组卷网 > 高中英语综合库 > 主题 > 人与社会 > 科普与现代技术 > 信息技术
题型:阅读理解-阅读单选 难度:0.65 引用次数:221 题号:7367181

Although his 1-year-old smart-phone still works perfectly, Li Jijia already feels the need to replace it. “There are many better ones available now. It's time to upgrade(更新)my phone.”

Li’s impatience is shared by many. Shortly after the season when new products are released(发布,发售), many consumers feel the urge to upgrade their electronic equipment, even though the ones they have still work just fine.

As consumers’ minds are occupied by Apple’s newly- released products and debate whether the Google tablet is better than the new Amazon Kindle, it might be time to take a step back and ask: “Do we really need the latest upgrades?”

According to Donald Norman, an American author, “planned obsolescence (淘汰)” is the trick behind the upgrading culture of today’s consumer electronics industry.

Electronics producers strategically(战略性地) release new upgrades periodically, both for hardware and software, so that customers on every level feel the need to buy the newest version.

“This is an old-time trick---they’re not inventing anything new,” Norman said. “This is a wasteful system through which companies--many of them producing personal electronics-- release poor-quality products simply because they know that, in six months or a year, they’ll put out a new one.”

But the new psychology of consumers is part of this system, as Norman admitted, “We now want something new, something pretty, the next shiny thing.” In its most recent year, Apple's profit margin(利润) was more than 21 percent. At Hewlett-Packard, the world’s biggest PC maker, it was only 7 percent.

Apple’s annual upgrades of its products create sales of millions of units as owners of one year’s MacBook or iPhone line up to buy the newest version(版本), even when the changes are slight.

As to Li Jijia, the need for upgrading his smart-phone comes mainly from friends and classmates. When they are switching to the latest equipment, he worries about feeling left out.

“Some games require better hardware to run,” said Li. “If you don't join in, you lose part of the connection to your friends.”

1. What’s the author’s attitude towards people’s greed for new products?
A.Supportive.B.Satisfied.
C.Critical.D.Unclear.
2. How do the electronics companies successfully promote their latest products?
A.They make a fool of customers by recycling their old products.
B.They make full use of the “planned obsolescence” strategy.
C.They control the customers’ way of thinking while shopping.
D.They invent new products to attract the youth like Li Jijia.
3. Why is Apple Company interested in producing latest version of its product?
A.To provide customers with better service.
B.To defeat other competitors like Hewlett-Packard.
C.To establish a favorable image of itself among its customers.
D.To make huge profits(利润) out of its business.
4. It can be inferred (推断)from the last two paragraphs that Li Jijia feels the need to replace his smart-   phone because of_____.
A.peer pressureB.new psychology
C.life styleD.friends' expectation

相似题推荐

阅读理解-阅读单选(约410词) | 适中 (0.65)
名校

【推荐1】With the coming of big data age, data science is supposed to be starved for, of which the adaption can point a profound change in corporate competitiveness. Companies, both   born-in the digital era and traditional world are showing off their skills in data science. Therefore, it seems to have been creating a great demand for the experts of this type.

Mr Carlos Guestrin, machine learning professor from University of Washington argues that all software applications will need inbuilt intelligence within five years, making data scientists—people trained to analyze large bodies of information — key workers in this emerging “cognitive” technology economy. There are already critical applications that depend on machine learning, a subfield of data science, led by recommendation programs, fraud detection system, forecasting tools and applications for predicting customer behavior.

Many companies that are born digital—particularly internet companies that have a great number of real-time customer interactions to handle—are all-in when it comes to data science. Pinterest, for instance, maintains more than 100 machine learning models that could be applied to different classes of problems, and it constantly fields request from managers eager to use this resource to deal with their business problem.

The most important factor weighing on many traditional companies will be the high cost of launching a serious machine-learning operation. Netflix is estimated to spend $150m a year on a single application and the total bills is probably four times that once all its uses of the technology are taken into account.

Another problem for many non-technology companies is talent.Of the computer science experts who use Kaggle, only about 1000 have deep learning skills, compared to 100,000 who can apply other machine learning techniques, says Mr Goldbloom. He adds that even some big companies of this type are often reluctant to expend their pay scales to hire the top talent in this field.

A third barrier to adapting to the coming era of “smart” applications, however, is likely to be cultural. Some companies, such as General Electric, have been building their own Silicon Valley presence to attract and develop the digital skills they will need.

Despite the obstacles, some many master this difficult transition.But companies that were built, from the beginning, with data science at their center, are likely to represent serious competition.

1. What cannot be inferred from the passage about the machine learning ?
A.Machine learning operations are costly in Netflix.
B.Machine learning plays an important role in existent applications.
C.Machine learning experts are not highly paid in some non-technology companies.
D.Machine learning models are not sufficient to solve business problems in Pinterest.
2. The underlined word in the 3rd paragraph “field” mostly probably means______________.
A.avcids
B.creates
C.solves
D.classifies
3. Which one is the biggest obstacle for many traditional companies to begin a machine-learning operation ?
A.High cost
B.Expert crisis
C.Technological problem
D.Customer interactions
2019-10-31更新 | 78次组卷
阅读理解-阅读单选(约640词) | 适中 (0.65)
名校

【推荐2】The Amazon Echo, a voice-driven cylindrical computer that sits on a table top and answers to the name Alexa, can call up music tracks and radio stations, tell jokes, answer trivia questions and control smart appliances; even before Christmas it was already resident in about 4% of American households. Voice assistants are proliferating in smartphones, too: Apple’s Siri handles over 2bn commands a week, and 20% of Google searches on Android-powered handsets in America are input by voice. Dictating e-mails and text messages now works reliably enough to be useful. Why type when you can talk?

