1 . You are just waking up in the spring of 2030. Your Internet of Things (IoT) bedroom opens solar powered e-windows and plays gentle music while your smart lighting displays a montage (剪辑的) of beachfront sunrises from your recent vacation.
Your shower uses very little water or soap. It recycles your grey water and puts the extra heat back into your home’s operating system. While you dress, your artificial intelligence (Al) assistant shares your schedule for the day and plays your favorite tunes.
You still start your day with a coffee but it comes from your IoT refrigerator which is capable of providing a coffeehouse experience in your home. A hot breakfast tailored to your specific nutritional needs (based on chemical analysis from your trips to the “smart toilet”) is waiting for you in the kitchen.
When it’s time to leave, an on-demand transport system has three cars waiting for you, your wife (or husband) and your kids. On the road, driverless cars and trucks move with mathematical accuracy, without traffic jams, routine maintenance or road rage. Accident rates are near zero.
On the way, you call your R&D team, who are enveloping a day’s work in Shanghai. Your life-sized image is projected (投射) into the China Innovation Centre and your colleagues see you as if you were sitting in the room. It’s a bit strange for them to see you in the morning light because it’s dark on the Bund, Shanghai’s waterfront, though the novelty disappears after a few uses.
You review the day’s cloud- based data from your Shenzhen manufacturing center, your pilot project in San Diego, and your QA team in Melbourne. The large amounts of datasets were collected in real-time from every piece of equipment and have been beautifully summarized by your company’s AI. All these facilities are closely maintained and operated through an advanced predictive analytics platform.
Pleased with the team’s progress, you end the call and ease into a good book.
This is the future and it will be here sooner than you think.
1. How can we describe the life in the future?| A．Virtual | B．Romantic |
| C．Inspiring | D．Intelligent |
| A．We can have a bath without using water. |
| B．We can drive to work without concerning any accidents. |
| C．We can enjoy the coffeehouse experience without going there. |
| D．We can deal with all our work at home without turning to others for help. |
| A．To attract us to use the AI system. |
| B．To introduce the life in the future. |
| C．To teach us how to use the AI system. |
| D．To encourage us to study hard for the future. |
2 . Smart cities are coming. And you can be sure that hackers (黑客) won’t be very far behind. We’ve already gotten a glimpse of that future, as cities across the globe start to use technology to connect their services and people in ways that were science film just a few years ago. They are using sensors to collect data — such as traffic, garbage collecting, and road conditions —and then using that data to deliver services to more people and more efficiently.
But this rush to become a smart city has a major weakness: The more connected a city is, the easier it is to cyber-attacks. Hackers have, in recent years, effectively held cities hostage through ransom ware (赎金器), sometimes damaging critical systems for months at a time. The damage can cost millions to repair, as Baltimore and Atlanta have discovered.
And this is just the beginning. As cities add connectivity to their streetlights, power grids, dams, transit lines and other services, they are adding more targets that are possible to be hacked. What’s more, as additional information on people is collected, officials worry the result —lots of data could attract nation-states or terrorists who could use the data to launch physical and cyber war.
What cyber security lesson can’t be taught in this hack? For example: Don’t open email attachments from unfamiliar sources; don’t click on unrecognized links; don’t leave sensitive information visible on the walls or surfaces of your office.
But let’s just stick to the most important lesson: The information you share on social media can be used to profile and target you, whether that’s by engineering click bait (点击诱饵) aimed at your particular interests, guessing your password based on your birthday or figuring out your schedule and travels so that an intruder can access your home or office.
Wednesday, September 18, 2019 THE WALL STREET JOURNAL.
1. What did people use to think of smart cities?| A．It was the product of science. | B．It was sure to be popular. |
| C．It existed in imagination. | D．It improved people’s life. |
| A．Introduce the harm of hackers. |
| B．Show the danger of a smart city. |
| C．Add some background information. |
| D．Summarize the previous paragraphs. |
| A．It is convenient to provide service. |
| B．It is certain to bring about progress. |
| C．There are actually potential dangers. |
| D．There’s competition in high technology. |
| A．Describe. | B．Protect. | C．Impress. | D．Fund. |
3 . Looking out across the city and on top of the tall buildings before you are cows. Yes, you read that right. Farm animals are eating grass on high-rise urban farms on top of high buildings in London. Elsewhere, off the coast of mainland England, against the background of extremely beautiful White Cliffs of Dover, a wonderful pod (吊舱) structure forms part of floating city. This is how we will live 100 years from now — if a group of UK experts to be believed.
Temporary housing pods, underwater cities and 3D-printed houses will also help reduce the burden of overpopulation and inner city living-space shortages. Building with their own microclimates and cities built in the skies are also among the amazing achievements of future engineering predicted by experts.
But not only today’s architects continue to advance towards the clouds, building higher and higher, as engineering advances allow, but we’ll also be headed deep below ground. Meanwhile, the future will feature city-spanning (跨城市) bridges. Want to travel to Mars quickly? No problem — the experts are predicting spaceports (宇航基地) will become common places, so future generations will be able to head over to their local station and hitch (搭顺风车) the next ride.
