The next time you sit down to watch a movie, the algorithm behind your streaming service might recommend a blockbuster that was written by AI, performed by robots, and animated and rendered by a deep learning algorithm. An AI algorithm may have even read the script and suggested the studio buy the rights. It's easy to think that technology like algorithms and robots will make the film industry go the way of the factory worker and the customer service rep, and argue that artistic filmmaking is in its death throes. For the film industry, the same narrative doesn't apply -- artificial intelligence seems to have enhanced Hollywood's creativity, not squelched it. It's true that some jobs and tasks are being rendered obsolete now that computers can do them better.

Entertainment companies are entering the Age of Data, where they'll have access to more information than ever about their products, their audiences and how to create, market and distribute one to the other. Now, those companies and their leadership have to be ready to embrace the coming huge opportunities, especially as data-driven competitors such as Netflix, MoviePass and Amazon transform the industry. That was one message this morning from Stephen F. DeAngelis, CEO and founder of AI provider Enterra Solutions, speaking before a group of Hollywood technology executives in Beverly Hills. He noted wryly that Hollywood has portrayed AI technologies in dark or at least complicated ways over the years, from the murderous HAL 9000 in 2001: A Space Odyssey to the world-ending SkyNet in the Terminator films to the runaway AIs of Ex Machina and Her. We're quite a ways still from AI with that kind of power and autonomy, DeAngelis said, but he cautioned that people think of AI tools in overly limited ways.

In a world where our content is increasingly digital, it feels like searching for an exact piece of information should be simple. However, when was the last time you scrolled through your phone's photos to look for a specific moment but had trouble finding it? While content is becoming more accessible, the volume has made searching tougher. This past October, cloud storage company Box announced a new feature called Skills, which uses artificial intelligence to make content like photos and video "smarter." When we saw this, we thought it had the potential to help residents and city staff more efficiently search the vast video archives of our city meetings. We explain more below, but if you want to jump straight to the experience, here are our Box Skills-enabled videos: San Jose Smart Cities & Service Improvements Committee meetings.

Researchers at the University of Pompeu Fabra, Cardiff University and the Technical University of Madrid used machine-learning algorithms to discover new things about the history of music. One of the main tasks of musicology researchers is to develop and validate musical hypotheses, after studying historical documents and other available information. Many historical documents have now been digitized and can be accessed and browsed on a computer, making it easy for researchers to access them online. However, basic search engines operate at an "exact text string matching" level, and hence do not always capture the underlying meaning in the content. In a recently published study, music data science researcher Sergio Oramas and his colleagues tested natural language processing (NLP) approaches that could make the most out of archived historical documents, helping scientists to uncover new hypotheses and identifying interesting patterns in available data.

Twitter recently took drastic action as part of an effort to slow the spread of misinformation through its platform, shutting down more than two million automated accounts, or bots. You can expect the tricksters to up their game when it comes to disguising fake users as real ones. It's important not to be swayed by fake accounts or waste your time arguing with them, and identifying bots in a Twitter thread has become a strange version of the Turing test. Accusing posters of being bots has even become an oddly satisfying way to insult their intelligence. Advances in machine learning hint at how bots could become more humanlike.

One of the most surprising biographical tidbits in McQueen, the new documentary about the late fashion designer Alexander McQueen, is that he didn't know a collection could tell a "story" until he was several apprenticeships into the fashion industry. He was obviously a fast learner. Even among top-tier designers, McQueen became well-known for his theatrical runway shows. The half-dozen or so presentations we see in the film evoke Jack the Ripper, a mental asylum, sexual assault, robots, demons, goddesses, and animal chimeras. Not all the shows were well received. Directors Ian Bonhôte and Peter Ettedgui's smartest tactic--the one that makes McQueen such a pleasure to watch, even for fashion outsiders--is giving viewers a front-row seat to the runway, then letting us judge the designer's oeuvre for ourselves.

Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." At the time, Facebook CEO Mark Zuckerburg described such warnings as "pretty irresponsible." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it: "The example I would offer is, would you not invent the telephone because of the possible misuse of the telephone by evil people? No, you would build the telephone and you would try to find a way to police the misuse of the telephone," he said at the VivaTech conference in Paris last month. Others talk about the singularity – the point at which an AI suddenly becomes sentient – and use that possibility to stoke fears already fueled by dozens of sci-fi movies.

While machine intelligence is certain to play a key role in the creation of next generation systems in a wide variety of industry sectors in the near future, it is particularly relevant in rapidly developing industries such as ICT, manufacturing and transportation. Across the globe, mobile operators are getting ready to deploy the 5th generation of 3GPP mobile wireless networks (5G). Compared to the mobile infrastructure that is currently in place, 5G will bring higher throughput, lower latency, more efficient signaling, support for more spectrum bands, more programmability and other additional advanced techniques to maximize usage and optimize costs [1]. The number of connected devices will greatly increase as a result of this improved performance: sensors will benefit from more affordable bandwidth to the internet; heavy users of uplink traffic like video cameras will be able to share more data; fast-moving devices (drones, cars) will have more reliable connectivity and so on. These new devices will be the catalysts of a new wave of innovation for all involved industries.