A new citizen-science project will improve the chances of finding ET
Ever since 1993, when funding from America’s space agency, NASA, was cut, the Search for Extraterrestrial Intelligence, which scans the sky looking for radio signals from intelligent aliens, has been inventive in its methods. In particular, it was one of the pioneers of the field of citizen science.
In 1999 it started SETI home, an application that uses spare processing power on volunteers’ computers to filter the information generated by its radio telescopes. These days, SETI home boasts more than one million users.
On February 29th the SETI Institute launched another citizen-science project. This time, though, its researchers are less interested in the digital computers on volunteers’ desks than in the biological ones between their ears.
Unfortunately, some parts of the radio covering scope are full of signals created by Earthlings, rather than aliens. Everything from passing satellites and space junk to ground-based radar and even the starting systems of nearby cars can generate fake radio waves that confuse the software.
But SETILive will bring them into play.
| A．That’s where interested amateurs help professionals process data. |
| B．Rather than examining on stored data, aliens are hunted on the fly. |
| C．Volunteers working on SETIhome have found plenty of interesting signals. |
| D．It will do so by feeding data from these noisy parts of the scope to its users. |
| E．SETI is to detect distinctive radio-frequency emissions from advanced aliens. |
| F．Until now, the project has tackled it by ignoring the crowded bits of the scope. |
| G．SETI Live, as the project is called, uses brain capacity to solve a lingering headache. |
相似题推荐
【推荐1】What Is the Metaverse (元宇宙) Tech Companies Aim to Build?
You may have heard the term metaverse to describe a new virtual world that major technology companies aim to develop. The word is a combination of the prefix meta—which means beyond—and verse, which relates to the universe.
The main technologies that would drive such a world would be VR, and augmented reality (AR).
A company has invested much money in VR and AR technologies to create the most realistic virtual interactions possible.
With the help of AR gasses, individuals might be able to see a large amount of information pass before their eyes while moving around in a city. This could include traffic and pollution data, information on he natural environment or local history.
| A．People linked to the metaverse would be connected a all times. |
| B．Such a system could one day be used with headsets in a metaverse. |
| C．It has also created a new team to specially develop metaverse products. |
| D．A metaverse environment might look a lot like many of the online video games. |
| E．The term appeared in the 1992 science fiction book written by Neal Stephenson. |
| F．Other yet-to-be invented technologies would likely also be used to improve experiences. |
| G．However, most predictions for a future metaverse see the technology going much further. |
【推荐2】The recent world chess championship saw Magnus Carlsen defend his title against Fabiano Caruana. But it was not a contest between the two strongest chess players on the planet, only the strongest humans. Soon after Garry Kasparov, the former world chess champion, lost his re-match against IBM’s Deep Blue in 1997, the short window of human-machine chess competition was shut forever. Unlike humans, machines keep getting faster, and today a smartphone chess app can be stronger than Deep Blue.
In the late 19th century, Alfred Binet hoped that understanding why certain people stood out at chess would unlock secrets of human thought. Sixty years later, Alan Turing wondered whether this sort of ability represents an essential difference between the potentialities of the machine and the mind. Much as airplanes don’t flap their wings like birds, machines don’t generate chess moves like humans do. Early programs that attempted it were weak.
But now things are different. Based on a common game-playing algorithm(算法), AlphaZero incorporates deep learning and other AI techniques to play against itself to generate its own chess knowledge. AlphaZerostarts out knowing only the rules of chess, with no inserted human strategies(策略). In just a few hours, it plays more games against itself than have been recorded in human chess history. It teaches itself the best way to play, reevaluating such fundamental concepts as the relative values of the pieces.It quickly becomes strong enough to defeat the best chess-players in the world, winning 28, drawing 72, and losing none in a victory over Stockfish, one of the strongest chess engines.
The conventional wisdom is that machines would approach perfection with endlessstrategies, usually leading to drawn games. But AlphaZero prefers positions that look risky and aggressive, and it programs itself, which allows it to outclass the world’s top traditional program despite calculating far fewer positions per second. It’s the example of the cliché, “work smarter, not harder.”
AlphaZero shows us that machines can be the experts, not merely expert tools. It’s not going to put chess coaches out of business just yet. But the knowledge it generates is information we can all learn from. AlphaZero is surpassing us in a profound and useful way.
Machine learning systems aren’t perfect, even at a closed system like chess. There will be cases where an AI will fail to detect exceptions to their rules. Therefore, we must work together, to combine our strengths. Instead of being angry against them, it’s better if we’re all on the same side.
