Mr. Smith Goes to Washington 1939 TCM Tue. 7 p.m. Mean Streets 1973 Cinemax Sun. 6 a.m. Batman Begins 2005 AMC Sun. Throw Momma From the Train 1987 EPIX Sun. Die Hard 1988 IFC Sun. I Know What You Did Last Summer 1997 Starz Tue. Gone in 60 Seconds 2000 CMT Wed. 8 p.m., Thur. Total Recall 1990 Encore Thur. 2 a.m. A Fish Called Wanda 1988 Encore Thur. 2 p.m., 9 p.m. The World Is Not Enough 1999 EPIX Sat. 4 p.m. Look Who's Talking 1989 OVA Sun. Die Hard With a Vengeance 1995 IFC Thur. Oil-platform workers, including an estranged couple, and a Navy SEAL make a startling deep-sea discovery. A clueless politician falls in love with a waitress whose erratic behavior is caused by a nail stuck in her head. After glimpsing his future, an ambitious politician battles the agents of Fate itself to be with the woman he loves. To help a friend, a suburban baby sitter drives into downtown Chicago with her two charges and a neighbor. Two teenage baby sitters and a group of children spend a wild night ...

England fans know the drill all too well - the national team heads into a major international football tournament having qualified with a near-perfect record. Hopes are high, but then… well, you know what happens - lacklustre performances or penalty shoot-out heartbreak, followed by an early flight home. So what really determines the success or failure of a team going into a major international football tournament like the World Cup? Is it a side's quality (class) or its recent performances (form)? Reality Check has teamed up with the BBC's statistics department to try to answer one of the biggest debates in football - how much does form matter? To do this, we built a computer program that predicts football results by analysing ratings data.

On Thursday, Google released a document entitled "Artificial Intelligence at Google: Our Principles," vowing to avoid Pentagon projects to develop AI weapons. However, they'll continue to work with the US military on a host of other projects, including AI projects, so long as they don't include surveillance that runs counter to human rights. "Google is in a spot at the moment," Wallis, editor-at-large for Digital Journal and author of more than a dozen books, told Loud & Clear hosts John Kiriakou and Nicole Roussell. "This is gold rush time for artificial intelligence; everybody wants a piece of it, and we're not talking about the sort of generic type of artificial intelligence -- we're talking about possibly thousands or millions of different kinds of artificial intelligence." In other words, the advent of artificially intelligent weapons is "inevitable," Wallis said.

On Thursday, Google released a document entitled "Artificial Intelligence at Google: Our Principles," vowing to avoid Pentagon projects to develop AI weapons. However, they'll continue to work with the US military on a host of other projects, including AI projects, so long as they don't include surveillance that runs counter to human rights. "Google is in a spot at the moment," Wallis, editor-at-large for Digital Journal and author of more than a dozen books, told Loud & Clear hosts John Kiriakou and Nicole Roussell. "This is gold rush time for artificial intelligence; everybody wants a piece of it, and we're not talking about the sort of generic type of artificial intelligence -- we're talking about possibly thousands or millions of different kinds of artificial intelligence." In other words, the advent of artificially intelligent weapons is "inevitable," Wallis said.

Explaining automatically generated recommendations allows users to make more informed and accurate decisions about which results to utilize, and therefore improves their satisfaction. In this work, we develop a multi-task learning solution for explainable recommendation. Two companion learning tasks of user preference modeling for recommendation} and \textit{opinionated content modeling for explanation are integrated via a joint tensor factorization. As a result, the algorithm predicts not only a user's preference over a list of items, i.e., recommendation, but also how the user would appreciate a particular item at the feature level, i.e., opinionated textual explanation. Extensive experiments on two large collections of Amazon and Yelp reviews confirmed the effectiveness of our solution in both recommendation and explanation tasks, compared with several existing recommendation algorithms. And our extensive user study clearly demonstrates the practical value of the explainable recommendations generated by our algorithm.

