Everything is more extreme on the moon. On top of temperatures that range from -300 F to 224 F, future astronauts and probes must deal with lighting conditions generously described as "harsh." To help, researchers at Ames Research Center in Silicon Valley created a lunar testbed, complete with craters, fluffy dust and solar simulator lights. The goal is to develop sensors that can "see" in such conditions to help probes and, eventually, humans navigate the surface safely. With no atmosphere to scatter and reflect lighting, "what you get on the Moon are dark shadows and very bright regions that are directly illuminated by the Sun -- the Italian painters in the Baroque period called it chiaroscuro," says NASA Ames computer scientist Uland Wong.

The Somalia-based al-Shabab earlier this month mocked Trump for the first time in a video that called him a "brainless billionaire." The extremist group also has vowed to step up attacks in Somalia after the president elected in February declared a new offensive against al-Shabab, which continues to carry out deadly attacks in the capital, Mogadishu.

FILE - In this file photo dated Tuesday, Oct. 14, 2014, Serbia's Stefan Mitrovic grabs a banner containing the Albanian flag attached to a drone flying above the pitch during the Euro 2016 Group I qualifying match between Serbia and Albania in Belgrade, Serbia. The banner prompted fan violence with the match was suspended, and a man who claims to have flown the drone has been detained but it is revealed Saturday July 29, 2017, that Albania's soccer federation is calling on Albanian authorities to stop his extradition to Serbia.

Artificial intelligence, more commonly known under AI acronym, has become a very hot topic these days. Forrester Research forecasts a 300 percent growth of AI investment this year. Toyota invests $100 million in fund for AI, UBS is trying to bring AI to its investment bank's operations, while VCs frivolously dream of replacing all of us with AI to cut costs. Some people even feel embarrassed because they have never used or implemented AI in their office or home. Obviously, many cybersecurity vendors leverage the term in an attempt to increase sales and impress their customers.

Artificial intelligence is fast changing the world. The premise that intelligent machines will perform tasks more efficiently and at a lower cost than human beings is by no means far-fetched. The challenges facing the workers of the future are multiplying before our very eyes. Some of the most vulnerable jobs in the transition to automation, robotics and artificial intelligence are related to transport, mechanical work in factories and customer service. But no sector, be it health, finance or even the military, is excluded.

After Meg Whitman dismissed speculation that she is replacing Travis Kalanick as Uber's CEO, the board is struggling to find someone to fill the company's top spot. Amidst the disorganization of the board, Kalanick continues to meddle despite the fact that he stepped down in June, according to Recode. The outlet reported that Kalanick has been telling people that he is'Steve Jobs-ing it', a reference to the Apple founder who was fired and then returned to the company. Sources have said Kalanick is trying to stay involved in daily operating decisions and is having a difficult time letting go of the company. Top executives are now hoping they can look to the board for help, the outlet said.

Welcome to the new week. Over the weekend, we talked about our new robot friends, HTC's return to flagship smartphone form and fines for walking while texting -- if you're in Honolulu. They only want your love (and occasionally some anonymized metadata.) Who needs friends when robots are this sociable? From social robots to military tools, where do you draw the line? How do you add personality to a robot, and why would you?

From the Australian government's new "data-driven profiling" trial for drug testing welfare recipients, to US law enforcement's use of facial recognition technology and the deployment of proprietary software in sentencing in many US courts … almost by stealth and with remarkably little outcry, technology is transforming the way we are policed, categorized as citizens and, perhaps one day soon, governed. We are only in the earliest stages of so-called algorithmic regulation -- intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws -- but it already has profound implications for the relationship between private citizens and the state. Furthermore, the rise of such technologies is occurring at precisely the moment when faith in governments across much of the Western world has plummeted to an all-time low. Voters across much of the developed world increasingly perceive establishment politicians and those who surround them to be out-of touch bubble-dwellers and are registering their discontent at the ballot box. In this volatile political climate, there's a growing feeling that technology can provide an alternative solution.

BRITAIN'S brightest minds have asked the government to step in and protect vulnerable Britons from the rise of artificially intelligent machines. The Royal Society say that super smart computers which can "learn" and make better decisions than humans will be released within five years time. These machines will help teach our children, nurse the sick and improve social services. They're likely to be driving our cars, pulling our pints and even cooking our dinners, too. But there's a danger that they will create huge inequality across our nation, threatening the very fabric of society.

Two-sample feature selection is the problem of finding features that describe a difference between two probability distributions, which is a ubiquitous problem in both scientific and engineering studies. However, existing methods have limited applicability because of their restrictive assumptions on data distributoins or computational difficulty. In this paper, we resolve these difficulties by formulating the problem as a sparsest $k$-subgraph problem. The proposed method is nonparametric and does not assume any specific parametric models on the data distributions. We show that the proposed method is computationally efficient and does not require any extra computation for model selection. Moreover, we prove that the proposed method provides a consistent estimator of features under mild conditions. Our experimental results show that the proposed method outperforms the current method with regard to both accuracy and computation time.