The most-torrented shows of 2013, according to Torrent Freak. Torrent Freak Game of Thrones again turned out to be the most-pirated TV show of 2013, according to a report from Torrent Freak. The show was downloaded an estimated 5.9 million times, besting its proportion of conventional television viewers, which clocks in at 5.5 million. That is a 37 percent increase from 2012, when Torrent Freak estimated Game of Thrones was downloaded 4.28 million times. As the New York Times points out , illegal downloads grew about 10 percent in 2013, with 327 million unique users navigating 13.9 billion webpages that handle pirated movies and TV. The shows Breaking Bad, The Walking Dead, The Big Bang Theory , and Dexter contributed another 14.3 million downloads between them. 2013 also saw plenty of industry leaders endorsing illegal downloading in one way or another. Game of Thrones director David Petrarca said the show thrives on “cultural buzz” in part generated by pirates; Time Warner CEO Jeff Bewkes said that Game of Thrones ’ status as the most pirated show was “ better than an Emmy ;” Netflix stated that it uses piracy statistics to determine what types of shows to produce or license; Breaking Bad creator Vince Gilligan said piracy ” helped… in terms of brand awareness .” The Walking Dead executive producer Gale Ann Hurd disagreed , calling the idea that piracy does good for content a “mistaken belief” and saying the activity is not something “we should encourage.” Read 1 remaining paragraphs | Comments
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Game of Thrones illegal downloads exceed TV viewers for second year
KentuckyFC writes “A curious thing about video games is that computers have never been very good at playing them like humans by simply looking at a monitor and judging actions accordingly. Sure, they’re pretty good if they have direct access to the program itself, but ‘hand-to-eye-co-ordination’ has never been their thing. Now our superiority in this area is coming to an end. A team of AI specialists in London have created a neural network that learns to play games simply by looking at the RGB output from the console. They’ve tested it successfully on a number of games from the legendary Atari 2600 system from the 1980s. The method is relatively straightforward. To simplify the visual part of the problem, the system down-samples the Atari’s 128-colour, 210×160 pixel image to create an 84×84 grayscale version. Then it simply practices repeatedly to learn what to do. That’s time-consuming, but fairly simple since at any instant in time during a game, a player can choose from a finite set actions that the game allows: move to the left, move to the right, fire and so on. So the task for any player — human or otherwise — is to choose an action at each point in the game that maximizes the eventual score. The researchers say that after learning Atari classics such as Breakout and Pong, the neural net can then thrash expert human players. However, the neural net still struggles to match average human performance in games such as Seaquest, Q*bert and, most importantly, Space Invaders. So there’s hope for us yet… just not for very much longer.” Read more of this story at Slashdot. 
