1 . Last week, I sent the same request to ChatGPT, the latest artificial-intelligence chatbot from OpenAI. “Upon the Firth of Forth, a bridge doth stand,” it began. In less than a minute, the program had created in full a rhyming Shakespearean sonnet (莎士比亚十四行诗). Tools like ChatGPT seem poised to change the world of poetry — and so much else — but poets also have a lot to teach us about artificial intelligence. If algorithms (算法) are getting good at writing poetry, it’s partially because poetry was always an algorithmic business.

Even the most rebellious (叛逆的) poets follow more rules than they might like to admit. When schoolchildren are taught to imitate the structure of sonnet, they are effectively learning to follow algorithmic constraints. Should it surprise us that computers can do so, too?

But considering how ChatGPT works, its ability to follow the rules for sonnets seems a little more impressive. No one taught it these rules. It is based on a newer kind of AI known as a large language model (LLM). To put it simply, LLMs analyze large amounts of human writing and learn to predict what the next word in a string of text should be, based on context. One frequent criticism of LLMs is that they do not understand what they write; they just do a great job of guessing the next word.

When a private verse by Dickinson makes us feel like the poet speaks directly to us, we are experiencing the effects of a technology called language. Poems are made of paper and ink — or, these days, electricity and light. There is no one “inside” a Dickinson poem any more than one by ChatGPT. Of course, every Dickinson poem reflects her intention to create meaning. When ChatGPT puts words together, it does not intend anything. Some argue that writings by LLMs therefore have no meaning, only the appearance of it. If I see a cloud in the sky that looks like a giraffe, I recognize it as an accidental similarity. In the same way, this argument goes, we should   regard the writings of ChatGPT as merely imitating real language, meaningless and random as cloud shapes.

When I showed my friends the sonnet by ChatGPT, they called it “soulless and barren.” Despite following all the rules for sonnets, the poem is predictable. But is the average sonnet by a human any better? If we now expect computers to write not just poems but good poems, then we have set a much higher bar.

1. What is the main idea of paragraph 1 and paragraph 2?

A．ChatGPT will make a difference to poetry based on algorithms.

B．There is no doubt that AI can copy the grammatical rules of poetry.

C．Poetry guidelines provide a possibility for AI’s poetry writing.

D．There is a similarity between algorithms and poetry.

2. How does ChatGPT write poems?

A．ChatGPT is trained to follow the rules by LLMs.

B．ChatGPT can analyze and predict human languages.

C．ChatGPT is technologically supported by LLMs.

D．ChatGPT itself learn to follow the rules.

3. Why does the author mention Dickinson and cloud in paragraph 4?

A．He talks about cloud to describe the meaninglessness of AI’s poetry.

B．He tells of Dickinson to describe the meaninglessness AI’s poetry.

C．He mentions cloud to suggest its close relationship with AI’s poetry.

D．He refers to Dickinson to suggest her close relationship with AI’s poetry.

4. Which of the following can best describe the author’s attitude towards AI poetry?

A．Acceptable and favorable	B．Amazed and admiring
C．Indifferent and uncaring	D．Doubtful and uneasy

2 . 【课文原文】

SATISFACTION GUARANTEED

(Adapted)

Larry Belmont worked for a company that made robots. Recently it had begun experimenting with a household robot. It was going to be tested out by Larry’s wife, Claire.

Claire didn’t want the robot in her house, especially as her husband would be away on a business trip for three weeks, but Larry persuaded her that the robot wouldn’t harm her or allow her to be harmed. It would be a bonus. However, when she first saw the robot, she felt alarmed. His name was Tony. He seemed more like a human than a machine. He was tall and handsome with smooth hair and a deep voice, although his facial expression never changed.

On the second morning, Tony brought her breakfast and then asked her whether she needed help dressing. She felt embarrassed and quickly told him to go. Now she was being looked after by a robot that looked so human, and it was disturbing.

One day, Claire mentioned that she didn’t think she was clever. Tony said that she must feel very unhappy to say that. Claire thought it was ridiculous that she was being offered sympathy by a robot, but she gradually admired his wisdom and integrity and began to trust him. He always treated her with dignity. She told him how she was unhappy that her home wasn’t elegant enough for Larry, who wanted to improve his social position with a bigger salary. She wasn’t like Gladys Claffern, one of the richest and most powerful women around.

