1 . Debate about artificial intelligence (AI) tends to focus on its potential dangers: algorithmic bias (算法偏见) and discrimination, the mass destruction of jobs and even, some say, the extinction of humanity. However, others are focusing on the potential rewards. Luminaries in the field such as Demis Hassabis and Yann LeCun believe that AI can turbocharge scientific progress and lead to a golden age of discovery. Could they be right?

Such claims are worth examining, and may provide a useful counterbalance to fears about large-scale unemployment and killer robots. Many previous technologies have, of course, been falsely hailed as panaceas (万灵药). But the mechanism by which AI will supposedly solve the world’s problems has a stronger historical basis.

In the 17th century microscopes and telescopes opened up new vistas of discovery and encouraged researchers to favor their own observations over the received wisdom of antiquity (古代), while the introduction of scientific journals gave them new ways to share and publicize their findings. Then, starting in the late 19th century, the establishment of research laboratories, which brought together ideas, people and materials on an industrial scale, gave rise to further innovations. From the mid-20th century, computers in turn enabled new forms of science based on simulation and modelling.

All this is to be welcomed. But the journal and the laboratory went further still: they altered scientific practice itself and unlocked more powerful means of making discoveries, by allowing people and ideas to mingle in new ways and on a larger scale. AI, too, has the potential to set off such a transformation.

Two areas in particular look promising. The first is “literature-based discovery” (LBD), which involves analyzing existing scientific literature, using ChatGPT-style language analysis, to look for new hypotheses, connections or ideas that humans may have missed. The second area is “robot scientists”. These are robotic systems that use AI to form new hypotheses, based on analysis of existing data and literature, and then test those hypotheses by performing hundreds or thousands of experiments, in fields including systems biology and materials science. Unlike human scientists, robots are less attached to previous results, less driven by bias—and, crucially, easy to replicate. They could scale up experimental research, develop unexpected theories and explore avenues that human investigators might not have considered.

The idea is therefore feasible. But the main barrier is sociological: it can happen only if human scientists are willing and able to use such tools. Governments could help by pressing for greater use of common standards to allow AI systems to exchange and interpret laboratory results and other data. They could also fun d more research into the integration of AI smarts with laboratory robotics, and into forms of AI beyond those being pursued in the private sector. Less fashionable forms of AI, such as model-based machine learning, may be better suited to scientific tasks such as forming hypotheses.

I’m glad to know that you’re interested in the activity of painting Beijing Opera Masks (脸谱) held by our school’s Beijing Opera club last Sunday. I would like to share something about it with you.

I also want to know your school’s club activities. Hope to hear from you soon.   

Yours,

Li Hua

What may well be the oldest metal coins in the world have been identified at an ancient abandoned city known as Guanzhuang in China. Like many Bronze Age (青铜时代) coins from the region, they were cast in the shape of spades with finely carved handles. These ancient coins existed during an in-between period between barter (以物易物) and money, when coins were a novel concept, but everybody knew that agricultural tools were valuable.

Reading about this incredible discovery, I kept thinking about the way modern people represent computer networks by describing machines as having “addresses”, like a house. We also talk about one computer using a “port” to send information to another computer, as if the data were a floating boat with destination. It’s as if we are in the Bronze Age of information technology, grasping desperately for real-world reference to transform our civilization.

Now consider what happened to spade coins. Over centuries, metalworkers made these coins into more abstract shapes. Some became almost human figures. Others’ handles were reduced to small half-circles. As spade coins grew more abstract, people carved them with number values and the locations where they were made. They became more like modern coins, flat and covered in writing. Looking at one of these later pieces, you would have no idea that they were once intended to look like a spade.

This makes me wonder if we will develop an entirely new set of symbols that allow us to interact with our digital information more smoothly.

Taking spade coins as our guide, we can guess that far-future computer networks will no longer contain any recognizable references to houses. But they still might bring some of the ideas we associate with home to our mind. In fact, computer networks — if they still exist at all — are likely to be almost the indispensable part of our houses and cities, their sensors inset with walls and roads. Our network addresses might actually be the same as our street addresses. If climate change leads to floods, our mobile devices might look more like boats than phones, assisting us to land.

