1 . According to a recent study in the Journal of Consumer Research, both the size and consumption habits of our eating companions can influence our food intake. And contrary to existing research that says you should avoid eating with heavier people who order large portions(份), it's the beanpoles with big appetites you really need to avoid.
To test the effect of social influence on eating habits, the researchers conducted two experiments. In the first, 95 undergraduate women were individually invited into a lab to ostensibly(表面上)participate in a study about movie viewership. Before the film began, each woman was asked to help herself to a snack. An actor hired by the researchers grabbed her food first. In her natural state, the actor weighed 105 pounds. But in half the cases she wore a specially designed fat suit which increased her weight to 180 pounds.
Both the fat and thin versions of the actor took a large amount of food. The participants followed suit, taking more food than they normally would have. However, they took significantly more when the actor was thin.
For the second test, in one case the thin actor took two pieces of candy from the snack bowls. In the other case, she took 30 pieces. The results were similar to the first test: the participants followed suit but took significantly more candy when the thin actor took 30 pieces.
The tests show that the social environment is extremely influential when we're making decisions. If this fellow participant is going to eat more, so will I. Call it the “I’ll have what she's having” effect. However, we'll adjust the influence. If an overweight person is having a large portion, I'll hold back a bit because I see the results of his eating habits. But if a thin person eats a lot, I'll follow suit. If he can eat much and keep slim, why can't I?
1. What is the recent study mainly about?| A．Food safety. | B．Movie viewership. |
| C．Consumer demand. | D．Eating behavior. |
| A．Big eaters. | B．Overweight persons. |
| C．Picky eaters. | D．Tall thin persons. |
| A．To see how she would affect the participants. |
| B．To test if the participants could recognize her. |
| C．To find out what she would do in the two tests. |
| D．To study why she could keep her weight down. |
| A．How hungry we are. | B．How slim we want to be. |
| C．How we perceive others. | D．How we feel about the food. |
2 . When you were trying to figure out what to buy for the environmentalist on your holiday list, fur probably didn’t cross your mind. But some ecologists and fashion (时装)enthusiasts are trying to bring back the market for fur made from nutria(海狸鼠).
Unusual fashion shows in New Orleans and Brooklyn have showcased nutria fur made into clothes in different styles. “It sounds crazy to talk about guilt-free fur-unless you understand that the nutria are destroying vast wetlands every year”, says Cree McCree, project director of Righteous Fur.
Scientists in Louisiana were so concerned that they decided to pay hunters $5 a tail. Some of the fur ends up in the fashion shows like the one in Brooklyn last month.
Nutria were brought there from Argentina by fur farmers and let go into the wild. “The ecosystem down there can’t handle this non-native species(物种).It’s destroying the environment. It’s them or us.” says Michael Massimi, an expert in this field.
The fur trade kept nutria in check for decades，but when the market for nutria collapsed in the late 1980s，the cat-sized animals multiplied like crazy.
Biologist Edmond Mouton runs the nutria control program for Louisiana. He says it’s not easy to convince people that nutria fur is green, but he has no doubt about it. Hunters bring in more than 300,000 nutria tails a year, so part of Mouton’s job these days is trying to promote fur.
Then there’s Righteous Fur and its unusual fashion. Model Paige Morgan says，”To give people a guilt-free option that they can wear without someone throwing paint on them-I think that’s going to be a massive thing, at least here in New York.” Designer Jennifer Anderson admits it took her a while to come around to the opinion that using nutria fur for her creations is morally acceptable. She is trying to come up with a label to attach to nutria fashions to show it is eco-friendly.