As a favour, Tony promised to help Claire make herself more beautiful and her home more elegant. So Claire borrowed some library books for him to read, or rather, scan. She looked at his fingers with wonder as they turned each page. How absurd, she thought. He was just a machine.

Tony gave Claire a new hairstyle and improved her makeup. As he was not allowed to accompany her to the shops, he wrote out a list of things that he would need for his work on the house. Claire went downtown and bought these things. She had an appointment to paint her nails,   then she went into an expensive clothes shop. The saleswoman there was rude to her, so she rang Tony and told him she was being treated badly. He spoke to the woman, who immediately changed her attitude. Claire thanked Tony, telling him that he was a “dear”. As she turned around, there stood Gladys Claffern. How awful to be discovered by her, Claire thought. By the look on her face, Claire knew that Gladys thought they were in a relationship. After all, she knew Claire’s husband’s name was Larry, not Tony. Although it was completely innocent, Claire felt guilty.

When Claire got home, she wept. Gladys was everything Claire wished to be. Tony told her she was being sensitive and was just as good as Gladys. He suggested that she invite Gladys and her friends to the house the night before he was to leave and Larry was to return. By that time, Tony expected that the house, which was being completely transformed, would be ready.

Tony worked steadily on the improvements. Claire tried to help by working on a light suspended from the ceiling, but she fell off the ladder. Even though Tony had been in the next room, he managed to catch her in time. As he held her, she felt the warmth of his body. She screamed, pushed him away, and ran to her room.

The night of the party arrived. The clock struck eight. The guests would be arriving soon, so Claire dismissed Tony for the rest of the night. At that moment, Tony took her in his arms, bringing his face close to hers. She heard him declare that he did not want to leave her the next day, and that he felt more than just the desire to please her. Then the front door bell rang.

1. What’s the text mainly about?

A．How to make a robot.

B．How a robot helps people.

C．What a robot can do.

D．A test on a household robot.

2. Match the main idea with each part.

A. The night of the party. B. Claire’s attitude to the robot and her feeling at the sight of the robot. C. What Tony did for Claire.

Part 1 (Paras.1－2) ____
Part 2 (Paras.3－8) ____
Part 3 (Para.9) ____
3. What does Larry Belmont think of testing out the robot in his house?

A．It is an extra benefit.	B．It is his responsibility.
C．It helps improve his house.	D．It can make Claire happy.

4. How did Claire feel when Tony offered to help her get dressed?

A．Proud.	B．Happy.
C．Guilty.	D．Embarrassed.

5. Why does Tony work on the house improvements?

A．Because Claire wants to hold a party in her house.

B．Because Claire plans to give Larry a surprise.

C．Because Claire doesn’t think it good enough for Larry.

D．Because Claire intends to make the best of Tony.

6. What can we infer from the last paragraph?

A．Tony falls in love with Claire.

B．Tony will have a rest that night.

C．Tony will stay with Claire forever.

D．Tony，the robot needs to be improved.

7. Complete the passage according to the text.

A household robot called Tony was to be tested out in Larry’s house. Though Claire, Larry’s wife, didn’t like ________ idea in the beginning, she was persuaded to let the robot ________ (company) her while her husband was away on a business trip. The robot looked like a tall and handsome man with smooth hair. Though his facial ________ (express) never changed, the robot was ________ (gift) with a charming deep voice. At the sight of Tony, Claire felt alarmed because he seemed ________ (much) like a human than a machine. So when Tony offered to help her get dressed, Claire felt more than embarrassed.

However, Tony gradually won Claire’s trust. He took good care of Claire and even managed to rescue her ________ she fell off the ladder. He also helped Claire realize her dream by ________ (make) her home elegant, giving her a new haircut and retouching her makeup. He advised her to throw a party and expected all the guests who ________ (invite) would be filled with admiration when they saw her house was ________ (complete) transformed. And Tony said he was so attached ________ her that he was unwilling to leave.

