Yours,

Li Hua

Yours,

Li Hua

6 . Home prices remained divergent in China during December, with some of the first-tier cities recording price drops, while second and third-tier cities saw increases due to the varied market policies, the National Bureau of Statistics said on Thursday.

Newly built commercial housing prices in the first-tier cities－namely Beijing, Shanghai, Guangzhou and Shenzhen－remained stable in December, while those in second and third- tier cities rose by 0.6 percent and 0.5 percent respectively from November 2017.

The same trend was witnessed in second-hand home prices, which dropped slightly by 0.1 percent in first-tier cities and rose 0.3 percent in both second and third-tier cities in December, said Liu Jianwei, a senior statistician at the NBS.

In September 2017, the local governments of several regional capitals launched new restrictions to further slow home sales, in response to the central government’s call to end housing speculation and cool the red-hot housing market in certain cities.

As housing regulations in larger cities have tightened, investors have started looking for opportunities in medium-sized and small cities, thus causing a noticeable home price increase in third-tier cities.

Fan Hengshan, deputy secretary-general of the National Development and Reform Commission, said at an economic forum on Thursday that housing prices in third and fourth-tier cities have risen too fast, and this needs to be monitored carefully.

“The home price increase in third-tier cities will have a fairly large impact, considering that a large part of China’s gross domestic product and population come from these cities,” said Zhang Zhiwei, chief economist and head of equity strategy for China at Deutsche Bank, during a recent media briefing.

Zhang estimated that third-tier cities accounted for a major part of Chinese residents’ 50 trillion yuan wealth gains, driven by rising home prices in 2017.

“Despite a relatively large increase in home prices in third-tier cities, studies have found that at the end of 2017, local residents in 85 third-tier cities need to save four to eight years of their income to buy a home, meaning that house price to income ratios are not too high in these cities,” he said.

Up to 82 percent of children with healthy mothers are not easy to be obese（肥胖的）, according to research. A mother,     1     has a healthy weight, exercises regularly, eats a healthy diet, doesn’t smoke and only     2    (drink) wine in moderation, is significantly less likely     3    (have)a fat child, scientists say.

And research suggests it could be more to do with nurture(养育)    4     nature, as a mother's lifestyle appears     5    (direct) linked to the health of her child. When both mother and child follow a healthy lifestyle, the risk of obesity     6    (reduce)even more, the study of more than 24,000 children found.

The study examined the medical history and lifestyles of more than 24,000 children aged nine     7     fourteen, born to almost 17,000 women in the US. Researchers looked at the link between overall mother health and likelihood of a child     8    (be) obese.

The mother's health was judged on her height-to-weight ratio(比例), her diet, amount of physical     9    (active), smoking status and how much alcohol she drank. A healthy weight and diet, regular exercise, no smoking and moderate drinking all reduce the chance of a woman having     10     obese child.

9 . Hollywood’s theory that machines with evil(邪恶) minds will drive armies of killer robots is just silly. The real problem relates to the possibility that artificial intelligence(AI) may become extremely good at achieving something other than what we really want. In 1960 a well-known mathematician Norbert Wiener, who founded the field of cybernetics（控制论）, put it this way: “If we use, to achieve our purposes, a mechanical agency with whose operation we cannot effectively interfere(干预), we had better be quite sure that the purpose put into the machine is the purpose which we really desire.”

A machine with a specific purpose has another quality, one that we usually associate with living things: a wish to preserve its own existence. For the machine, this quality is not in-born, nor is it something introduced by humans; it is a logical consequence of the simple fact that the machine cannot achieve its original purpose if it is dead. So if we send out a robot with the single instruction of fetching coffee, it will have a strong desire to secure success by disabling its own off switch or even killing anyone who might interfere with its task. If we are not careful, then, we could face a kind of global chess match against very determined, super intelligent machines whose objectives conflict with our own, with the real world as the chessboard.

The possibility of entering into and losing such a match should concentrate the minds of computer scientists. Some researchers argue that we can seal the machines inside a kind of firewall, using them to answer difficult questions but never allowing them to affect the real world. Unfortunately, that plan seems unlikely to work: we have yet to invent a firewall that is secure against ordinary humans, let alone super intelligent machines.

Solving the safety problem well enough to move forward in AI seems to be possible but not easy. There are probably decades in which to plan for the arrival of super intelligent machines. But the problem should not be dismissed out of hand, as it has been by some AI researchers. Some argue that humans and machines can coexist as long as they work in teams—yet that is not possible unless machines share the goals of humans. Others say we can just “switch them off” as if super intelligent machines are too stupid to think of that possibility. Still others think that super intelligent AI will never happen. On September 11, 1933, famous physicist Ernest Rutherford stated, with confidence, “Anyone who expects a source of power in the transformation of these atoms is talking moonshine.” However, on September 12, 1933, physicist Leo Szilard invented the neutron-induced(中子诱导) nuclear chain reaction.