1. According to the passage, Alan Turing might agree that .| A．airplanes can be as good as birds. |
| B．the unlocked secrets of human thought are powerful. |
| C．machines are better than human in generating chess moves. |
| D．the potentialities of the human mind are better than that of the machine. |
| A．AlphaZero have AI techniques. |
| B．AlphaZero can defeat the best chess players. |
| C．AlphaZero can play more games more quickly. |
| D．AlphaZero can generate its own chess knowledge. |
| A．Become | B．Beat | C．Leave | D．Distinguish |
| A．machine learning in chess is perfect. |
| B．human chess coaches are not needed yet. |
| C．AI will be learning to challenge their rules. |
| D．humans and AI can work together to advance. |
【推荐3】It was in the archives(档案室) of the Archbishop of York that Matthew Collins had a sudden insight: He was surrounded by millions of animal skins.
Another person might say they were surrounded by books and manuscripts written on parchment, which is made from skins, usually of cows and sheep. Collins, however, had been trying to make sense of animal—bone fragments from archaeological digs, and he began to think about the advantages of studying animal skins, already cut into rectangles and arranged neatly on a shelf. Archaeologists consider themselves lucky to get a few dozen samples, and here were millions of skins just sitting there.
In recent years, archaeologists and historians have awakened to the potential of ancient DNA extracted from human bones and teeth. DNA evidence has enriched—and complicated—stories of prehistoric human migrations. It has provided clues to epidemics such as the black death. It has identified the remains of King Richard III, found under a parking lot. But Collins isn't just interested in human remains. He’s interested in the things these humans made; the animals they bred, slaughtered, and ate; and the economies they created.
That’s why he was studying DNA from the bones of livestock—and why his lab is now at the forefront of studying DNA from objects such as parchment and beeswax. These objects can fill in gaps in the written record, revealing new aspects of historical production and trade. How much beeswax came from North Africa, for example?
Collins splits his time between Cambridge and the University of Copenhagen, and it’s hard to nail down exactly what kind of -ologist he is. He has a knack for gathering experts as diverse as parchment specialists, veterinarians, geneticists, archivists, economic historians, and protein scientists (his own background). “All I do is connect people together,” he said. “I’m just the ignorant one in the middle.”
However, it didn’t take long his group to hit their first culture conflict. In science and archaeology, destructive sampling is at least tolerated, if not encouraged. But book conservators were not going to let people in white coats come in and cut up their books. Instead of giving up or fighting through it, Sarah Fiddyment, a postdoctoral research fellow working with Collins, shadowed conservationists for several weeks. She saw that they used white Staedtler erasers to clean the manuscripts, and wondered whether that rubbed off enough DNA to do the trick. It did: the team found a way to extract DNA and proteins from eraser pieces, a compromise that satisfied everyone. The team has since sampled 5,000 animals from parchment his way.
Collins is not the first person to think of getting DNA from parchment, but he’s been the first to do it at scale. Studying the DNA in artifacts is still a relatively new field, with many prospects that remain unexplored. But in our own modern world, we’ve already started to change the biological record, and future archaeologists will not find the same treasure of hidden information in our petroleum - laden material culture. Collins pointed out what we no longer rely as much on natural materials to create the objects we need. What might have once been leather or wood or wool is now all plastic.
1. How is Collin’s study different from the study of other archaeologists?| A．He studies human skins and bones. |
| B．He is the first person to study animal skins. |
| C．He studies objects related to humans and their lives. |
| D．His study can provide clues to previous epidemics. |
| A．a subject covering a wide area |
| B．an area to explore |
| C．a person with special expert knowledge |
| D．a method to carry out research |
| A．his major doesn’t help his research |
| B．he can’t connect experts of different fields |
| C．he finds it hard to identify what kind of -ologist he is |
| D．his study covers a wide range of subjects beyond his knowledge |
| A．Destructive sampling is not allowed in the field of science and archeology. |
| B．Collin made a compromise by only studying copies of books made of animal skins. |
| C．Book protectors were opposed to Collin’s study because his group tracked them for several weeks. |
| D．It is difficult for future archeologist to study what society is like today due to plastic objects. |
| A．A new discovery in archaeology |
| B．A lab discovering DNA in old books |
| C．Archaeology on animals seeing a breakthrough |
| D．Collin's contributions to the identification of old books |
