A
A. Land Rover approached a Chevy Tahoe estate car that had stopped at a kerb; the Land Rover pulled out and tried to pass the Tahoe just as it started off again. There was a crack of fenders and the sound of paintwork being scraped, the kind of minor mishap that occurs on roads thousands of times every day Normally drivers get out, gesticulate, exchange insurance details and then drive off. But not on this occasion. No one got out of the cars for the simple reason that they had no humans inside them; the Tahoe and Land Rover were being controlled by computers competing in November's DARPA (the U.S. Defence Advanced Research Projects Agency) Urban Challenge.
B
B. The idea that machines could perform to such standards is startling. Driving is a complex task that takes humans a long time to perfect. Yet here, each car had its onboard computer loaded with a digital map and route plans, and was instructed to negotiate busy roads; differentiate between pedestrians and stationary objects; determine whether other vehicles were parked or moving off; and handle various parking manoeuvres, which robots turn out to be unexpectedly adept at. Even more striking was the fact that the collision between the robot Land Rover, built by researchers at the Massachusetts Institute of Technology, and the Tahoe, fitted out by Cornell University Artificial Intelligence (AI) experts, was the only scrape in the entire competition. Yet only three years earlier, at DARPA's previous driverless car race, every robot competitor directed to navigate across a stretch of open desert either crashed or seized up before getting near the finishing line.
C
C. It is a remarkable transition that has clear implications for the car of the future. More importantly, it demonstrates how robotics sciences and Artificial Intelligence have progressed in the past few years a point stressed by Bill Gates, the Microsoft boss who is a convert to these causes. The robotics industry is developing in much the same way the computer business did 30 years ago,' he argues. As he points out, electronics companies make toys that mimic pets and children with increasing sophistication. 'I can envision a future in which robotic devices will become a nearly ubiquitous part of our day-to-day lives,' says Gates. 'We may be on the verge of a new era, when the PC will get up off the desktop and allow us to see, hear, touch and manipulate objects in places where we are not physically present.'
D
D. What is the potential for robots and computers in the near future? The fact is we still have a way to go before real robots catch up with their science fiction counterparts/ Gates says. So what are the stumbling blocks? One key difficulty is getting robots to know their place. This has nothing to do with class or etiquette, but concerns the simple issue of positioning. Humans orient themselves with other objects in a room very easily. Robots find the task almost impossible. 'Even something as simple as telling the difference between an open door and a window can be tricky for a robot,' says Gates. This has, until recently, reduced robots to fairly static and cumbersome roles.
E
E. For a long time, researchers tried to get round the problem by attempting to recreate the visual processing that goes on in the human cortex. However, that challenge has proved to be singularly exacting and complex. So scientists have turned to simpler alternatives: 'We have become far more pragmatic in our work,' says Nello Cristianini, Professor of Artificial Intelligence at the University of Bristol in England and associate editor of the Journal of Artificial Intelligence Research. 'We are no longer trying to recreate human functions. Instead, we are looking for simpler solutions with basic electronic sensors, for example.' This approach is exemplified by vacuuming robots such as the Electrolux Trilobite. The Trilobite scuttles around homes emitting ultrasound signals to create maps of rooms, which are remembered for future cleaning. Technology like this is now changing the face of robotics, says philosopher Ron Chrisley, director of the Centre for Research in Cognitive Science at the University of Sussex in England.
F
F. Last year, a new Hong Kong restaurant, Robot Kitchen, opened with a couple of sensorladen humanoid machines directing customers to their seats. Each possesses a touchscreen on which orders can be keyed in. The robot then returns with the correct dishes. In Japan, University of Tokyo researchers recently unveiled a kitchen 'android' that could wash dishes, pour tea and make a few limited meals. The ultimate aim is to provide robot home helpers for the sick and the elderly, a key concern in a country like Japan where 22 per cent of the population is 65 or older. Over US$1 billion a year is spent on research into robots that will be able to care for the elderly. 'Robots first learn basic competence how to move around a house without bumping into things. Then we can think about teaching them how to interact with humans,' Chrisley said. Machines such as these take researchers into the field of socialised robotics: how to make robots act in a way that does not scare or offend individuals. 'We need to study how robots should approach people, how they should appear. That is going to be a key area for future research,' adds Chrisley.
Nếu chỉ skim/scan từ khoá giống nhau giữa đoạn văn và list of headings, thí sinh rất dễ chọn những heading như:
IV. Examples of robots at work
Thí sinh dễ chọn heading này khi đọc câu cuối “The Tahoe and Land Rover were being controlled by computers” => vì computers là một loại robots nên tưởng đoạn này đưa ra ví dụ robots đang làm việc. Tuy nhiên, cần chú ý rằng heading này ở số nhiều (Examples) => phải đưa ra nhiều công việc khác nhau. Trong khi đó, trong đoạn trên chỉ nói đúng một công việc của robots: lái xe.
III. How robots can save human lives
Một vài thí sinh hay chọn nhầm câu này vì “suy diễn": thấy phần trên bài đọc có đề cập tới tai nạn xe hơi, phần dưới lại nói hai chiếc xe “were controlled by computers" => suy diễn rằng computers cứu mạng con người, trong khi trong bài không hề nói tới việc này.
Linearthinking: 
Để làm đúng Matching Heading, cần áp dụng Linearthinking qua hai bước Simplify + Read Connection
Simplify + Read connection
(1) - (2) Miêu tả một tai nạn xe: Câu 1 giới thiệu 2 chiếc xe, câu 2 nói về tai nạn xảy ra (there was a crack = có tiếng gãy)
(3) Việc thường xảy ra khi có tai nạn
(4) (5) Sự đặc biệt trong vụ tai nạn này: Không hề có humans mà chỉ có computers control cars.
=> Main idea: Sự khác biệt giữa vụ tai nạn này với vụ tai nạn thông thường 