Go behind the scenes with Tom Cruise as he performs one of the "most dangerous sports in the world" for "Mission: Impossible." (Credit: Paramount Picture/Skydance) Tom Cruise's "Mission: Impossible – Dead Reckoning" co-stars have revealed the "thoughtful" gifts the 61-year-old star gave them during filming, and they are fitting of an action hero. "He's always very keen to show his appreciation," Simon Pegg, who also starred with Cruise in the last four "Mission: Impossible" films, told People magazine. "I think he's so used to being the focus of attention, it's naturally his instinct to kind of reflect everything back. And he's always incredibly sort of generous in terms of his gratitude to us and how he thanks us and how he lets us know that we're valued." Pegg said one day, when the cast had the afternoon off, Cruise flew them in a helicopter to go shark diving.

American action movie villains have always acted as a sort of paranoia litmus test, capturing a snapshot of the particular anxieties plaguing the country and its citizens at any given time. In the 1990s and '00s, with the Red Menace long forgotten, movies leaned heavily on the awful "bad Arab" trope, pulling their villains from the Middle East. Other recent smash-'em-ups have made bad guys out of rogue spies, shadowy cyber terrorists, and self-interested arms dealers, all common players in the global news landscape. But for Mission: Impossible--Dead Reckoning Part One, out this week, writers Bruce Geller, Erik Jendresen, and Christopher McQuarrie (who also directed the movie) made their big bad--known as The Entity--out of a slightly more amorphous fear: that of an all-powerful, all-seeing, sentient AI. It has access to anything with an online network and can use those evil techno powers to manipulate everything from global military superpowers to a grandma with a gun.

Walt Disney Co.'s "Captain Marvel" is expected to open with a spectacular $100 million in ticket sales from the U.S. and Canada alone next month. And yet, according to the highly influential website Rotten Tomatoes, only 28% of moviegoers are interested in seeing Marvel Studios' first superhero film with a solo female lead. Blame online trolls, who have previously waged campaigns to lower audience ratings for movies including "Star Wars: The Last Jedi" and "Ghostbusters" by flooding their pages with negative, sometimes sexist comments. Such "review bombing" efforts are a serious problem for Rotten Tomatoes, which depends on credible ratings to drive traffic to its free website. The company, owned by the largest online movie ticket seller, Fandango, now has a plan to curb the abuse.

Success in the movie industry relies on a studio's ability to attract moviegoers--but that's sometimes easier said than done. Moviegoers are a diverse group, with a wide variety of interests and preferences. Historically, movie studios have relied heavily on experience when deciding to invest in a particular script--but this can lead to huge risks, particularly when investing in new, original stories. The iterative and complex process of matching stories and audiences is something that Julie Rieger, President, Chief Data Strategist and Head of Media, and Miguel Campo-Rembado, SVP of Data Science, together with their team of data scientists at 20th Century Fox, decided to clarify with data. Understanding the market segmentation of the movie-going public is a core function of movie studios.

When you go to the movies, how do you decide what you want to see? Maybe you're more likely to purchase a ticket if a movie is part of an established franchise in which you are already invested. Maybe a beloved actor or the buzz of awards-season brings you to the big screen. Or maybe a friend hasn't stopped raving about a recent release and you just have to check it out for yourself. Whichever reason brings you to the movies, the question has now become whether artificial intelligence (AI) can predict what you're most likely to see.

No other film genre boasts such an unimpeachable reputation for dreadfulness as the video game adaptation. Some, such as this year's Tomb Raider film and the zombie-themed Resident Evil efforts, almost achieve mediocrity. Others are so fascinatingly terrible that they have become Hollywood legend – for instance, the baffling interpretation of Super Mario Bros proffered by edgy British directors Annabel Jankel and Rocky Morton in 1993, in which Nintendo's bright, joyful Mushroom Kingdom was reimagined as a futuristic dystopia called Dinohattan, where everyone was dressed in fishnets and black leather trenchcoats. A quarter of a century later, it is still impossible to understand why anyone thought that was a good idea. The ever-expanding Marvel cinematic universe is ample proof that films can do an excellent job of exploring geek culture and fleshing out the paper-thin characters that dominate it; Black Panther has just become the fifth highest-grossing movie ever at the US box office.

Family Flicks The delightful 1995 charmer Babe about a smart but sweetly naive little pig who goes to live on a storybook-like farm (each chapter is introduced with title cards by a trio of singing mice) is still a treat for adults and tots. James Cromwell is excellent as Farmer Hoggett. The meditative drama is as spare in dialogue as it is rich visually. Indeed it is the villainous, lip-reading AI computer, Hal 9000 (voiced by Douglas Rain), who delivers the film's most memorable lines. Thin Man Double Feature Shot over just two weeks on a B-movie budget, The Thin Man (1934) was an immediate hit with both critics and audiences.

Brandon is an author and deep learning developer. He has worked as Principal Data Scientist at Microsoft, as well as for DuPont Pioneer and Sandia National Laboratories. Brandon earned a Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology. Bayesian inference is a way to get sharper predictions from your data. It's particularly useful when you don't have as much data as you would like and want to juice every last bit of predictive strength from it. Although it is sometimes described with reverence, Bayesian inference isn't magic or mystical. And even though the math under the hood can get dense, the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer. Bayesian inference is based on the ideas of Thomas Bayes, a nonconformist Presbyterian minister in London about 300 years ago. He wrote two books, one on theology, and one on probability.

Since there are 25 long haired women and 2 long haired men, guessing that the ticket owner is a woman is a safe bet. To lay our foundation, we need to quickly mention four concepts: probabilities, conditional probabilities, joint probabilities and marginal probabilities. The probability of a thing happening is the number of ways that thing can happen divided by the total number of things that can happen. Combining these by multiplication gives the joint probability, P(woman with short hair) P(woman) * P(short hair woman).

Bayesian inference is a way to get sharper predictions from your data. It's particularly useful when you don't have as much data as you would like and want to juice every last bit of predictive strength from it. Although it is sometimes described with reverence, Bayesian inference isn't magic or mystical. And even though the math under the hood can get dense, the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer. Bayesian inference is based on the ideas of Thomas Bayes, a nonconformist Presbyterian minister in London about 300 years ago. He wrote two books, one on theology, and one on probability. His work included his now famous Bayes Theorem in raw form, which has since been applied to the problem of inference, the technical term for educated guessing. The popularity of Bayes' ideas was aided immeasurably by another minister, Richard Price. He saw their significance, refined them and published them. It would be more accurate and historically just to call Bayes' Theorem the Bayes-Price Rule.