Tech giants are pouring money into artificial intelligence. Baidu and Google spent between $20 and $30 billion on AI in 2016 alone, according to research from McKinsey. In Google's case, a portion of that investment went to AI centers in China and France, and the Mountain View company shows no signs of slowing down. Today, Google announced its next AI research center will be in Accra, Ghana. "In recent years, we've … witnessed an increasing interest in machine learning research across the continent," senior Google AI fellow Jeff Dean and staff research scientist Moustapha Cisse wrote in a blog post.

Moving to a new country can be hard. You don't know the language. Cultural differences create conversational landmines. And you just can't be sure that everyone will like you. As it turns out, that as true for people as it is for Amazon's Alexa voice assistant, which officially sets up residence in France today.

AI is an area of computer science dedicated to creating software that can be taught to perform complex procedures. What makes AI "intelligent" is that it can learn new behaviours, improve performance as more experience is gained, and make decisions and predictions based on available data. The algorithms at the core of some AI systems are trained using the large datasets that are now available thanks to the "big data" revolution. It is the intelligent capabilities of AI systems that allow for the automation of tasks that until now required human judgement to deliver. There is enormous potential for how AI can benefit the developing world and what it can contribute towards achieving the UN's Sustainable Development Goals: AI can play a crucial role in augmenting healthcare capacity by filling gaps in human expertise, increasing productivity, and enhancing disease surveillance.

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.