至少每5分鐘查一次郵件。

　　If you want to go off-grid for a week to work on your novel, your response time must slow to a week.

　　如果你想戒網(wǎng)一周來(lái)寫小說(shuō)，那么你的響應(yīng)時(shí)間就必須放慢至一周。

　　Any solution should acknowledge that trade-off.

　　任何解決方案都應(yīng)該承認(rèn)這種取舍。

　　Decide on an acceptable response time and interrupt yourself accordingly.

　　確定一個(gè)可接受的響應(yīng)時(shí)間，然后據(jù)此打斷自己的工作。

　　If you think it’s perfectly fine to answer emails within four hours — fine by most standards — then you only need to check your email once every four hours, not once every four minutes.

　　如果你認(rèn)為在4小時(shí)之內(nèi)回復(fù)郵件完全沒有問(wèn)題(按多數(shù)標(biāo)準(zhǔn)都沒問(wèn)題)，那么你只需要每4個(gè)小時(shí)查一次郵件，而不是每4分鐘查一次。

　　As Christian and Griffiths advise, decide how responsive you want to be.

　　正如克里斯蒂安和格里菲思建議的那樣，決定自己想要如何響應(yīng)。

　　If you want to get things done, be no more responsive than that.

　　如果你想好好做點(diǎn)事情，就別超過(guò)那個(gè)響應(yīng)標(biāo)準(zhǔn)。