8. Analyse and translate the sentences.
(1)Claire didn’t want the robot in her house, especially as her husband would be away on a business trip for three weeks, but Larry persuaded her that the robot wouldn’t harm her or allow her to be harmed.
______________________________________________________________________
______________________________________________________________________
(2)Claire thought it was ridiculous that she was being offered sympathy by a robot, but she gradually admired his wisdom and integrity and began to trust him.
______________________________________________________________________
______________________________________________________________________
(3)She told him how she was unhappy that her home wasn’t elegant enough for Larry, who wanted to improve his social position with a bigger salary.
______________________________________________________________________
______________________________________________________________________

3 . When you ask people to judge others by their speech, a trend emerges: Listeners dislike disfluency. Slow talkers producing loads of ums and pauses(停顿)are generally perceived as less charming. But science tells us there may be even more to disfluency.

Disfluencies do not occur in arbitrary positions in sentences. Ums typically occur right before more difficult or low-frequency words. Imagine you’re having dinner with a friend at a restaurant,and there’re three items on the table: a knife, a glass, and a wine decanter(醒酒器). Your friend turns to you and says, “Could you hand me the...um...” What would you assume they want? Since it’s unlikely that they will hesitate before such common words as knife, and glass, chances are you’ll pick up the decanter and ask, “You mean this?”

This is exactly what we demonstrated through controlled eye-tracking studies in our lab. Apparently, listeners hear the um and predict that an uncommon word is most likely to follow.Such predictions, though, reflect more than just simple association between disfluencies and difficult words; listeners are actively considering from the speaker’s point of view. For example, when hearing a non-native speaker say the same sentence but with a thick foreign accent, listeners don’t show a preference for looking at low-frequency objects. This is probably because listeners assume non-native speakers may have as much trouble coming up with the English word for a common object, like a knife, as for unusual ones and can’t guess their intention.

In another experiment, listeners were presented with an atypical speaker who produced disfluencies before simple words and never before difficult words. Initially, participants displayed the natural predictive strategy: looking at uncommon objects. However, as more time went by, and they gained experience with this atypical distribution of disfluencies, listeners started to demonstrate the contrary predictive behavior: They tended to look at simple objects when hearing the speaker say um.

These findings represent further evidence that the human brain is a prediction machine: We continuously try to predict what will happen next, even though not all disfluencies are created equal.

1. What does the underlined word “arbitrary”mean in paragraph 2?

A．Random.

B．Strategic.

C．Obvious.

D．Consistent

2. What does the author say about the non-native speakers?

A．They can be understood easily.	B．They actively put themselves in others’ shoes
C．Their vocabularies are limited.	D．Their disfluencies are a little less predictive.

3. What does the experiment in paragraph 4 show?

A．Simple things are difficult in some cases.	B．Listeners can adjust predictions accordingly.
C．Distribution of disfluencies is changeable.	D．Disfluencies in communication can be avoided.

4. Which of the following can be the best title for the text?

A．Pauses Coexist with Prediction.	B．Brains Are Powerful Prediction Machines.
C．Active Listeners Simplify Talks.	D．Disfluency Says More Than You Think.

4 . Animal appear to predict earthquakes by sensing electricity in the air — the first study to find reliable evidence of the phenomenon has shown.

Cameras revealed an “amazing” drop in the number of animals up to 23 days before a major quake hit their rainforest home at Yanachaga National Park in Peru. Lead scientist Dr Rachel Grant, from Anglia Ruskin University, said, “The results showed that just before the earthquake, animals’ activity dropped right down.”

On a normal day the cameras placed around Yanachaga National Park record between 5 and 15 animals. But in the 23 days before the earthquake, the number of animals dropped to five or fewer per day. No animals were photographed at all on five of the seven days immediately before the quake.

Another study showed that animal activity remained normal in the park over a different period when seismic (地震的) activity was low. Co-author, professor Friedemann Freund, said, “The cameras were located at an altitude of 900 meters. If air ionization occurred, the animals would escape to the valley below, where there were fewer positive ions ( 离子). With their ability to sense their environment, animals can help us understand small changes that occur before major earthquakes.”

Other evidence suggested that before the earthquake, the air around the high mountain sites filled with positive ions that can be produced when rocks are placed under stress. Positive ions have been known to cause ill effects in humans as well as animals. Scientists believe the animals were made to feel uncomfortable by the positive ions, leading them to avoid the area. They are thought to have escaped to lower ground, where the air was less ionized. The findings may help experts develop better short-term seismic forecasts.

