US law enforcement has sentenced seven criminals who were part of an online fraud ring which duped victims out of their cash through romance, shopping and job opportunity scams. On Wednesday, the US Department of Justice (DoJ) said that Chief U.S. District Judge Louis Guirola Jr. of the Southern District of Mississippi sentenced seven citizens for their roles in online fraud schemes, which included counterfeit checks, "mystery shopper" websites and fake work-from-home jobs. According to Assistant Attorney General Leslie Caldwell, all seven were members of a "large scale" international fraud ring which also used online dating sites as a platform to coax lonely hearts out of their money. In addition, fraudulent mystery shopper and personal assistance job opportunities were ran, in which victims -- believing they had legitimate work -- would be sent checks and instructions for various assignments. The checks, which were counterfeit, would bounce after the criminal ring received funds from victims, destined to be laundered in the US before transferring over to Nigeria.

Three military veterans once involved in the U.S. drone program have thrown their support behind a Yemeni man's legal fight to obtain details about why his family members were killed in a 2012 strike. The former soldiers' unusual decision to publicly endorse the lawsuit against President Obama and other U.S. officials adds another twist to Faisal bin Ali Jaber's four-year quest for accountability in the deaths of his brother-in-law and nephew, who he believes needlessly fell victim to one of the most lethal covert programs in U.S. history. The former enlisted service members told the U.S. Court of Appeals for the District of Columbia Circuit in a recent filing that they believe the 2012 drone strike serves as a case study of how mistakes frequently occur in the nation's targeted-killing program, where life-or-death decisions are based upon top-secret evidence. The veterans say they "witnessed a secret, global system without regard for borders, conducting widespread surveillance with the ability to conduct deadly targeted killing operations." Though the veterans did not disclose any personal knowledge of the strike that is alleged to have killed Jaber's relatives, they claim the military frequently labels the deaths of unknown victims as "enemy kills."

Since 1990, extreme poverty has been cut in half worldwide. But there are still more than 700 million people living on less than two dollars a day around the globe. The United Nations has made the elimination of poverty number one on its list of 17 Sustainable Development Goals by 2030, a challenge that may sound impossible but that a team of Stanford University researchers believe could actually be well within reach. That's because they've come up with a cost-effective method of getting over one of the most difficult, if not most obvious, hurdles toward reaching that goal on time. "Poverty is this big problem that everybody wants to solve, but you can't even begin to work on it if you don't know where the poor are," said Neal Jean, a doctoral student and lead author of the Stanford research.

Enterprises collect large amounts of data and analyze it to obtain a competitive advantage. Some are using machine learning techniques to create predictive applications for fraud detection, demand forecasting, click prediction, and other data-intensive analyses. Recent advancements in machine learning make it possible to go even further, bringing deep learning within reach of developers everywhere. Now, computer vision, speech recognition, natural language processing, and audio recognition applications are being developed to give enterprises a competitive advantage. Processing large amounts of data for deep learning requires large amounts of computational power.

One of the ironies of cloud computing is that, the more its cookie-cutter architecture allows it to scale, then the more it becomes possible to reintroduce diversity into that architecture. While cloud computing's early successes came from working out how to automatically manage serried ranks of identical general-purpose commodity computers, the vast scale that providers have now reached makes it economically and operationally viable to introduce pools of specialized computing into that infrastructure. Nowhere is this more pertinent than in the analysis of huge volumes of data, in applications such as big data and, increasingly, machine learning. In search of high performance in these applications, the leading cloud providers are investing in increasingly esoteric processor technologies, even to the extent of custom-building their own designs, as both Google and IBM are known to have done, while Microsoft and Amazon are thought to be doing the same -- perhaps also Apple and Facebook. Google's Tensor Processing Unit (TPU) is a case in point.

Artificial intelligence is set to challenge traditional technologies in financial services, if the startups that demoed at BBVA Open Talent in New York today are any indication. The BBVA Open Talent Challenge is part of Next Money NYC. Today's event is one of three regional finals, from which a few lucky winners will get the chance to work with BBVA. Consult Hyperion and NYPAY are also partners of the Next Money events, formerly known as Next Bank. More than half of the companies that presented in the first session used or mentioned AI, which is an umbrella term that covers a number of technologies used to manage data, often employing the ability to "learn" or change behavior based on trends in data.

We'd forgive you for immediately imagining a character out of I, Robot when we mention the term'artificial intelligence', but it does in fact describes when a machine perceives its surrounding environment and takes actions accordingly. Well, that's exactly what we do in the digital marketing world when we test and improve our campaigns. Once upon a time digital copywriters would write their own calls to action at the end of blog posts and direct users towards relevant blog content that they might be interested in based on the article they had just read. Well, personalised calls to action convert 42% better than generic ones. Now content suggestions can be computer generated and personalised to each reader based on their internet history, in the same way similar products may appear at the bottom of a product page.

The Guardian has launched a news chatbot on Facebook Messenger in a further experimentation with the format that it first used to share recipes this summer. A chatbot is a computer programme that a user can interact with in a conversational, human way. The idea being that you can ask it any question and it will give you the answer. Send a message to the Guardian on Facebook Messenger, whatever it may be, and you'll be met with a polite response from the "prototype chatbot" asking if you want a daily news briefing. Say "yes" and it will ask you what time you want it delivered in the morning and whether you'd like to see the headlines or the most popular stories of the moment.

Tennis fans watching the U.S. Open at home or in person this year will get some extra insights delivered by IBM's machine learning technologies. "The way we're thinking about it is: the first time Watson's come to the U.S. Open," says IBM program manager John Kent. IBM is using its cloud-based data-processing tools, including the Watson machine learning suite, to enhance its online videos by automatically generating everything from video captions to automated analyses of ongoing matches. During each match, IBM's online SlamTracker platform provides real-time scores and assessments, pulling in data from officials and on-court speed tracking radar to evaluate players' moves as they happen. "We not only provide the real-time scores, but for each point, try to provide a little bit of insight as to what happened," Kent says. For example, the system can indicate on which areas of the court each player won the most points, how many feet each player moved over the course of a match, and which points were won by unforced error.

IBM's artificial intelligence programme obviously reached the pinnacle when it guest-edited an issue of the The Drum magazine but now it has also conceived the world's first ever movie trailer composed by an AI (trailer above - behind the scenes follows). Watson was fed the trailers of more than 100 horror films to help it identify the normative structure and path in the horror genre. It embarked on a visual, audio, and composition analysis of these clips, categorising the variables and generating the movie using probabilities once it gained an understanding of the genre. The tricky part was teaching the machine the tropes involved in cutting the trailers, from moments of terror, suspense and more using sequential clips from the movie, making the most of audio and visual cues. John R Smith of IBM said: "There are patterns and types of emotions in horror movies that resonate differently with each viewer, and the intricacies and interrelation of these are what an AI system would have to identify and understand in order to create a compelling movie trailer. "Our team was faced with the challenge of not only teaching a system to understand, 'what is scary', but then to create a trailer that would be considered'frightening and suspenseful' by a majority of viewers.