With the world moving towards being increasingly dependent on computers and automation, one of the main challenges in the current decade has been to build secure applications, systems and networks. Alongside these challenges, the number of threats is rising exponentially due to the attack surface increasing through numerous interfaces offered for each service. To alleviate the impact of these threats, researchers have proposed numerous solutions; however, current tools often fail to adapt to ever-changing architectures, associated threats and 0-days. This manuscript aims to provide researchers with a taxonomy and survey of current dataset composition and current Intrusion Detection Systems (IDS) capabilities and assets. These taxonomies and surveys aim to improve both the efficiency of IDS and the creation of datasets to build the next generation IDS as well as to reflect networks threats more accurately in future datasets. To this end, this manuscript also provides a taxonomy and survey or network threats and associated tools. The manuscript highlights that current IDS only cover 25% of our threat taxonomy, while current datasets demonstrate clear lack of real-network threats and attack representation, but rather include a large number of deprecated threats, hence limiting the accuracy of current machine learning IDS. Moreover, the taxonomies are open-sourced to allow public contributions through a Github repository.

This document gives a knowledge-oriented analysis of about 20 interesting Recognizing Textual Entailment (RTE) examples, drawn from the 2005 RTE5 competition test set. The analysis ignores shallow statistical matching techniques between T and H, and rather asks: What would it take to reasonably infer that T implies H? What world knowledge would be needed for this task? Although such knowledge-intensive techniques have not had much success in RTE evaluations, ultimately an intelligent system should be expected to know and deploy this kind of world knowledge required to perform this kind of reasoning. The selected examples are typically ones which our RTE system (called BLUE) got wrong and ones which require world knowledge to answer. In particular, the analysis covers cases where there was near-perfect lexical overlap between T and H, yet the entailment was NO, i.e., examples that most likely all current RTE systems will have got wrong. A nice example is #341 (page 26), that requires inferring from "a river floods" that "a river overflows its banks". Seems it should be easy, right? Enjoy!

WASHINGTON – One U.S. special operations soldier was killed and four U.S. service members wounded in an "enemy attack" Friday in Somalia, the U.S. military said -- casualties that are likely to put renewed scrutiny on America's counterterror operations in Africa. It's the first public announcement of a U.S. military combat death on the continent since four U.S. service members were killed in a militant ambush in the west African nation of Niger in October. U.S. Africa Command said in a statement that U.S. troops with Somali and Kenyan forces came under mortar and small-arms fire in Jubaland, Somalia, at around 2.45 p.m. local time. One member of the "partner forces" was wounded. One of the wounded U.S. service members received sufficient medical care in the field, and the other three were medically evacuated for additional treatment.

A funny thing has happened to Google and Amazon on their path toward high-tech success: They have become crucial cogs in the U.S. national security establishment. Both companies are expanding teams of employees with security clearances to work on projects that include deploying artificial intelligence and building digital "clouds" to offering law enforcement facial recognition tools that can even read the mood of people caught on camera. The security establishment's embrace of Big Tech has ruffled the feathers of traditional defense contractors and roiled employee ranks, in Google's case, over whether the company is being drawn into what disguntled employees called "the business of war." Defense industry analysts say the Pentagon views Big Tech, and particularly Google with its deep bench of artificial intelligence researchers, as vital to the nation's future safety. "They are becoming a critical part of national security, without question," said Alexander Rossino, a senior principal research analyst at Deltek, a Herndon, Virginia, firm that offers software and services to defense?

International trade has dominated the global headlines recently. Much of the discussions have been focused on the threat of a trade war, the tit-for-tat tariffs, and the health of the global trade order. While extremely important, these conversations are missing a brighter side of international trade – how innovative technologies in the Fourth Industrial Revolution are transforming trade by making the processes more inclusive and efficient. The steam power revolution connected the world like never before. The invention of shipping containers laid the foundation for globalization.