【推荐2】What if we had the power to control time, instead of moving from the past to the present to the future? What if we could jump and travel through time in a machine? What if we could go wherever and whenever we pleased?

The mysterious puzzle of time has kept people debating its nature for hundreds of years. Science fiction writers have turned it into imaginative stories. Some scientists have even attempted to explain it using math, trying to make the dream of time travel come true.

Albert Einstein said that time and space are one thing called “spacetime.” He said there are three dimensions in space: height, width and depth. A scientist named Hermann Minkowski added time as a fourth dimension.

Einstein introduced two ideas that have led to theories about the possibility of time travel. The first is relativity. The idea of relativity is that the force of gravity causes space to bend, which causes time to twist. The second idea focuses on special relativity. The idea is that a traveler moving super-fast through flat spacetime will enter the future. Einstein considered time “relative” because it is measured based on where we are on Earth or in space.

Stephen Hawking believes that a time machine will never be built. If it were possible, he thinks we would already know. If a time machine could be built, how come no one from the future has invaded us?

The first science fiction story with this theme is The Clock That Went Backward by Edward P. Mitchell, which was published in 1881. Since then, thousands of books, films and television shows have explored the idea of time travel, in which some tools such as phones, watches, photographs and old books take travelers backward and forward.

Will time travel ever happen? Who knows? Most important is to keep your eyes open and have a sense of wonder.

【推荐1】Machines might one day replace human laborers in a number of professions, but surely they won’t ever replace human artists. Right?

Think again. Not even our artists will be safe from the inevitable machine takeover, if a new development in artificial intelligence by a team of researchers from Rutgers University and Facebook’s A.I. lab offers a clue of what’s to come. They have designed an A.I. capable of not only producing art, but actually inventing whole new aesthetic styles similar to movements like impressionism or abstract expressionism, reports. The idea, according to researcher Marian Mazzone, was to make art that is “novel, but not too novel.”

The model used in this project involved a generator network, which produces the images, and a discriminator network, which “judges” whether it’s art. Once the generator learns how to produce work that the distributor recognizes as art, it’s given an additional directive: to produce art that doesn’t match any known aesthetic styles.

“You want to have something really creative and striking — but at the same time not go too far and make something that isn’t aesthetically (美学地) pleasing,” explained Ahmed Elgammal.

The art that was generated by the system was then presented to human judges alongside human-produced art without showing which was which. To the researchers’ surprise, the machine-made art scored slightly higher overall than the human-produced art.

Of course, machines can’t yet replace the meaning that’s infused in works by human artists, but this project shows that artist skill sets certainly seem duplicatable by machines.

What will it take for machines to produce content that’s infused with meaning? That might be the last A.I. frontier. Human artists can at least hang their hats in that field...for now.

“Imagine having people over for a dinner party and they ask, ‘Who is that by?’ And you say, ‘Well, it’s a machine actually’. That would be an interesting conversation starter,” said Kevin Walker.

【推荐3】Predicting extreme weather events is a tricky business. Changing climate conditions have increased the frequency of severe storms, floods, and heatwaves, along with larger wildfires. As a result, scientists are using artificial intelligence (AI) techniques for more accurate forecasts that help to minimize damage and save lives.

Researchers at Pennsylvania State University have worked together with meteorologists (气象学家) to analyze more than 50,000 weather satellite images to quickly identify storms. They found comma-shaped cloud formations that often lead to severe weather such as hail, blizzards, high winds, and thunderstorms.

Computers were then taught using computer vision and machine learning to automatically detect these clouds from satellite images, with almost 100 percent accuracy, in less than a minute. By refocusing meteorologists’ attention on potential storm cloud formation the AI tool helped predict 64 percent of severe weather events and beat established detection systems.

Expensive supercomputers are often used to process vast amounts of data needed for accurate weather prediction. But powerful AI methods can run on smaller computers. Climate risk and planning company ClimateAI uses a technique to downscale global weather forecasts to a local scale, cutting down on costs and computing power.

It uses a machine learning technique that pits two neural networks against each other. The neural networks - designed to work like neurons connected in the brain - fight and train each other using global weather data until they get a result.

Using this method ClimateAI researchers generate highly accurate and inexpensive local forecasts for hours or days ahead. And because it is not as costly, it allows poorer countries affected by climate change to use forecasts to change the way they farm, build bridges, roads, or homes, and adapt to extreme weather.

Average costs associated with extreme weather events in the United States have increased steadily since 1980. These have costly impacts on cities’ basic services, infrastructure, housing, human livelihoods, and health. AI helps us to calculate that risk and can be used as a preventive measure.