When Facebook announced a tweak to its news feed algorithm Wednesday, dating apps were put in a bind. The change that would soon prioritize friends' posts over those from publishers quickly led media industry types to declare it, once again, the end of media. But Facebook's decision doesn't solely affect news outlets. More than 50 million businesses use Facebook Pages -- from big brands like McDonald's and Nike to small shop owners to startups building the next top smartphone app. The downgrade could encourage more page owners to pay Facebook to boost their posts into the news feeds of users.

Disney broke the news during a special livestream on Facebook today, announcing that it's working on Wreck-It Ralph 2, which will go beyond the confines of the arcade seen in the first movie and into the internet. There weren't many additional details divulged to go on, but this could mean some interesting changes for both the film's format and the type of game references we might see. It's a bit of a wait for the sequel to hit theaters, but it's just one in a long line of video game-focused films coming down the pipeline. For instance, the Minecraft film is arriving n 2019, and the Tetris film (now a trilogy) is planned to begin shooting next year. The future is rife with video game movies, but will they be any good?

Ask Apple's Siri digital assistant if she's evil, and she'll respond curtly, "Not really." Repeat a famous line from the movie "2001: A Space Odyssey," in which a computer on a spaceship kills nearly all the human crew, and Siri groans. And who can blame her? We humans have a morbid fascination with machines rising up to wipe us out or to enslave us as cocooned, flesh-and-blood battery packs. You can see that vision of the future streaming over Netflix whenever you want.

Go to the movies or turn on a TV, and you'll quickly learn to fear artificial intelligence. The power of rogue computers is one of Hollywood's most popular topics. Call it an existential fear of the unknown, or perhaps a sense of our own mortality. Whatever our future actually holds, we're fascinated today by how we might share it with machines that become smarter, nimbler and -- gulp -- meaner than we are. Even a techno-sophisticate like Elon Musk frets about us "summoning the demon," and research companies like OpenAI have been founded with the goal of ensuring that AI doesn't turn around and bite us. While researchers creating AI in Silicon Valley and collegiate computer science labs have their own theories about what this software will become, they've seen the movies just like us, and they know what's on our minds.

Ask Apple's Siri digital assistant if she's evil, and she'll respond curtly, "Not really." Repeat a famous line from the movie "2001: A Space Odyssey," in which a computer on a spaceship kills nearly all the human crew, and Siri groans. And who can blame her? We humans have a morbid fascination with machines rising up to wipe us out or to enslave us as cocooned, flesh-and-blood battery packs. You can see that vision of the future streaming over Netflix whenever you want.

Drawing from artificial intelligence (AI) advances that often don't trickle down to consumers out of the commercial sector, the company behind the Overdrive robotic cars is preparing to ship an animated little bot. Anki's Cozmo, with its machine learning and dynamic personality, is redefining the term "bringing toys to life." Anki describes Cozmo as being a real-life version of the type of robot companions seen in films. When watching the little soda-can-sized robot take in the world around it, Pixar's Wall-E comes to mind. Cozmo can get around the real world using a set of caterpillar tracks, the continuous tracking technology that's often employed in tank designs.

Each year at Cannes Lions, the Saatchi & Saatchi New Directors' Showcase features a live show conceived around a theme that mirrors the most exciting happenings in the ad industry. This year it was less a live show, more an experiment. In a nod to the rising prominence of artificial intelligence, Saatchi & Saatchi and its LA agency Team One set about potential capabilities of the technology. The result is a music video that was creatively conceived, cast, directed, shot and edited wholly by machines. Saatchi & Saatchi hid it within the NDS reel and tasked the audience to try and pick it out among a crop of films by some of the world's most talented new directors.

A.I.: Artificial Intelligence--which was released 15 years ago today--was an unprecedented collaboration between two titans of cinema: Stanley Kubrick and Steven Spielberg. The film, based on the 1969 short story Supertoys Last All Summer Long, is set in the late 21st century and tells the story of a robot named David (Haley Joel Osment) who is programmed to feel human love for his parents, Henry and Monica. After Henry and Monica's human son Martin is brought back to life from suspended animation, his jealousy leads him to get David cast off into the wilderness with Teddy, his robotic teddy bear friend. David and Teddy soon befriend a robotic prostitute named Gigolo Joe (Jude Law), and David's quest to become a "real boy" begins in earnest. In 1983, 18 years before A.I. made it into theaters, Stanley Kubrick bought the movie rights to author Brian Aldiss' short story, Supertoys Last All Summer Long.

Most recommender systems recommend a list of items. The user examines the list, from the first item to the last, and often chooses the first attractive item and does not examine the rest. This type of user behavior can be modeled by the cascade model. In this work, we study cascading bandits, an online learning variant of the cascade model where the goal is to recommend $K$ most attractive items from a large set of $L$ candidate items. We propose two algorithms for solving this problem, which are based on the idea of linear generalization. The key idea in our solutions is that we learn a predictor of the attraction probabilities of items from their features, as opposing to learning the attraction probability of each item independently as in the existing work. This results in practical learning algorithms whose regret does not depend on the number of items $L$. We bound the regret of one algorithm and comprehensively evaluate the other on a range of recommendation problems. The algorithm performs well and outperforms all baselines.

One of the most intriguing public discussions to emerge over the past year is humanity's wrestling match with the threat and promise of artificial intelligence. AI has long lurked in our collective consciousness -- negatively so, if we're to take Hollywood movie plots as our guide -- but its recent and very real advances are driving critical conversations about the future not only of our economy, but of humanity's very existence. In May 2014, the world received a wakeup call from famed physicist Stephen Hawking. Together with three respected AI researchers, the world's most renowned scientist warned that the commercially-driven creation of intelligent machines could be "potentially our worst mistake in history." Comparing the impact of AI on humanity to the arrival of "a superior alien species," Hawking and his co-authors found humanity's current state of preparedness deeply wanting.