An "AI writing robot" produced up to 58 articles per day for a Chinese publication at the Olympic Games in Rio de Janeiro this month. The Xiaomingbot wrote reports for the news syndication service Toutiao, delivering news items within two minutes of events ending. During the two weeks of the Olympics, the robot reporter produced a total of 450 stories. Xiaomingbot is not the first artificial intelligence (AI) reporter, though the quantity of reports makes it arguably the most prolific. The articles--ranging from around 100 words to 821 articles--appear to have been well received by readers, though some comments seen by Quartz reportedly claimed the prose was "too robotic."

In this special guest feature, Cecilia Pizzurro, Senior Director, Strategic Data Projects at LOGICnow, discusses the convergence of data/machine learning and cybersecurity, and the idea that these two are playing off of each other in a more meaningful way than ever before. Cecilia leads a team of data scientists and software engineers in Cambridge (US) and Newcastle (UK). These teams use machine learning and big data analytics to find business value in the vast amount of customer data gathered from LOGICnow's products. She was also the co-founder and CTO of the The Dolomite Group, a South American mining consortium, pioneering machine learning and big data analyses to improve mining efficiency and reduce environmental impact in Peru. This company is currently finalizing its acquisition by a Chilean mining company.

Why can't computers watch the Earth from above and automatically map our roads, buildings, and trash heaps? Satellite operator DigitalGlobe is teaming up with Amazon, the venture arm of the CIA, and chipmaker Nvidia to try to make it happen. In a joint project, DigitalGlobe today released satellite imagery depicting the whole of Rio de Janeiro to a resolution of 50 centimeters. The outlines of 200,000 buildings inside the city's roughly 1,900 square kilometers have been manually marked on the photos. The SpaceNet data set, as it is called, is intended to spark efforts to train machine-learning algorithms to interpret high-resolution satellite photos by themselves.

A consortium of companies, including DigitalGlobe, CosmiQ Works and NVIDIA, today launched SpaceNet, an open-data initiative aimed at improving image analysis tools. The data are being hosted by Amazon Web Services as part of a partnership. With an increase in the number of CubeSats, high-resolution satellites and drones of every shape and size, we have accumulated petabytes of imagining data that can be processed with analytics to solve myriad problems. DigitalGlobe, which operates imaging satellites, has built out partnerships with companies like Facebook to target rural villages with internet access using photography as a guide. Satellite imaging has also been analyzed to help the Navy find Somali pirates, crowdsource the hunt for Malaysia Airlines flight 370 and identify deforestation zones.

It sounds like something out of a sci-fi film - an AI that constantly monitors the Earth, looks for unusual activity. However, CosmiQ Works, a division of the CIA's venture arm, has revealed SpaceNet, a project with Amazon, satellite mapping firm DigitalGlobe and chip firm Nvidia to train algorithms to work out what's happening on our planet. The project will create a giant online database of hi-res images that AIs will be able to use to teach themselves - and started with images of Rio during the Olympics. SpaceNet will launch with an initial contribution of DigitalGlobe multi-spectral satellite imagery and 200,000 curated building footprints across the city of Rio de Janeiro, Brazil. 'Each minute something is happening in the world,' said said Tony Frazier, Senior Vice President at DigitalGlobe.

Why can't computers watch the Earth from above and automatically map our roads, buildings, and trash heaps? Satellite operator DigitalGlobe is teaming up with Amazon, the venture arm of the CIA, and chipmaker Nvidia to try to make it happen. In a joint project, DigitalGlobe today released satellite imagery depicting the whole of Rio de Janeiro to a resolution of 50 centimeters. The outlines of 200,000 buildings inside the city's roughly 1,900 square kilometers have been manually marked on the photos. The SpaceNet data set, as it is called, is intended to spark efforts to train machine-learning algorithms to interpret high-resolution satellite photos by themselves.

This artist's impression shows the planet Proxima b orbiting the red dwarf star Proxima Centauri, the closest star to the Solar System. The double star Alpha Centauri AB also appears in the image between the planet and Proxima itself. Proxima b is a little more massive than the Earth and orbits in the habitable zone around Proxima Centauri, where the temperature is suitable for liquid water to exist on its surface. It was just over 20 years ago--a blink of a cosmic eye--that astronomers found the first planets orbiting stars other than our Sun. All these new worlds were gas-shrouded giants like Jupiter or Saturn and utterly inhospitable to life as we know it--but for years each discovery was dutifully reported as front-page news, while scientists and the public alike dreamed of a day when we would find a habitable world. An Earth-like place with plentiful surface water, neither frozen nor vaporized but in the liquid state so essential to life. Back then the safe bet was to guess that the discovery of such a planet would only come after many decades, and that when a promising new world's misty shores materialized on the other side of our telescopes, it would prove too faraway and faint to study in any detail.

One way to solve lasso problems when the dictionary does not fit into available memory is to first screen the dictionary to remove unneeded features. Prior research has shown that sequential screening methods offer the greatest promise in this endeavor. Most existing work on sequential screening targets the context of tuning parameter selection, where one screens and solves a sequence of $N$ lasso problems with a fixed grid of geometrically spaced regularization parameters. In contrast, we focus on the scenario where a target regularization parameter has already been chosen via cross-validated model selection, and we then need to solve many lasso instances using this fixed value. In this context, we propose and explore a feedback controlled sequential screening scheme. Feedback is used at each iteration to select the next problem to be solved. This allows the sequence of problems to be adapted to the instance presented and the number of intermediate problems to be automatically selected. We demonstrate our feedback scheme using several datasets including a dictionary of approximate size 100,000 by 300,000.

Naturalist Charles Darwin believed the expanse of open ocean in the Pacific was an'impassable barrier' that separated species living on its east and west coasts. This, he argued, accounted for the differences seen in animals on each side of the ocean in much the same way as a mountain range or a desert may split habitats and lead to different species evolving on either side. Now researchers have proved him correct after showing that coral living in the eastern tropical Pacific are completely isolated from the rest of the ocean. Researchers have simulated how coral larvae spread across the Pacific Ocean using computer simulations. While coral themselves are invertebrates that form large static reefs fixed in place by their hard exoskeletons, they can spread by producing swarms of larvae that can colonise new areas.

The idea for Prime Minister Shinzo Abe's surprising "Super Mario" appearance at the closing ceremony of the Rio de Janeiro Olympics came originally from former Prime Minister Yoshiro Mori, now president of the 2020 Tokyo Olympics organizing committee. The behind-the-scenes story was disclosed by Toshiro Muto, director-general of the committee. "I hear he (Abe) willingly accepted our request when we told him he was the most suitable person to go on stage to raise publicity for the 2020 Games," Muto said Monday. At the Rio closing ceremony Sunday, Abe popped up from a huge green pipe, dressed as Mario from Nintendo Co.'s popular "Super Mario Bros." video game franchise. Tokyo 2020 organizers said in a statement that the idea came up during a brainstorming session.