1. What is the purpose of the fashion shows in New Orleans and Brooklyn?| A．To promote guilt-free fur. |
| B．To expand the fashion market. |
| C．To introduce a new brand. |
| D．To celebrate a winter holiday. |
| A．Nutria damage the ecosystem seriously. |
| B．Nutria are an endangered species. |
| C．Nutria hurt local cat-sized animals. |
| D．Nutria are illegally hunted. |
| A．Boomed. | B．Became mature. | C．Remained stable. | D．Crashed. |
| A．It’s formal. | B．It’s risky. | C．It’s harmful. | D．It’s traditional. |
3 . Certain forms of AI are indeed becoming ubiquitous. For example, algorithms (算法) carry out huge volumes of trading on our financial markets, self-driving cars are appearing on city streets, and our smartphones are translating from one language into another. These systems are sometimes faster and more perceptive than we humans are. But so far that is only true for the specific tasks for which the systems have been designed. That is something that some AI developers are now eager to change.
Some of today’s AI pioneers want to move on from today’s world of “weak” or “narrow” AI, to create “strong” or “full” AI, or what is often called artificial general intelligence (AGI). In some respects, today’s powerful computing machines already make our brains look weak. AGI could, its advocates say, work for us around the clock, and drawing on all available data, could suggest solutions to many problems. DM, a company focused on the development of AGI, has an ambition to “solve intelligence”. “If we’re successful,” their mission statement reads, “we believe this will be one of the most important and widely beneficial scientific advances ever made.”
Since the early days of AI, imagination has outpaced what is possible or even probable. In 1965, an imaginative mathematician called Irving Good predicted the eventual creation of an “ultra-intelligent machine…that can far surpass all the intellectual (智力的) activities of any man, however clever.” Good went on to suggest that “the first ultra-intelligent machine” could be “the last invention that man need ever make.”
Fears about the appearance of bad, powerful, man-made intelligent machines have been reinforced (强化) by many works of fiction — Mary Shelley’s Frankenstein and the Terminator film series, for example. But if AI does eventually prove to be our downfall, it is unlikely to be at the hands of human-shaped forms like these, with recognisably human motivations such as aggression (敌对行为). Instead, I agree with Oxford University philosopher Nick Bostrom, who believes that the heaviest risks from AGI do not come from a decision to turn against mankind but rather from a dogged pursuit of set objectives at the expense of everything else.
The promise and danger of true AGI are great. But all of today’s excited discussion about these possibilities presupposes the fact that we will be able to build these systems. And, having spoken to many of the world’s foremost AI researchers, I believe there is good reason to doubt that we will see AGI any time soon, if ever.
1. What does the underlined word “ubiquitous” in Paragraph I probably mean?| A．Enormous in quantity. | B．Changeable daily. |
| C．Stable in quality. | D．Present everywhere. |
| A．Help to tackle problems. | B．Make brains more active. |
| C．Benefit ambitious people. | D．Set up powerful databases. |
| A．supportive | B．disapproving |
| C．fearful | D．uncertain |
| A．It may be only a dream. |
| B．It will come into being soon. |
| C．It will be controlled by humans. |
| D．It may be more dangerous than ever. |
4 . Elizabeth Spelke, a cognitive (认知的) psychologist at Harvard, has spent her career testing the world's most complex learning system-the mind of a baby. Babies might seem like no match for artificial intelligence (AI). They are terrible at labeling images, hopeless at mining text, and awful at video games. Then again, babies can do things beyond the reach of any AI. By just a few months old, they’ve begun to grasp the foundations of language, such as grammar. They’ve started to understand how to adapt to unfamiliar situations.
Yet even experts like Spelke don’t understand precisely how babies — or adults, for that matter — learn. That gap points to a puzzle at the heart of modern artificial intelligence: We're not sure what to aim for.
Consider one of the most impressive examples of AI, Alpha Zero, a programme that plays board games with superhuman skill. After playing thousands of games against itself at a super speed, and learning from winning positions, Alpha Zero independently discovered several famous chess strategies and even invented new ones. It certainly seems like a machine eclipsing human cognitive abilities. But Alpha Zero needs to play millions more games than a person during practice to learn a game. Most importantly, it cannot take what it has learned from the game and apply it to another area.
