Facebook has developed the first machine learning model that can translate between any two of 100 languages without going into English first. It says the new multilingual machine translation model was created to help its more than two billion users Worldwide. The company is still testing the translation system-which it calls M2M-100-and hopes to add it to different products in the future.

Angela Fan, a research assistant at Facebook, said the model produces better results than other machine learning systems that depend on English to help in the translation process. The other systems use it as an intermediate step-like a bridge-to-translate between two non-English languages.

One example would be a translation from Chinese to French. Fan noted that many machine translation models begin by translating from Chinese to English first, and then from English to French. This is done “because English training data is the most widely available,” she said. But such a method can lead to mistakes in translation.

Facebook says about two-thirds of its users communicate in a language other than English. The company already carries out an average of 20 billion translations every day on Facebook’s News Feed. But it faces a huge test with many users publishing large amounts of content in more than 160 languages.

One difficulty the team faced was trying to develop an effective machine translation system for language combinations that are not widely used, Facebook calls these “low-resource languages”. The data used to create the new model was collected from content available on the Internet. But there is limited Internet data on low-resource languages.

For now, it plans to continue exploring new language research methods while working to improve the new model. No date has been set for launching the translation system on Facebook.

But Angela Fan said the new system marks an important step for Facebook, especially for the times we live in. "Breaking language barriers through machine language translation is one of the most important ways to bring people together, provide authoritative information on COVID-19, and keep them safe from harmful content,” she said.

Pigeons in London have a bad reputation. Some people call them flying rats. And many blame them for causing pollution with their droppings. But now the birds are being used to fight another kind of pollution in this city of 8.5 million.

“The problem for air pollution is that it’s been largely ignored as an issue for a long time,” says Andrea Lee, who works for the London-based environmental organization Client Earth. “People don’t realize how bad it is, and how it actually affects their health.” London’s poor air quality is linked to nearly 10,000 early deaths a year. Lee says, citing(引用)a report released by the city manager last year. If people were better informed about the pollution they’ re breathing, she says, they could pressure the government to do something about it.

Nearby, on a windy hill in London’s Regent’s Park, an experiment is underway that could help—the first week of flights by the Pigeon Air Patrol. It all began when Pierre Duquesnoy, the director for DigitasLBi, a marketing firm, won a London Design Festival contest last year to show how a world problem could be solved using Twitter. Duquesnoy, from France, chose the problem of air pollution.

“Basically, I realized how important the problem was,” he says.   “But also I realized that most of the people around me didn’t know anything about it.” Duquesnoy says he wants to better measure pollution, while at the same time making the results accessible to the public through Twitter.

“So”, he wondered, “how could we go across the city quickly collecting as much data as possible?” Drones were his first thought. But it’s illegal to fly them over London. “But pigeons can fly above London, right?” he says. “They live—actually, they are Londoners as well. So, yeah, I thought about using pigeons equipped with mobile apps. And we can use not just street pigeons, but racing pigeons, because they fly pretty quickly and pretty low.”

So it might be time for Londoners to have more respect for their pigeons. The birds may just be helping to improve the quality of the city’s air.

Look out, Einstein, a robot wants your job! This robot, named Adam, may be the first non-human to ever independently think up and test hypotheses in order to discover new scientific knowledge. Adam’s discoveries so far have something to do with yeast genetics — not nearly as mind-blowing as Einstein’s theories on relativity, but still impressive when you realize that nobody told Adam which yeast gene to study. “Adam makes up its mind about what to do,” Rose King of Aberyth University in the United Kingdom, the robot’s creator, told CBC News in Canada. “It decides what experiments to do and what to test.”

Of course, Adam’s choices are limited by the information King feeds it and the lab equipment it has access to. The physical robotic system includes robotic arms, a freezer, fans and equipment useful for biological research. Adam also has loads of data on yeast and other organisms.

To decide what to do, Adam finds a place where the yeast genetic data is incomplete, and then searches for complete information about similar genes in other organisms. By comparing all of this data, Adam is able to form a hypothesis and start experimenting. Adam can bring up to 1,000 new experiments each day.

Why Yeast? Biologists use this simple organism as a model for more complex ones, like human cells. So far, Adam has figured out the functions of 12 different yeast genes. When King and his team tested Adam’s results, everything was correct. Eventually, Adam will be able to move beyond yeast as long as King uploads the data necessary for new experiments. King’s team has also built a new robotic scientist named Eve. This robot will screen new drugs for diseases like malaria.

Robotics has been useful in scientific laboratories for a long time, but usually the machines just do the work and deal with data that humans have to sort through. This is the first time a robot has not only designed its own experiment, but determined its own results! Still, modern Einsteins should not worry about being replaced. Robot scientists like Adam are much more likely to be lab assistants rather than brilliant theorists.