My point is that the metaphors of the information age aren’t random. Mobile devices do offer us comfort after a long day at work. In some sense, our desire to settle on the shores of data lakes could change the way we understand home, as well as how we build computers. So as we cast our minds forward, we have to think about what new abstractions will go along with our information technology. Perhaps the one thing we count on is that humans will still appreciate the comforts of home.

6 . If you’ re reaching for the last piece of pizza at a party, and meanwhile see another hand going for it, your next move probably depends on how you feel and whom the hand belongs to. Your little sister — you might just grab the pizza. Your boss — you probably will give up. But if you’re hungry and feeling particularly confident, you might go for it.

Now researchers have made progress in understanding how mammals’ brain encodes social rank and uses this information to shape behaviours — such as whether to fight for that last pizza slice. They discovered that an area of the brain called the medial prefrontal cortex (mPFC) was responsible for representing social rank in mammals; changes to a mouse’s mPFC affect its dominance (支配) behaviour. But it was unknown how the mPFC represented this information and which neurons (神经元) were involved in changing dominance behaviour.

In the new study, Professor Kay Tye let groups of four mice share a cage, allowing a social hierarchy (等级) to naturally develop — some mice became more dominant and others more subordinate. As soon as the mice were paired up, he discovered, the activity of their mPFC neurons could predict — with 90 percent certainty — the rank of their opponent.

“We expected animals might only signal rank when they are in a competition,” says co-researcher Nancy. “But it turns out animals walk around with this representation of social rank all the time.”

When the researchers next asked whether the activity of the mPFC neurons was associated with behaviour, they found something surprising. The brain activity patterns were linked with slight changes in behaviour, such as how fast a mouse moved, and they also could predict — a full 30 seconds before the competition started — which mouse would win the food reward.

The winner was not always the more dominant, but the one engaged in a “winning mindset”. Just as you might sometimes be in a more competitive mood and be more likely to snatch that pizza slice before your boss, a subordinate mouse might be in a more “winning mindset” than a more dominant mouse and end up winning.

The areas of the mPFC associated with social rank and “winning mindset” are next to one another and highly connected. Signals on social rank impact the state of the brain involved in “winning mindset”. In other words, a subordinate mouse’s confidence and “winning mindset” may partially decrease when faced with a dominant one.

“This is further evidence to suggest that we are in different brain states when we are with others compared to when we’re alone,” says Tye. “Regardless of who you’re with, if you’re aware of other people around you, your brain is using different neurons.”

8 . Should schools report a student’s health to parents?

As if grades weren’t enough to worry about, some students now have weight on their minds too. The number of overweight children in the United States has more than doubled in the past 20 years, according to the U.S. Centers for Disease Control and Prevention.     1    

As a result, schools in several states, from California to Pennsylvania, have started sending home "BMI report cards". Those schools send home a report of a student’s body mass index (BMI). BMI is a calculation of weight and height that tells whether a person is overweight for his or her age.

    2     People on both sides of the debate are weighing in.

Some lawmakers say BMI reports warn parents of their children s health problem help fight against obesity. In 2003, former Arkansas Governor. Mike Huckabee helped launch the first program to report students’ BMI.       3     Pechatrician Joe Thompson helped plan the BMI program for Arkansas schools. He explains that the reports in Arkansas are sent home separately from report cards. “The misconception is that students are being graded on their weight,” he told WR News, “Just like a school screen for vision or hearing, this is a health approach to raise awareness about a risk.”

    4     Parents have complained that the reports damage their children’s self-respect. Some parents say kids also worry that they are being “graded” on their weight.       5     They point out that many school cafeterias serve tasty foods. Parent Brett Levy from Chicago, Illinois, believes that schools should teach kids to lead healthy lifestyles instead of reporting their BMIS. “Telling a boy or girl a BMI is not education,” he told WR News. “It’s a fear strategy.”