To some AI experts, that calls for a new approach. In a November research paper, Francois Chollet, a well-known AI engineer, argued that it’s misguided to measure machine intelligence just according to its skills at specific tasks. “Humans don’t start out with skills; they start out with a broad ability to acquire new skills,” he says. “What a strong human chess player is demonstrating is not only the ability to play chess, but the potential to fulfill any task of a similar difficulty.” Chollet posed a set of problems, each of which requires an AI programme to arrange colored squares on a grid (格栅) based on just a few prior examples. It’s not hard for a person. But modern machine-learning programmes-trained on huge amounts of data — cannot learn from so few examples.
Josh Tenenbaum, a professor in MIT's Center for Brains, Minds & Machines, works closely with Spelke and uses insights from cognitive science as inspiration for his programmes. He says much of modern AI misses the bigger picture, comparing it to a cartoon about a two-dimensional world populated by simple geometrical (几何形的) people. AI programmes will need to learn in new ways — for example, by drawing causal inferences rather than simply finding patterns. “At some point — you know, if you’re intelligent — you realize maybe there's something else out there,” he says.
1. Compared to an advanced AI programme, a baby might be better at _______________.| A．labeling images | B．identifying locations |
| C．playing games | D．making adjustments |
| A．Stimulating. | B．Measuring. | C．Beating. | D．Limiting. |
| A．AI is good at finding similar patterns |
| B．AI should gain abilities with less training |
| C．AI lacks the ability of generalizing a skill |
| D．AI will match humans in cognitive ability |
| A．What is exactly intelligence? |
| B．Why is modern AI advanced? |
| C．Where is human intelligence going? |
| D．How do humans tackle the challenge of AI? |
5 . A robot with a sense of touch may one day feel “pain”, both its own physical pain and sympathy for the pain of its human companions. Such touchy-feely robots are still far off, but advances in robotic touch-sensing are bringing that possibility closer to reality.
Sensors set in soft, artificial skin that can detect both a gentle touch and a painful strike have been hooked up to a robot that can then signal emotions, Asada reported February 15 at the annual meeting of the American Association for the Advancement of Science. This artificial “pain nervous system,” as Asada calls it, may be a small building block for a machine that could ultimately experience pain. Such a feeling might also allow a robot to “sympathize” with a human companion’s suffering.
Asada, an engineer at Osaka University, and his colleagues have designed touch sensors that reliably pick up a range of touches. In a robot system named Affetto, a realistic looking child’s head, these touch and pain signals can be converted to emotional facial expressions.
A touch-sensitive, soft material, as opposed to a rigid metal surface, allows richer interactions between a machine and the world, says neuroscientist Kingson Man of the University of Southern California. Artificial skin “allows the possibility of engagement in truly intelligent ways”.
Such a system, Asada says, might ultimately lead to robots that can recognize the pain of others, a valuable skill for robots designed to help care for people in need, the elderly, for instance.
But there is an important distinction between a robot that responds in a predictable way to a painful strike and a robot that’s able to compute an internal feeling accurately, says Damasio, a neuroscientist also at the University of Southern California. A robot with sensors that can detect touch and pain is “along the lines of having a robot, for example, that smiles when you talk to it,” Damasio says. ‘It’s a device for communication of the machine to a human.” While that’s an interesting development, “it’s not the same thing” as a robot designed to compute some sort of internal experience, he says.
1. What do we know about the “pain nervous system”?| A．It is named Affetto by scientists. | B．It is a set of complicated sensors. |
| C．It is able to signal different emotions. | D．It combines sensors and artificial skin. |
| A．Delivered. | B．Translated. | C．Attached. | D．Adapted. |
| A．Robots can smile when talked to. |
| B．Robots can talk to human beings. |
| C．Robots can compute internal feelings |
| D．Robots can detect pains and respond accordingly. |
| A．Machines Become Emotional | B．Robots Inch to Feeling Pain |
| C．Human Feelings Can Be Felt | D．New Devices Touch Your Heart |
6 . According to a new study， teens focus on rewards and have a hard time learning to avoid punishment or consider the consequences of alternative actions.