1. How did scientists conduct the study?

A．By comparing different animals’ habits.

B．By observing animals in high mountains.

C．By explaining the positive ion phenomenon.

D．By analyzing images of animals they obtained.

2. What can be inferred from animal activity before earthquakes?

A．The ground at a lower altitude is less ionized.

B．Cameras normally record more animals per day.

C．Earthquake warnings can be detected in lower places.

D．The activity of animals and earthquakes is consistent.

3. What can we learn from the text?

A．The findings make for accurate seismic forecast.

B．Animals tend to be uneasy with more positive ions.

C．Positive ions make humans and animals depressed.

D．All the animals remain abnormal before the earthquake.

4. What can be a suitable title for the text?

A．Negative Influence of Positive Ions.

B．Ions’ Destruction to the Environment.

C．Animals’ Behavior Before Earthquakes.

D．Creatures’ Ability to Predict Earthquakes.

5 . The Great PowerPoint Panic of 2003.

Sixteen minutes before touchdown on the morning of February 1, 2003, the space shuttle Columbia (“哥伦比亚”号航天飞机)______ into the cloudless East Texas sky. All seven astronauts aboard were killed. As the shattered shuttle flew toward Earth in pieces, it looked to its live TV viewers like a swarm of shooting stars.

The immediate ______ of the disaster, a report from a NASA Accident Investigation Board determined that August, was a piece of insulating foam (绝缘泡沫胶) that had broken loose and damaged the shuttle’s left wing soon after liftoff. But the report also   ______ out a less direct, more surprising cause. Engineers had known about - and inappropriately______ - the wing damage long before Columbia’s attempted reentry, but the flaws in their analysis were ______ in a series of overstuffed computer-presentation slides that were shown to NASA officials.

By the start of 2003, the phrase “death by PowerPoint” had well and truly entered the ______ vocabulary. Edward Tufte was the first to have taken it literally: That spring, the Yale statistician published a booklet entitled The Cognitive Style of PowerPoint, whose core argument was that the medium of communication influences the substance of communication. While PowerPoint, as a medium, did not ______ create unclear, lazy presentations, it certainly ______ and sometimes even masked them — with potentially deadly consequences. This is exactly what Tufte saw in the Columbia engineers’ slides.

Wired ran an excerpt (节选) from Tufte’s booklet in September 2003 under the headline “PowerPoint Is Evil.” A few months later, The New York Times Magazine included his assessment — summarized as “PowerPoint Makes You Dumb” — in its ______ of the year’s most important ideas. “Perhaps PowerPoint is uniquely suited to our modern age of confusion,” the entry read.

Despite the backlash it inspired in the ______, the presentation giant rolls on. The program has more monthly users than ever before, well into the hundreds of millions. During lockdown, people ______ PowerPoint parties on Zoom. Kids now make PowerPoint presentations for their parents when they want to get a puppy. If PowerPoint is evil, then evil ______ the world.

On its face at least, the idea that PowerPoint makes us stupid looks like a textbook case of misguided technological doomsaying. Today’s concerns about social media somehow resemble the PowerPoint critique. Both boil down to a worry that new media technologies ______ form over substance, that they are designed to hold our attention rather than to convey truth, and that they make us stupid.

______, concerns about new media rarely seem to make a difference. If the innovation did change the way we think, we are measuring its effects with an altered mind. Either the critical remarks were wrong, or they were so right that we can no longer tell the   ______.

1.

A．disappeared

B．disintegrated

C．distributed

D．disappointed

2.

A．side

B．cause

C．feature

D．issue

3.

A．collected

B．unified

C．dropped

D．single

4.

A．discounted

B．viewed

C．accessed

D．founded

5.

A．muted

B．absorbed

C．buried

D．sunk

6.

A．technical

B．popular

C．negative

D．special

7.

A．possibly

B．reasonably

C．ordinarily

D．necessarily

8.

A．accommodated

B．combined

C．distinguished

D．enhanced

9.

A．abstract

B．repetition

C．review

D．brief

10.

A．press

B．publication

C．media

D．criticism

11.

A．opened

B．created

C．threw

D．jumped

12.

A．rules

B．harmonizes

C．impacts

D．roars

13.

A．feature

B．encourage

C．value

D．defend

14.

