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In Mangtuan, a village in Yunnan's Gengma Dai and Wa autonomous county, an ancient paper-making tradition remains alive. (inspire) by village elders' paper-making during her childhood, local artisan Ai Ye chose to carry this tradition.

The paper made in the village is known as mulberry bark paper. One sheet of paper takes three days (make). The process includes soaking, pulping (制浆), sheet-forming drying.

Hundreds of years ago, Mangtuan was chosen as the county's official paper-making village. In 2006, the Dai paper-making tradition (include) in the national intangible cultural heritage list.

Despite a modern paper factory nearby, the tradition in Mangtuan not only survived but grew. Ai Ye made some changes. She used fresh flowers and leaves, (color) them, and developed new ways to prevent dehydration (脱水). Tourists loved these (wonder) products and prices increased.

In 2014, she founded a company, (develop) over 20 cultural products for export. Last year, the village produced over 3.9 million sheets of paper, benefited local employment and income. Ai believes paper has emotions, and if treated(careful), it won't let people down.

On the way home, I2 in a small town to get petrol. I fuelled (给……加油) up and then went inside to3.

I was in my early 20s and wasn't earning money because I'd been4 my grandmother, so I put only $20 worth of petrol in. But my card didn't work. This was a time before mobile phones, so I couldn't call anyone else to5 them to put money in my account. I felt a wave of6 wash over me.

Behind the counter was a young man. He just had this7 on the situation I was in. He said, "I'll pay for the fuel."

I politely refused. But he8, saying he understood that sometimes this happens. His9 seemed beyond his years.

When I got back in the car, I was still feeling10. But I was committed to getting that money back to him somehow, and I did. Back then, $20 felt like a huge amount. I'm11 that it was a lot for him too.

In the years after, I often drove past that petrol station hoping to12 him again. Sadly, I never did.13, his kind act of offering me the money really made a14. It inspired me to be a better person, and even now, I am deeply15.

They must not only know various kinds of music but also select music to suit different events and audiences. DJs must be confident in skillfully guiding their listeners through an enjoyable experience using music. So DJs must be capable of using computers and music-mixing software. DJs must also be ready to think on their feet when their equipment does not work properly. Finally, DJs must be good at working with people and organizations so that they can get more DJing opportunities.

If you dream of becoming a DJ, there are some key steps to follow. First, decide if DJing is just a hobby or your future career. What skills do you already have? What skills do you need to develop? Listen to many styles of music, and start building your music playlists. Buy basic music-mixing software, and practice creating a continuous flow of music.

As you improve, develop your style, and record your mixes. Post your mixes online to get followers, and make connections with other DJs to learn from them. Experience is key! Volunteer to DJ for local events and on radio stations. Build relationships with organizations, and offer your DJ services.

A. DJs need a particular skill set.

B. Technology is a big part of the job.

C. There are several challenges of being a DJ.

D. If so, DJing might be a great career for you.

E. We have to decide what type of DJ you want to become.

F. This will help you know how much time and money to put into it.

G. The more people know about you, the more chances you'll get to DJ.

Present methods can only narrow down locations to within tens of kilometres, says Stefania Ursica at the Helmholtz Centre for Geosciences in Germany. In remote areas, this can lead to slowdowns if rescuers are sent to the wrong place. "That time loss can be critical," Ursica says.

Many countries have a network of seismic monitors to record activity related to earthquakes and volcanoes. This data can also be used to detect events such as landslides — the risk of which is increasing because of climate change — but the data from these kinds of events is much messier and harder to analyse than that from earthquakes, says Ursica.

There are two new features of her team's technique, she says. The first is to analyse five different aspects (方面) of the seismic waveform to pick out from the noise exactly when an event happened.

This information is then fed to a dozen or so mathematical programmes that search for the location of the event. They do this by working out what waveform would have been produced if the event had happened in a particular place and comparing it to the recorded waveform. If it doesn't match, they try a different place.

Each programme "moves" in a way inspired by the behaviour of animals, from the spiralling of a falcon to the long migrations of elephants, until they have collectively homed in on the most likely location of the event. The whole process takes only around 10 seconds. "We have basically an order of magnitude (巨大) of improvement," Ursica says.

In addition to helping rescue efforts, it will help researchers locate events in remote areas where satellite data is unclear or unavailable. She says: "We can locate events that we otherwise couldn't see."

I could argue that AI — like machine learning and big language models — will clearly help important fields like healthcare. But there are real worries too, like hackers (黑客) misusing it or the huge energy needed for data centers. Still, I'm not too concerned about AI taking over people's jobs.

Why not? Because of "Polanyi's Paradox" — the idea that humans know things we can't explain, which limits AI's ability to copy key human skills. For example, in math, we can describe processes involving data collection and analysis that can be taught to students. That's explicit knowledge, which enables us to program a computer to analyze and learn from data. But many human activities use abilities we understand intuitively (直觉地) but cannot clearly explain. This is implicit knowledge.

Therefore, human subjective experiences, beliefs and empathy (共情) form unbeatable barriers (障碍) that keep AI from replacing humans at work. As Dr. Tom McClelland at Clare College observed, it's one thing to win a game of chess; another thing to feel the excitement of victory. That's because those internal processes come from human consciousness (意识), which plays an important role in the development of humans — biologically, culturally and behaviorally, all of which form the basis of our society. You can't program consciousness — mountains of literature and research have been published on the subject, and yet we still can't agree on what it is.

These barriers to AI's failure in replacing humans don't necessarily benefit my Phoenix taxi driver, who must compete with driverless cars. But they should remind us that we've faced similar fears before — and that technology has improved, not lowered, our quality of life over the centuries.