University College London researchers compared how teens and adults learn to make choices based on the available information. They tracked the way in which 18 volunteers aged 12-17 and 20 volunteers aged 18-32 completed tasks in which they had to choose between abstract symbols.
Each symbol was consistently associated with a fixed chance of a reward, punishment, or no outcome. As the trial progressed ， participants learned which symbols were likely to lead to each outcome and adjusted their choices accordingly. Teens and adults were equally good at learning to choose symbols associated with reward， but teens were less good at avoiding symbols associated with punishment. Adults also performed significantly better when they were told what would have happened if they had chosen the other symbol after each choice， while teens did not appear to take this information into account.
“From this experimental lab study we can draw conclusions about learning during the teen years. We find that teens and adults learn in different ways， something that might be relevant to education," said lead author Dr. Stefano Palminteri. " Unlike adults, teens are not so good at learning to adjust their choices to avoid punishment. This suggests that incentive systems based on reward rather than punishment may be more effective for this age group. Additionally, we found that teens did not learn from being shown what would have happened if they made alternative choices."
To interpret the results, the researchers developed computational models of learning and ran simulations （模拟）applying them to the results of the study. The first was a simple model, one that learned from rewards, and the second model added to this by also learning from the option that was not chosen. The third model was the most complete and took the full context into account, with equal weight given to punishment avoidance and reward seeking. For example, obtaining no outcome rather than losing a point is weighted equally to gaining a point rather than having no outcome.
Comparing the experimental data to the models, the team found that teens" behavior followed the simple reward-based model while adults" behavior matched the complete, contextual model. “Our study suggests that teens are more receptive to rewards than they are to punishments of equal value, ” said senior author Dr. Sarah-Jayne Blakemore. “As a result, it may be useful for parents and teachers to frame things in more positive terms.”
1. It can be learned from the study that .| A．adults made choices faster than teens |
| B．adults understood rewards better than teens |
| C．teens reacted better to reward than punishment |
| D．teens were aware of the outcome of each choice |
| A．They reflected people’s strong desire for punishment avoidance. |
| B．They gave circumstances different degrees of consideration. |
| C．They paid equal attention to reward and punishment. |
| D．They shaped the behavior of people at different ages. |
| A．accustomed | B．opposed |
| C．sympathetic | D．responsive |
| A．“If you insist on doing things in this way， you will lose ten points. " |
| B．“If we had talked about this earlier， you wouldn’t have made the mistake. " |
| C．“ If you hand in your assignment ahead of time， you will get an extra bonus." |
| D．“If you want to approach a problem differently ， you can talk to your parents. " |
7 . As the effects of climate change become more disastrous, well-known research institutions and government agencies are focusing new money and attention on an idea: artificially cooling the planet, in the hopes of buying humanity more time to cut greenhouse gas emissions.
That strategy, called solar climate intervention (干预) or solar geoengineering, involves reflecting more of the sun’s energy back into space — abruptly reducing global temperatures in a way that imitates the effects of ash clouds flowing out from the volcanic eruptions. The idea has been considered as a dangerous and fancied solution, one that would encourage people to keep burning fossil fuels while exposing the planet to unexpected and potentially threatening side effects, producing more destructive hurricanes, wildfires floods and other disasters.
But. as global warming continues, producing more destructive hurricanes, wildfires floods and other disasters, some researchers and policy experts say that concerns about geoengineering should be outweighed by the imperative to better understand it, in case the consequence of climate change become so terrible that the world can’t wait for better solutions.
One way to cool the earth is by injecting aerosols (气溶胶) into the upper layer of the atmosphere. where those particles reflect sunlight away from the earth. That process works, according to Douglas MacMartin, a researcher at Cornell University.
“We know with 100% certainty that we can cool the planet,” he said in an interview. What’s still unclear, he added, is what happens next. Temperature, MacMartin said, is an indicator for a lot of climate effects. “What does it do to the strength of hurricanes?” he asked, “What does it do to agriculture production? What does it do to the risk of forest fires?”