A．Therefore

B．However

C．Certainly

D．Surprisingly

15.

A．difference

B．truth

C．time

D．concern

7 . Armed with a toolkit of techniques and tricks to calm the mind and bring focus back to your body, you can stop stressful situations from sabotaging your day, says Katy Georgiou.

GROUND YOURSELF

Making contact with the ground is your baseline go-to response for stress. This technique can be especially helpful if you find your stress regularly turns into panic. Wherever you are, whatever you’re doing, place your feet flat on the ground so that you feel stable, and then close your eyes. If you’re able to sit on the floor cross-legged or to lie down flat, then even better.

Think of this as earthing: really connect with the ground beneath your body. Some studies suggest that this simple act can help reduce or relieve symptoms of stress such as pain and fatigue, reduce blood pressure, and improve sleep. If you’re feeling disconnected from the world, it can also remind you that you belong to it and are a crucial part of it — the ground will always be there for you.

LOVE THYSELF

Adopting regular, daily or weekly routines for self-care can be very containing, creating consistency amid all sorts of stressful life events happening around you. Looking in the mirror each day can actually remind you that you exist, so feel free to factor some reflective gazing into your daily routine, whether it’s while applying moisturiser, shaving, or brushing your hair. Studies have shown that being confronted with your reflection can have powerful effects, taking us out of our heads and into the immediate present. For added effect, pay attention to the way your products interact with your hair and skin as you apply them.

Playing around with smells, colours and textures in your hands will also engage your senses. Using a scented shampoo or smoothing on body lotion after a warm bath can be easy ways to do this.

CLEAR YOUR MIND

Abandon all your thoughts and try to focus only on your surroundings. What can you see, hear, smell, taste and touch? Identify three things you can hear, one thing you can taste, four things you can see and two things you can feel on your skin. Pick out colours in the room you are sitting in, notice textures and different kinds of light. If somebody is with you, tell them what you are experiencing. The point here is that your senses are your best and easiest route back to feeling calm, by coming out of your head and rooting yourself back in the present. This is incredibly helpful if you’re having a panic attack or flop response.

1. If your friend Jane always feels worn out and suffers from sleep deprivation, which of the following techniques will you especially recommend to her?

A．Connect her body to the ground beneath her.

B．Adopt a daily gaze at her reflection in the mirror.

C．Exchange her scentless shampoo for an aromatic one.

D．Focus on what she can see, hear, smell, taste and touch.

2. Which of the following statements is NOT TRUE according to the passage?

A．Lying down flat can better relieve your stress.

B．Grounding yourself can give you a sense of belonging to the world.

C．Brushing your hair while looking in the mirror can remind you of your existence.

D．Those having a panic attack should shut their senses down.

3. The passage is intended to __________.

A．help people understand themselves better

B．introduce some practical methods for stress management

C．emphasize the significance of exploiting multiple senses

D．promote a mindset of living in the moment

8 . How Did You Get Five Fingers?

Your arms and toes began as tiny buds that sprouted from your sides when you were just a four-week-old embryo (胚胎). By six weeks, these limb buds had grown longer and five rods of cartilage 软骨) had appeared in their flattened tips. By week seven, the cells between the rods had died away, forming five small fingers or toes from once-solid masses of flesh.

Now, a team of scientists led by James Sharpe from the Centre for Genomic Regulation in Barcelona has discovered that these events are carefully orchestrated by three molecules. They mark out zones in the embryonic hand where fingers will grow, and the spaces in between that are destined to die. Without such molecules, pianos and keyboards wouldn’t exist, and jazz hands would be jazz palms.

These three molecules work in a way first envisioned by Alan Turing, a legendary English mathematician and code-breaker. Back in 1952, Turing proposed a simple mathematical model in which two molecules could create patterns by spreading through tissues and interacting with each other. For example, the first molecule might activate the second, while the second blocks the first. Neither receives any guidance about where to go; through their dance, they spontaneously organize themselves into spots or stripes.

Since then, many scientists have found that these Turing mechanisms exist. They’re responsible for a cheetah’s spots and a zebrafish’s stripes. For 30 years, people have also suggested that they could sculpt our hands and feet, but no one had found the exact molecules involved.

