Parallel sentence extraction is a task addressing the data sparsity problem found in multilingual natural language processing applications. We propose a bidirectional recurrent neural network based approach to extract parallel sentences from collections of multilingual texts. Our experiments with noisy parallel corpora show that we can achieve promising results against a competitive baseline by removing the need of specific feature engineering or additional external resources. To justify the utility of our approach, we extract sentence pairs from Wikipedia articles to train machine translation systems and show significant improvements in translation performance.

Video-game players generate huge amounts of data, as everything they do within a game is recorded. In particular, among all the stored actions and behaviors, there is information on the in-game purchases of virtual products. Such information is of critical importance in modern free-to-play titles, where gamers can select or buy a profusion of items during the game in order to progress and fully enjoy their experience. To try to maximize these kind of purchases, one can use a recommendation system so as to present players with items that might be interesting for them. Such systems can better achieve their goal by employing machine learning algorithms that are able to predict the rating of an item or product by a particular user. In this paper we evaluate and compare two of these algorithms, an ensemble-based model (extremely randomized trees) and a deep neural network, both of which are promising candidates for operational video-game recommender engines. Item recommenders can help developers improve the game. But, more importantly, it should be possible to integrate them into the game, so that users automatically get personalized recommendations while playing. The presented models are not only able to meet this challenge, providing accurate predictions of the items that a particular player will find attractive, but also sufficiently fast and robust to be used in operational settings.

It sure is fascinating to watch Assassin's Creed reinvent itself. A series that was by and large stagnant for years--even going so far as to return to older design tropes with Unity--it now seems determined to evolve into something entirely new. Something that, if we're being honest, quite resembles (at least on the surface) The Witcher 3. Last year's Assassin's Creed: Origins was the first step in this process, removing the series from the cities it had outgrown and putting it in a vast, detailed recreation of Ptolemaic Egypt, and then filling Egypt with mysteries big and small. It continues in 2018's Assassin's Creed: Odyssey ($60 preorder on Amazon), as for the first time ever the series adds dialogue trees. Ubisoft is determined to turn Assassin's Creed into a full-fledged RPG, and damn it's exciting.

With the kickoff of the 2018 FIFA World Cup fast approaching, every soccer fan in the world is dying to know: Who will capture the coveted trophy? If you're not just a soccer fan but also a techie, I guess you have realized that Machine Learning and Artificial Intelligence are presently buzzwords too. Let us combine these two to predict which country will win the FIFA World Cup. Disclaimer: This should in no way be used for betting or any financial decision. Should you choose to, who am I to stop you.(just

Ubisoft's most-spotlighted (and most-leaked) game of E3 was definitely Assassin's Creed Odyssey, a new entry in the game that is…going back to making the series an annual franchise, even if Ubisoft said they were steering away from that. While Odyssey looks a lot like an Origins reskin, this time set in ancient Greece, it's going pretty hard into full-on RPG territory, complete with individual pieces of armor with different rarities, dialogue trees and even romance options for your character, where you can play as either the male Alexios or female Kassandra, both angling to become Spartan legends. What has been consistently weird about Assassin's Creed Odyssey is that other than looking like an Assassin's Creed game, there are almost no traces of…Assassins at all, at least as we've come to know them. There is an "assassin" skill tree, but that's a lower case "a" along with hunter and warrior skill trees. The only thing that seems remotely connected to the Assassin's Creed universe at all is that it seems pretty clear that your treasured weapon, the spear of Leonidas, is a Piece of Eden, giving you supernatural powers in combat.

As many as 42% of pediatric clinical trials end up in failure and inconclusive results. "That means we don't know one way or the other if a drug works or not," says Aparito founder Elin Haf Davies. This isn't just a problem for the big pharma companies who are spending billions of dollars developing successful studies. It's a problem for you, the patient, who pays a mark up on medication to cover these costs--and for taxpayers supporting healthcare services like the NHS. "Society as a whole is losing out," notes Davies, a former research nurse for medical institutions like London's Great Ormond Street Hospital.

Not long before Google announced it would end one part of its AI work for the U.S. military, the company's Cloud team was pitching artificial intelligence and machine learning tools to members of the U.S. special operations community, the soldiers very much at the front lines of combat in places like Syria, Iraq, Afghanistan, and Africa. The pitches were part of Google's sales work at the SOFIC convention, which draws special operators from around the world to Tampa, Florida, each May. A document distributed at a May 24 sales presentation touts Google Cloud and associated AI capabilities as useful for some of special operations forces' most important work. Defense One obtained a copy of the document. One sheet describes how the tools can help with sensitive site exploitation, or SSE.

In sub-Saharan Africa, home electricity is a 50-50 prospect and bank accounts can be rare, but most people have some kind of cellphone. The phones provide information often tough to come by in rural areas--the latest commodity prices, for example. And even in places where pastoral tribesmen tend livestock in very old-school ways, they may also chat over WhatsApp and use money-transfer apps to settle debts. To charge the phones without access to an electrical grid, Africans spend more than $17 billion a year on such fuels as kerosene and firewood to power sometimes primitive generators. Simon Bransfield-Garth is pitching a cleaner and, he says, smarter alternative.

Understanding the representational power of Restricted Boltzmann Machines (RBMs) with multiple layers is an ill-understood problem and is an area of active research. Motivated from the approach of \emph{Inherent Structure formalism} (Stillinger & Weber, 1982), extensively used in analysing Spin Glasses, we propose a novel measure called \emph{Inherent Structure Capacity} (ISC), which characterizes the representation capacity of a fixed architecture RBM by the expected number of modes of distributions emanating from the RBM with parameters drawn from a prior distribution. Though ISC is intractable, we show that for a single layer RBM architecture ISC approaches a finite constant as number of hidden units are increased and to further improve the ISC, one needs to add a second layer. Furthermore, we introduce \emph{Lean} RBMs, which are multi-layer RBMs where each layer can have at-most $O(n)$ units with the number of visible units being n. We show that for every single layer RBM with $\Omega(n^{2+r}), r \ge 0$, hidden units there exists a two-layered \emph{lean} RBM with $\Theta(n^2)$ parameters with the same ISC, establishing that 2 layer RBMs can achieve the same representational power as single-layer RBMs but using far fewer number of parameters. To the best of our knowledge, this is the first result which quantitatively establishes the need for layering.

I'll never forget the time I watched the trailer for 300, the iconic fantasy war film from 2006 about King Leonidas of Sparta and his clash against the Persians with a heavily outnumbered army. As soon as I saw the scene where Leonidas, played by Gerard Butler, screamed "This is Sparta" at the top of his lungs and then kicked a dude down a deep concrete well, I knew the movie was going to be an instant classic. Less than a year after touring Egypt with Origins, Ubisoft is taking us to King Leonidas' world in Assassin's Creed: Odyssey. The new game takes place in 431BC, right at the start of the Peloponnesian war between the competing cities of Sparta and Athens. As these two empires fight to establish broader power, your play as a young Spartan mercenary who goes on quest to help his people defeat the Athenians.