Another institution funded by the National Science Foundation will analyze hundreds of simulations of aerosol injection, testing the effects on weather extremes around the world. One goal of the research is to look for a sweet spot: the amount of artificial cooling that can reduce extreme weather events without causing broader changes in regional rainfall patterns or similar impacts.
1. Why do researchers and government agencies work on cooling the earth?| A．To prevent natural disasters. | B．To win more time to reduce gas emissions. |
| C．To imitate volcanic eruptions. | D．To encourage more people to bur fossil fuels. |
| A．More volcanoes will throw out. |
| B．More solar energy will go into space. |
| C．More disasters will endanger the future of the world. |
| D．People will keep burning fossil fuels to keep warm. |
| A．He thinks more research remains to be done. |
| B．He is optimistic about the effect of cooling the earth. |
| C．He is concerned about the reduction in agriculture production. |
| D．He disapproves of the practice of solar climate intervention. |
| A．The rainfall pattern of a region. |
| B．The modest drop in temperature. |
| C．The number of extreme weather events. |
| D．The injection amount of aerosol. |
8 . In the magnificent range of mountains of northern California, 42 radio telescopes point towards the stars, scanning for signs of life. The Search for Extraterrestrial Intelligence （SETI） Institute has been listening for a signal here since it was founded in 1984. Jill Tarter, its co — founder, says the programmed aim is not just to communicate with remote civilisations. It is also to remind human beings of its own modest, fragile （脆弱的）place in the universe. Thus, for the first time, SETI is cocking its ear towards Earth to look for a signal that can be sent into space to represent the species.
Felipe Perez Santiago, a Mexican musician and composer, has an idea of what might work.Since songs, like the human voices, are common to all languages and nations, he and Ms. Tarter have designed the “Earthling Project”-a call to people everywhere to upload extracts （精华）of song that he plans to melt into a collective human chorus. An initial composition will be launched into space this summer, recorded on a virtually indestructible disk. Future plans and dreams include an eventual landing on Mars.
Human music has been sent to the heavens in 1977. Distant beings can in theory already enjoy Peruvian panpipes, a Navajo chant, Bach, Beethoven and more. But no previous offering, and perhaps no composition undertaken anywhere, has tried to encompass the entire diversity of human song.
Mr. Santiago says he is thrilled about bringing together contributors from around the globe. Unlike other recordings sent into space, says Mr. Santiago, “Everyone's invited. You don't have to be one of the main composers of our history like Beethoven, just someone singing in their shower.” Download the “Earthling Project" app, sing up to three songs of 30 seconds each, and your voice will be sent into the sky.
1. Why does SETI look for a signal to be sent into space?| A．To stand for species on the earth. |
| B．To scan for other liveable planets. |
| C．To respond to the call of the universe. |
| D．To stress the importance of the earth. |
| A．It is a world music organization. |
| B．It intends to create a human chorus. |
| C．It tries to develop a universal language. |
| D．It aims to search for signals from space. |
| A．Include. | B．Appreciate. |
| C．Work out. | D．Relate to. |
| A．To inspire people to become composers. |
| B．To call on people to protect our planet. |
| C．To encourage people to explore space. |
| D．To invite people to join a programme. |
9 . If your in-box is currently reporting unread messages in the hundreds or thousands, you might have a hard time believing the news: e-mail is on the decline.
At first thought, that might seem to be the case. The incoming generation, after all, doesn’t do e-mail. Oh, they might have an account. They use it only as we would use a fax machine: as a means to communicate with old-school folks like their parents or to fulfill the sign-up requirements of Web sites. They rarely check it, though.
Today’s instant electronic memos — such as texting and Facebook and Twitter messages — are more direct, more concentrated, more efficient. They go without the salutation (称呼语) and the signoff (签收); we already know the “to” and “from.” Many corporations are moving to messaging networks for exactly that reason: more signal, less noise and less time. This trend is further evidence that store-and-forward systems such as e-mail and voicemail are outdated. Instead of my leaving you a lengthy message that you pick up later, I can now send you an easily-read message that you can read — and respond to — on the go.