Sharpe knew that these molecules would need to show a striped pattern. Sox9 seemed like the most promising candidate. It is activated in a striped pattern from a very early stage of development. By comparing cells where Sox9 is active or inactive, Jelena Raspopovic and Luciano Marcon found two other groups of genes—Bmp and Wnt—also formed striped patterns. Bmp rises and falls in step with Sox9 and both are active in the digits. Wnt is out of phase; it’s active in the gaps. The three molecules also affect each other: Bmp activates Sox9 while Wnt blocks it; and Sox9 blocks both of its partners. It looked like these were the molecules the team was searching for not a pair, as Turing suggested, but a trinity. To confirm this, they created a simulation of a growing limb bud and showed that Sox9, Bmp and Wnt could organize themselves into a pattern of five stripes, by activating and blocking each other.

There’s still a lot to discover, though. For example, I’ve used Bmp and Wnt as shorthands here—in reality, each represents a class of several molecules, and the team still needs to work out which specific member is part of the Turing’s proposal.

1. The underlined sentence in the second paragraph means that ________.

A．some certain molecules are necessary for the growth of human fingers

B．the development of embryos is dependent on some certain molecules

C．without some certain molecules, music won’t exist in this world

D．the molecules work in a way that Alan Turing once offered

2. What can we learn from the example given in the third paragraph?

A．Molecules interact by following a strict mathematical model.

B．Molecules have a strong will to form patterns in nature.

C．The formation of patterns in nature may be dominated by molecules.

D．Alan Turing was able to track down the movement of molecules.

3. What is “Sox9” according to the passage?

A．A protein that determines humans’ development in childhood.

B．A gene especially important for the development of our limbs.

C．A striped pattern that always interacts with Bmp and Wnt.

D．A simulation of growing limbs that activate and block each other.

4. Which of the following statements is TRUE according to the passage?

A．How human limbs are developed may well be similar to how animal spots are shaped.

B．The way Sox9 interacts with Bmp and Wnt is still a mystery that needs further studying.

C．Sox9 can activate both Bmp and Wnt to form our limbs, according to scientific research.

D．Sox9, Bmp and Wnt are three specific molecules that determine the growth of fingers.

9 . On March 7, 1907, the English statistician Francis Galton published a paper which illustrated what has come to be known as the “wisdom of crowds” effect. The experiment of estimation he conducted showed that in some cases, the average of a large number of independent estimates could be quite accurate.

This effect capitalizes on the fact that when people make errors, those errors aren’t always the same. Some people will tend to overestimate, and some to underestimate. When enough of these errors are averaged together, they cancel each other out, resulting in a more accurate estimate. If people are similar and tend to make the same errors, then their errors won’t cancel each other out. In more technical terms, the wisdom of crowds requires that people’s estimates be independent. If for whatever reasons, people’s errors become correlated or dependent, the accuracy of the estimate will go down.

But a new study led by Joaquin Navajas offered an interesting twist (转折) on this classic phenomenon. The key finding of the study was that when crowds were further divided into smaller groups that were allowed to have a discussion, the averages from these groups were more accurate than those from an equal number of independent individuals. For instance, the average obtained from the estimates of four discussion groups of five was significantly more accurate than the average obtained from 20 independent individuals.

In a follow-up study with 100 university students, the researchers tried to get a better sense of what the group members actually did in their discussion. Did they tend to go with those most confident about their estimates? Did they follow those least willing to change their minds? This happened some of the time, but it wasn’t the dominant response. Most frequently, the groups reported that they “shared arguments and reasoned together”. Somehow, these arguments and reasoning resulted in a global reduction in error. Although the studies led by Navajas have limitations and many questions remain, the potential implications for group discussion and decision-making are enormous.

1. What is paragraph 2 of the text mainly about?

A．The methods of estimation.	B．The underlying logic of the effect.
C．The causes of people’s errors.	D．The design of Galton’s experiment.

2. Navajas’ study found that the average accuracy could increase even if ________.

A．the crowds were relatively small	B．there were occasional underestimates
C．individuals did not communicate	D．estimates were not fully independent

3. What did the follow-up study focus on?

A．The size of the groups.	B．The dominant members.
C．The discussion process.	D．The individual estimates.

4. What is the author’s attitude toward Navajas’ studies?

A．Unclear.

B．Dismissive.

C．Doubtful.

D．Approving.