Simple though it may seem, voice has the power to transform computing, by providing a natural means of interaction. Windows, icons and menus, and then touchscreens, were welcomed as more intuitive ways to deal with computers than entering complex keyboard commands. But being able to talk to computers abolishes the need for the abstraction of a “user interface” at all. Just as mobile phones were more than existing phones without wires, and cars were more than carriages without horses, so computers without screens and keyboards have the potential to be more useful, powerful and ubiquitous than people can imagine today.

Voice will not wholly replace other forms of input and output. Sometimes it will remain more convenient to converse with a machine by typing rather than talking (Amazon is said to be working on an Echo device with a built-in screen). But voice is destined to account for a growing share of people’s interactions with the technology around them, from washing machines that tell you how much of the cycle they have left to virtual assistants in corporate call-centres. However, to reach its full potential, the technology requires further breakthroughs—and a resolution of the tricky questions it raises around the trade-off between convenience and privacy.

Computer-dictation systems have been around for years. But they were unreliable and required lengthy training to learn a specific user’s voice. Computers’ new ability to recognise almost anyone’s speech dependably without training is the latest manifestation of the power of “deep learning”, an artificial-intelligence technique in which a software system is trained using millions of examples, usually culled from the internet. Thanks to deep learning, machines now nearly equal humans in transcription accuracy, computerised translation systems are improving rapidly and text-to-speech systems are becoming less robotic and more natural-sounding. Computers are, in short, getting much better at handling natural language in all its forms

Although deep learning means that machines can recognise speech more reliably and talk in a less stilted manner, they still don’t understand the meaning of language. That is the most difficult aspect of the problem and, if voice-driven computing is truly to flourish, one that must be overcome. Computers must be able to understand context in order to maintain a coherent conversation about something, rather than just responding to simple, one-off voice commands, as they mostly do today (“Hey, Siri, set a timer for ten minutes”). Researchers in universities and at companies large and small are working on this very problem, building “bots” that can hold more elaborate conversations about more complex tasks, from retrieving information to advising on mortgages to making travel arrangements.

Many voice-driven devices are always listening, waiting to be activated. Some people are already concerned about the implications of internet-connected microphones listening in every room and from every smartphone. Not all audio is sent to the cloud—devices wait for a trigger phrase (“Alexa”, “OK, Google”, “Hey, Cortana”, or “Hey, Siri”) before they start relaying the user’s voice to the servers that actually handle the requests—but when it comes to storing audio, it is unclear who keeps what and when.

1. According to Paragraph I the American Echo ___
A.has been sold out before Christmas
B.has been used by most American families
C.came out the market later than Apple’s Siri
D.is more useful than smart phones in fictating e-mails
2. What can we infer about the technology of voice computing?
A.It is more effective and convenient than typing
B.It needs to be improved in some important aspects
C.It increases a person’s chances of communicating with others
D.It will replace other forms of input and output in the near future
3. What are some users of voice -driven devices concerned about?
A.The devices will be in charge of theit life
B.The devices need to be activeated before working
C.They are in the dark about their data’s ownership
D.Their voices can be recognized by every smart technology?
4. What’s the author’s attitude towards voice-driven technology?
A.WorriedB.Doubtful
C.SupportiveD.Objective
2020-04-03更新 | 31次组卷
阅读理解-阅读单选(约280词) | 适中 (0.65)

【推荐3】Amazon has announced that it has added features to its Alexa voice assistant that can help users determine their risk level for having got the COVID-19 coronavirus (新型冠状病毒). As of now all Alexa users in the United States can ask Alexa questions like, “Alexa, what do I do if I think I have COVID-19?” or “Alexa, what do I do if I think I have coronavirus?” upon which Alexa will begin triaging (检验分类) them.

Once one of the above questions is asked, Alexa will ask the user about their symptoms, travel history, and any possible exposure they may have had to someone infected with the disease. Depending upon the user’s response, Alexa will offer the user guidance that comes directly from the Centers for Disease Control and Prevention about what they should do next.

Another cool feature added to Alexa is the ability to ask the personal assistant to sing a song for 20 seconds while you wash your hands. Twenty seconds is the minimum washing time with soap and water people need to perform on their hands in order to destroy traces of the virus they may have picked up.

Users can take advantage of Alexa’s new COVID-19 features on any device Alexa runs on, including smartphones, tablets, Kindles, and more. It should also be noted that Amazon isn’t the first to empower its voice assistant to offer CDC COVID-19 information. Earlier this week Apple pushed an update out to Siri that allows users to ask, “Hey Siri, do I have the coronavirus?” and get advice based on CDC information.

1. What is Alexa?
A.It is a robot.B.It is a voice assistant.
C.It is a doctor.D.It is a computer.
2. How does AlexA help people clean their hands thoroughly?
A.It sings a 20-second song while people wash their hands.
B.It can remind you of washing your hands frequently.
C.It can turn on the tap for you when you wash your hands.
D.It can answer questions about washing hands.
3. From the passage, which statement is right?
A.Amazon is the first to empower its voice assistant to offer CDC COVID-19 information.
B.Alexa can only be used at home.
C.Both Alexa and Siri can offer you CDC COVID-19 formation.
D.People like Alexa better than Siri.
4. What can we infer about Alexa according to the passage?
A.Alexa will offer the user treatments directly from their doctors.
B.Alexa makes the judgment by having a medical examination on the user.
C.Once the user uses Alexa, they will be told whether they are infected.
D.Not all the possible exposures to someone infected with the disease will bring the user the disease.
2020-07-01更新 | 74次组卷
共计 平均难度:一般