Google's Deepmind AI has already learned how to best humans at Go, but now Deepmind's resources will be pointed at an entirely different game: Starcraft II. Blizzard just announced at Blizzcon that it is partnering with Google to open up Starcraft II as a research platform for those building AI programmers. "Blizzard will release an API early next year that will allow researchers and hobbyists around the world to build and train their own AI agents to play Starcraft II," said Oriol Vinyals, a research scientist at Google DeepMind. Rather than Google building an unstoppable Starcraft II machine on its own, Blizzard wants to give anyone the change to build their own AI bot using the upcoming API. Essentially, this framework serves as a testing ground for building and training new AIs -- it could lead to better AI in Starcraft II itself, or we could see better AI player coaches, or maybe just an unbeatable AI bot. "There's still a long way to go, but maybe we'll even see an agent take on the BlizzCon champion in a show match," Vinyals said.

Fraud is a big problem in the cellular networking market, and machine learning is one potential solution to the problem. Mathematics-based cyberdefence firm claims Antigena can teach itself to fight off new malicious intrusions -- without human involvement. Fraudulent usage of cellular networks costs the industry an estimated $38 billion a year, according to the 2015 Global Fraud Loss Survey by the Communications Fraud Control Association (CFCA), an international organization that promotes revenue assurance, loss prevention, and fraud control in the industry. The CFCA says fraudsters use methods including PBX hacking, subscription fraud, dealer fraud, service abuse, and account takeover to steal from service providers. Current fraud detection approaches in the industry rely on static rules with pre-set volume or frequency thresholds, said Ole J. Mengshoel, associate research professor in the Department of Electrical and Computer Engineering and director of the Intelligent and High-Performing Systems Lab at Carnegie Mellon University.

Google's DeepMind AI unit, which earlier this year achieved a breakthrough in computer intelligence by creating software that beat the world's best human player at the strategy game Go, is turning its attention to the sci-fi video game Starcraft II. The company said it had reached a deal with Blizzard Entertainment Inc., the Irvine, California-based division of Activision Blizzard, which makes the Starcraft game series, to create an interface to let artificial intelligence researchers connect machine-learning software to the game. London-based DeepMind, which Google purchased in 2014, has not said it has created software that can play Starcraft expertly -- at least not yet. "We're still a long way from being able to challenge a professional human player," DeepMind research scientist Oriol Vinyals said in a blog post Friday. But the company's announcement shows it's looking seriously at Starcraft as a candidate for a breakthrough in machine intelligence.

Google is slowly becoming (if it is not already) the go-to place for everyone who needs "smart" solutions to problems. However, researchers at Google's DeepMind may have found a way to make their AI smarter. This lets their artificial intelligence system recognize objects from a single example. Google DeepMind is the U.K.-based subsidiary of Alphabet, the parent company of Google. This is Google's not-so-secret lab for AI projects that range from translation and map guidance to machine learning.

Artificial intelligence ("AI") or cognitive computing involves the use of computer program code to control machines to mimic cognitive functions, such as learning, classification, and problem solving. AI is a technical field of computer science and includes machine learning and natural language processing. Machine learning is the ability to learn without being explicitly programmed. Machine learning uses pattern recognition and computational statistics to process a set of training data. The data can be represented by various graph and network structures.

Artificial intelligence is creeping into our daily lives in unexpected ways. It is not just transforming online services with innovations such as Apple's Siri voice recognition app, which will send emails when you instruct it to, or Microsoft's Skype translation services, which enable you to communicate online with people whose languages you do not speak. Wider applications of artificial intelligence, such as image and pattern recognition (classifying data or objects based on common features), natural language processing (how computers understand and respond to human speech) and machine learning (when software learns something without being programmed to do so) will soon be featuring in many products and services. Pest control In recent years, pest control company Rentokil Initial has been experimenting with rodent traps equipped with sensors and WiFi. These send data to a command centre, which the company has built with partners Google and PA Consulting.

It's no secret that Elon Musk, the modern day mad scientist behind SpaceX and Tesla, is a bit wary about the future of artificial intelligence. He recently took to Twitter to weigh in on the fairly widespread internet outage that occurred earlier this month, thanks to a hack on Dyn, a company that monitors traffic for a lot of the major websites. Only a matter of time before advanced AI is used to do this. Internet is particularly susceptible to a gradient descent algo. This isn't the first time that Musk has had some dark prognostications about how AI could go awry.

Tesla Motors and SpaceX founder Elon Musk added to his warnings of a dystopic future straight out of a "Terminator" film on Thursday in a Twitter post on the dangers of artificial intelligence (AI). Citing an article in The Economist on a recent cyberattack preventing internet users from reaching the sites of Twitter, PayPal, Netflix and hundreds of other companies, Musk tweeted that it's "only a matter of time before advanced AI is used to do this." Musk's aversion to autonomous technologies may come as a surprise--his previous comments on the matter aside--for those following his company's embrace of self-driving auto technology, which it plans to roll out next month. Musk has also founded a non-profit called OpenAI dedicated to "democratizing AI technology." Two years ago, Musk called for more regulatory oversight of the technology area, which he described in an interview with the Massachusetts Institute of Technology's AeroAstro Department head Jaime Peraire as humanity's "biggest existential threat."

Their model requires groups of sentences in order to train, and so trained on the BookCorpus Dataset. The dataset consists of novels by unpublished authors and is (unsurprisingly) dominated by romance and fantasy novels. This "bias" in the dataset will become apparent later when discussing some of the sentences used to test the skip-thought model; some of the retrieved sentences are quite exciting! Building a model that accounts for the meaning of an entire sentence is tough because language is remarkably flexible. Changing a single word can either completely change the meaning of a sentence or leave it unaltered.

Would you like to translate terabytes of data into unforgettable holidays for millions of people around the globe? Booking.com, the world's largest accommodation booking website, is looking for rock star Data Scientists to add to join our highly successful Personalization Team within the Front End department. This product development team crunches endless amounts of data to provide our customers with the best possible experience. They focus on anything from understanding and predicting market data, to ranking all properties on our website, and providing our customers with the most relevant personalized recommendations. As a Data Scientist you'll work side by side with Developers, Designers and Product Owners, and take full ownership of your work – from the initial idea-generation phase to the implementation of the final product on our website. Our ideal candidate is result-focused, innovative and has solid quantitative background and a good business understanding.