The coming of the mobile era is responsible for the decline of e-mail. Instant written messages bring great convince to people. They can deal with them at about any time: before a movie, in a taxi, waiting for lunch. And because these messages are very brief, they’re suitable for smart phone typing.
Does this mean e-mail is on its way to the dustbin of digital history? Not necessarily. E-mail still has certain advantages. On the other hand, tweets and texts feel ephemeral — you read them, then they’re gone, into an endless string, e-mail still feels like something you have and that you can file, search and return to later. It’s easy to imagine that it will continue to feel more appropriate for formal communications: agreements, important news, longer explanations.
So, e-mail won’t go away completely. Remember, we’ve been through a transition (过度) like this not so long ago: when e-mail was on the rise, people said that postal mail was dead. That’s not how it works. Postal mail found its smaller market, and so will e-mail. New technology rarely replaces old one completely; it just adds new alternatives.
1. What would the incoming generation like to do with their e-mail accounts?| A．Check bank accounts. | B．Send long messages. |
| C．Fill in some forms. | D．Communicate with their colleagues. |
| A．The possible reasons behind the decline of e-mail |
| B．The likes and dislikes of the young generation |
| C．The rapid development of e-communication channels |
| D．Evidence about the uncertain future of easily-consumed messages |
| A．Automatically-sending. | B．Randomly-written. |
| C．Hardly- recognized. | D．Shortly-appearing. |
| A．It’s too early to determine the decline of e-mail. |
| B．E-mail has reasons to exist with its own advantages. |
| C．E-mail, just like postal mail has come to its end. |
| D．We should feel sorry for the decline of e-mail. |
10 . JeffBezos has a rule at Amazon, or perhaps more appropriate a philosophy. If a team cannot be fed by two pizzas then that team is too large. The reasoning is quite straightforward and basic. More people means more communication, more bureaucracy, more chaos, and more of pretty much everything that slows things down, hence why large organizations are oftentimes considered as being so inefficient.
In 2013 Gallup released a report called “The State of The American Workplace", in which they found that smaller companies had more engaged employees. In fact,42% of employees working at companies of 10 or fewer were engaged at work versus only 30% of employees at large companies.
Most people are not familiar with the Ringelmann Effect which is the tendency for individual members to become less productive as the size of a group increases. This concept was named after Maximilien Ringelmann, a French professor of agricultural engineering who passed away in 1931.In one of his experiments he asked volunteers to perform a very simple task, to pull on a rope. He found that when only one person is pulling on the rope they give 100% of their effort; however, as more people are added the individual effort goes down.
This experiment was recreated in the 1970's by Alan Ingham who came up with the concept of “social loafing” which helps us understand why the individual effort decreases as the team size increases. So why does this happen? Because it becomes harder to extract the individual contributions and performance of each person.
Organizations should really think about what their team structures look like and create and follow similar “two pizza rules”. It's no coincidence that smaller organizations are oftentimes more nimble while large organizations look like they are stuck in the mud.
1. What is the author's purpose of mentioning “two pizza rules” in paragraph 1?| A．To make a comment. |
| B．To introduce the topic. |
| C．To provide an example. |
| D．To analyze a phenomenon. |
| A．It repeated the Ringelmann Effect experiment. |
| B．It was based on a simple task of pulling a rope. |
| C．It aimed to explore the reason behind the phenomenon. |
| D．It revealed the link between team size and individual effort. |
| A．Balanced. |
| B．Complicated. |
| C．Simple. |
| D．Flexible. |
| A．What Makes a Team More Productive? |
| B．Why Are Smaller Teams Better Than Larger Ones? |
| C．How Can Two Pizzas Be Shared by One Team? |
| D．Which Is More Important: Individual Effort r Team Size? |