The predictions were heavily focused on water - based architecture and present problems such as overpopulation, global warming and rising sea levels. Using the future tech predictions, 2,000 people were then surveyed to see which of the suggestions they thought — and hoped — would become a reality by 2115. Topping the survey was super-deep basement buildings complete with hotels, restaurants, green space, swimming pools and gyms. The survey also found that one in three respondents (调查对象) considered floating sea cities — which could use solar and tidal (潮汐的) energy — as a choice for future development.
1. The first paragraph is meant to ______.| A．present the topic | B．make a comment |
| C．give an example | D．draw a conclusion |
| A．different kinds of building structures. |
| B．recent development of building structures. |
| C．means to control the increase of population. |
| D．future building structures helping to solve the lack of living space. |
| A．air station | B．traveling agency |
| C．spaceport | D．traveling destination |
| A．City-spanning bridges | B．Deep underground buildings |
| C．Floating sea cities | D．slightly-deep basements |
4 . In the Hollywood movie The Martian, actor Matt Damon plays an astronaut who grows food on Mars(火星)to survive alone on the red planet.
After seeing the movie, Washington State University physicist Michael Allen and University of Idaho food scientist Helen Joyner decided to carry out a case study helping students figure out how to farm on Mars. In the case study, students have to imagine they are mining(采矿) on Mars and decide how to feed themselves there before starting on the journey. They get advice from Allen and Joyner on how to select crops and take the challenges of growing crops over long periods on Mars. Students use a scoring system to select three foods to plant on Mars.
Allen found the results impressive: among 30 students, “no two people have ever gotten the same answer”, he said.
Human travelers to Mars will likely have to make use of resources on the planet rather than take everything they need with them on a spaceship. This means farming their own food on another planet, one that has a very different ecosystem (生态系统) from Earth’s.
One challenge for those who would like to live on Mars is the fact that there can be no farming tools. Like real astronauts, students taking part in the study cannot take a lot of farming tools with them. As Joyner put it to his student astronauts, “You are starting with nothing.”
Besides, students also have to deal with a very limited choice of diet. “If I had to eat a single food for the rest of my life, could I do it?” Joyner asked.
But Allen believes the case study is about more than farming and eating on the Red Planet.
“I’m not teaching about growing food on Mars,” Allen said. “I’m teaching about living with choices. I’m teaching about problem solving.”
1. In the case study, students have to __________.| A．watch the movie to know the conditions on Mars |
| B．decide which crop to grow on Mars with the help of the teachers |
| C．design different types of diets on Mars for them to choose |
| D．understand how to farm on Mars with their favorite farming tools |
| A．increases students’ knowledge about farming |
| B．helps student know more about Mars |
| C．develops students’ skills of solving problems |
| D．teaches students how to make proper choices |
| A．to describe a research on how to farm on Mars |
| B．to prepare us to deal with problems on Mars |
| C．to teach us how to survive on Mars alone |
| D．to introduce a Hollywood movie, The Martian |
5 . Several recent studies examined how machine automation and artificial intelligence (AI) will change the future of work.
Some people predict these technologies could replace up to 30 percent of workers worldwide by 2030. The possibility of being replaced will greatly increase for workers with less education, said Price Waterhouse Coopers, an international company providing financial and tax services. It estimated(估计) that in Britain, up to 46 percent of workers without a college degree could be in danger because of automation. This would drop to about 12 percent for workers with undergraduate degrees or higher.
“New smart machines have the hidden power to replace our minds and to move around freely in the world,” the study said. It added that the greatest job replacement is expected to come in the areas of transportation, storage, manufacturing (制造业)and retail（零售）.
The Rand Corporation recently published its own report on the future effects of automation and AI on jobs and the workplace. Osonde Osoba was a co-author of the report. He noticed that fears over machines taking jobs from humans goes back centuries. He agrees there will be major job disruptions(混乱) because of AI and automation, especially for lower skilled workers. But he believes the future problems have been overestimated(高估) without historical evidence to support the predictions. “It’s not so much that the jobs are getting replaced, but it’s more like tasks are getting replaced and jobs are reconfiguring(重新装备) over time to account for that automation.” He added that it will be very difficult for companies to completely automate most jobs, because they request a worker to perform many different duties and to respond to unexpected situations.
“If you are thinking about detailed things an individual(个人) might do to prepare themselves, I guess being more adaptable and being able to reeducate yourself to fit into a different job.” Osonde Osoba suggests.
1. According to the whole passage, _________are most likely to lose their job?| A．scientists in laboratories | B．teachers in colleges and universities |
| C．milkmen in milk companies | D．officers in governments |
| A．Companies have completely automated most jobs for saving cost. |
| B．Humans have feared to be replaced by AI and automation. |
| C．The job replacement has come in transportation and retail. |
| D．People with high degrees get higher danger of losing jobs than those with no college degree. |
| A．Future workers: what to do to keep the job. |
| B．Job replacement: who is to blame. |
| C．Automation and AI: how to replace the future job. |
| D．New studies: why the future job is replaced. |
