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LPE006 Reading Comprehension

Section 3: Reading Comprehension


Questions 1 – 6: Choose the best multiple-choice answer for each question.
1
The Selfish Giant

Every afternoon, as they were coming from school, the children used to go and play in the Giant's garden.

It was a large lovely garden, with soft green grass. Here and there over the grass stood beautiful flowers like stars, and there were twelve peach-trees that in the spring-time broke out into delicate blossoms of pink and pearl, and in the autumn bore rich fruit. The birds sat on the trees and sang so sweetly that the children used to stop their games in order to listen to them. "How happy we are here!" they cried to each other.

(Excerpt from ‘The Selfish Giant’, Oscar Wilde, 1888)

What can be inferred about the children's feelings towards the giant's garden?

They disliked the garden and didn't want to play there.
They found the garden to be small and unattractive.
They enjoyed spending time in the garden and felt happy there.
They were scared of the giant and avoided going near the garden.
2
Where There's Smoke

A look at what we know and don't know about how growing wildfires impact our natural world, and how we can learn to cope.

Fire has shaped the natural history of Southern California for thousands of years, and the legacy of those cyclical burnings is recorded in museum collections. NHMLAC researchers use those collections—from fossilized pollen to the feathers of bird specimens and community science observations—to help us understand how fire shaped the region’s past, and how the terrible growth of these blazes threaten our future.

For the first story in our new series on wildfires, we checked in with museum experts to see how wildfires impact the organisms they study. They are examining this disastrous trend through the lens of natural history and other perspectives to understand how people can plan for—and benefit from—environmental restoration and recovery and what we humans need to do to collectively to bring our planet’s temperature down.

(Excerpt from ‘Where There's Smoke’, nhm.org)

What is the main focus of the text?

The history of wildfires in California.
The impact of growing wildfires on the natural world.
The study of fossilized pollen in museum collections.
The cyclical burnings in NHMLAC research.
3
AI Outraces Human Champs at the Video Game Gran Turismo

To hurtle around a corner along the fastest “racing line” without losing control, race car drivers must brake, steer and accelerate in precisely timed sequences. The process depends on the limits of friction, and they are governed by known physical laws—which means self-driving cars can learn to complete a lap at the fastest possible speed (as some have already done). But this becomes a much knottier problem when the automated driver has to share space with other cars. Now scientists have unraveled the challenge virtually by training an artificial intelligence program to outpace human competitors at the ultrarealistic racing game Gran Turismo Sport. The findings could point self-driving car researchers toward new ways to make this technology function in the real world.

Artificial intelligence has already conquered human players within certain video games, such as Starcraft II and Dota 2. But Gran Turismo differs from other games in significant ways, says Peter Wurman, director of Sony AI America and co-author of the new study, which was published in Nature. “In most games, the environment defines the rules and protects the users from each other,” he explains. “But in racing, the cars are very close to each other, and there’s a very refined sense of etiquette that has to be learned and deployed by the [AI] agents. In order to win, they have to be respectful of their opponents, but they also have to preserve their own driving lines and make sure that they don’t just give way.”

To teach their program the ropes, the Sony AI researchers used a technique called deep reinforcement learning. They rewarded the AI for certain behaviors, such as staying on the track, remaining in control of the vehicle and respecting racing etiquette. Then they set the program loose to try different ways of racing that would enable it to achieve those goals. The Sony AI team trained multiple different versions of its AI, dubbed Gran Turismo Sophy (GT Sophy), each specialized in driving one particular type of car on one particular track. Then the researchers pitted the program against human Gran Turismo champions. In the first test, conducted last July, humans achieved the highest overall team score. On the second run in October 2021, the AI broke through. It beat its human foes both individually and as a team, achieving the fastest lap times.

The human players seem to have taken their losses in stride, and some enjoyed pitting their wits against the AI. “Some of the things that we also heard from the drivers was that they learned new things from Sophy’s maneuvers as well,” says Erica Kato Marcus, director of strategies and partnerships at Sony AI. “The lines the AI was using were so tricky, I could probably do them once. But it was so, so difficult—I would never attempt it in a race,” says Emily Jones, who was a world finalist at the FIA-Certified Gran Turismo Championships 2020 and later raced against GT Sophy.

(Excerpt from ‘AI Outraces Human Champs at the Video Game Gran Turismo’, scientificamerican.com, 2022)

What is this text mainly about?

A computer learning to race in a video game
How humans are better at racing than computers
How a smart computer won a racing game against people
A new video game called Gran Turismo Sport
4
What technique did the Sony AI researchers use to train their AI program?
Virtual reality simulations
Human-guided programming
Deep reinforcement learning
Human-controlled gameplay
5
In the sentence "They rewarded the AI for certain behaviors," what does the pronoun "They" refer to?
Human Gran Turismo champions
Sony AI researchers
Racing etiquette rules
Different versions of the AI program
6
In the sentence "The lines the AI was using were so tricky," what does the word "tricky" mean?
straightforward
complicated
predictable
boring
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