After fifty years of books, games and movies, what more could the Aliens franchise deliver? The description "genre-defying" gets thrown around a lot these days - it is a convenient sticking plaster for any film or series that hasn't quite figured out what it wants to be. That said, it is an apt term for the Alien franchise. Ridley Scott's 1979 movie Alien, in which Ellen Ripley (Sigourney Weaver) is part of a crew trapped on a spaceship with a salivating, scorpion-like "xenomorph", had such blood-curdling visuals that it made an indelible impact on both science fiction and horror films. But while the deadly parasite and its psychosexual torment were ever present, subsequent instalments tried their hand at being everything from a blockbuster to a prison flick to a philosophical drama.

As far back as the 19th century, soothsayers have been promising and warning against it in equal measure. While we have yet to achieve a post-scarcity utopia or descend into a robot-ruled wasteland, year upon year, little by little, many of those predictions have jumped from the pages of sci-fi novels and into news headlines as ever-increasing computing power turns future fantasies into tangible reality. From law enforcement to medicine and visual arts to weaponry, the real-world impacts of AI are already being felt. Tech's best and brightest are hard at work trying to streamline the songwriting process or replace it altogether: Splice's Similar Sounds uses AI to scan thousands of samples before offering the best kick to complement your snare; Orb's Producer Suite generates rhythms, melodies and chord progressions to help you get started on a track; and services like Amper need only a few keywords to create fully realised background music. So, are composers and songwriters staring into the void of their own obsolescence?

Neural machine translation systems are often optimized to perform well for specific text genres or domains, such as newspaper articles, user manuals, or customer support chats. In industrial settings with hundreds of language pairs to serve, however, a single translation system per language pair, which performs well across different text domains, is more efficient to deploy and maintain. Additionally, service providers may not know in advance which domains customers will be interested in. At this year's Conference on Empirical Methods in Natural Language Processing (EMNLP), we are presenting a new approach to multidomain adaptation for neural translation models, or adapting an existing model to new domains while maintaining translation quality in the original domain. Our approach provides a better trade-off between performance on old and new tasks than its predecessors do.

Artificial intelligence (AI) is a wide-ranging branch of computer science that is concerned with building smart machines that have the capability of performing tasks requiring human intelligence. This technology is likely to progress in near future. Artists create new forms of art by using AI while in museums it is used to create immersive experiences. Everyone is curious and talks about artificial intelligence. Today, this technology is in trend.

The introduction of new technologies such as Artificial Intelligence (AI) is causing ripples in the art market and whilst not everyone in the industry is prepared to embrace it, there is no denying its impact. Artificial intelligence is changing value chains for creative content, helping creators match content with audiences by classifying their interests and enabling them to recommend specifically tailored content. Various art platforms are using this technology, creating a filtering system to help their users. AI is also now being used to create works of art. In 2017 experts in the Artificial Intelligence Laboratory at Rutgers University in New Jersey created CANs (Creative Adversarial Networks) that allow for AI to create physical works that appear to be human-crafted.

The nightmare scenario for computer security – artificial intelligence programs that can learn how to evade even the best defenses – may already have arrived. That warning from security researchers is driven home by a team from IBM Corp. who have used the artificial intelligence technique known as machine learning to build hacking programs that could slip past top-tier defensive measures. The group will unveil details of its experiment at the Black Hat security conference in Las Vegas on Wednesday. State-of-the-art defenses generally rely on examining what the attack software is doing, rather than the more commonplace technique of analyzing software code for danger signs. But the new genre of AI-driven programs can be trained to stay dormant until they reach a very specific target, making them exceptionally hard to stop.

The nightmare scenario for computer security - artificial intelligence programs that can learn how to evade even the best defenses - may already have arrived.

IBM has uncovered the existence of artificial intelligence-based hacking programs that can get past top-tier defensive measures. At the Black Hat security conference in Las Vegas this week, IBM revealed the existence of a variety of artificial intelligence (AI) hacking programs that could get past top-tier defensive measures. IBM researchers say the AI-driven programs can be trained to remain dormant until they reach a specific target. A demonstration of IBM's DeepLocker software exploited publicly available photos of a target in conjunction with a hacked version of videoconferencing software that activated only when it detected the target's face. Stoecklin, "We have a lot of reason to believe this is the next big thing. This may have happened already, and we will see it two or three years from now."

SAN FRANCISCO (Reuters) - The nightmare scenario for computer security - artificial intelligence programs that can learn how to evade even the best defenses - may already have arrived. That warning from security researchers is driven home by a team from IBM Corp. (IBM.N) who have used the artificial intelligence technique known as machine learning to build hacking programs that could slip past top-tier defensive measures. The group will unveil details of its experiment at the Black Hat security conference in Las Vegas on Wednesday. State-of-the-art defenses generally rely on examining what the attack software is doing, rather than the more commonplace technique of analyzing software code for danger signs. But the new genre of AI-driven programs can be trained to stay dormant until they reach a very specific target, making them exceptionally hard to stop.

Anyone who has watched coverage of a festival or sports event in the last few years will probably have witnessed commercial drone use -- in the form of breathtaking aerial footage. But a collaboration of universities, research institutes and broadcasters is looking to take this to the next level by using a small swarm of intelligent drones. The EU-funded MULTIDRONE project seeks to create teams of three to five semi-automated drones that can react to and capture unfolding action at large-scale sports events. Project coordinator Professor Ioannis Pitas, of the University of Bristol, UK, says the collaboration aims to have prototypes ready for testing by its media partners Deutsche Welle and Rai – Radiotelevisione Italiana within 18 months. 'Deutsche Welle has two potential uses lined up – filming the Rund um Wannsee boat race in Berlin, Germany, and also filming football matches with drones instead of normal cameras – while Rai is interested in covering cycling races,' said Prof. Pitas.