Like lots of people who've cut cable TV, I couldn't have done it without Netflix. For a fraction of a typical cable bill, Netflix provides more TV shows, movies, and comedy specials than I have time to watch. And while I sometimes turn to other streaming services (and my over-the-air antenna) for specific content, most evenings I'll just thumb through the Netflix app until I find something that grabs my attention. Apart from not supporting 4K resolution or a voice-control remote control, Roku's latest streaming stick delivers the best price/performance ratio of any media-streaming device on the market. This is precisely how Netflix wants people to behave.

Chris Noonan's zesty, loveable story of a lonely piglet's path to acceptance and then glory at a bucolic farm remains a genuine example of that rare beast: the great family movie. In that sense, along with a gruff sheep dog (voiced by Hugo Weaving) and maddening sheep, it is a particularly Australian experience, even if the farming milieu has British overtones for an American audience. James Cromwell is the stoic farmer, with Magda Szubanski as a comic matriarch, but it's the old-fashioned filmmaking skills that make the wide circle of animals into engaging characters that supplies the standout performances. A brittle, telling invocation of masculinity told through the lens of near future science-fiction, Ex Machina thrusts humble programmer Caleb (Domhnall Gleeson) into the physically and mentally isolated world of Nathan (Oscar Isaac), his code savant boss who has retreated into the lab to create an artificial intelligence. The result is Ava (Alicia Vikander), a mix of moulded polymers and glowing cable shaped into a female form but rightly possessed of otherworldly instincts.

Although today's world offers us unprecedented access to greater and greater amounts of electronic information, we are faced with significant problems when it comes to finding the right information at the right time -- the essence of the information-overload problem. One of the proposed solutions to this problem is to develop technologies for automatically learning about the implicit and explicit preferences of individual users to customize and personalize the search for relevant information. In this article, we describe the development of the personalized television listings system (PTV),1 which tackles the information-overload problem associated with modern TV listings data by providing an Internet-based personalized TV listings service so that each registered user receives a daily TV guide that has been specially compiled to suit his/her particular viewing preferences.