In the last few years artificial intelligence (AI) and machine learning (ML) have both started to feature more prominently in technology. That is especially the case in video editing, where artificial intelligence is being integrated in more and more ways. Not long from now, AI may completely transform video editing – and in some ways it already is starting to do just that. One of the earliest examples of AI's use in video editing was as far back as 2016 when IBM used their Watson supercomputer to curate footage and create a trailer for the horror film Morgan. Essentially Watson used machine learning to analyze other trailers, and then applied what it learned to curate and select scenes from the film that it felt would be good for the trailer.

The first time I watched a 3D movie at the age of 12, I was mesmerized by the experience and literally tortured my parents to take me to that movie again and again. I was so much interested in 3D movies that I had to watch them alone as I grew up because my friends deemed such movies as fit for kids alone. I do blame my choice of movies though, as these movies were targeted at kids. But for me, it was the experience rather than the story, I would eagerly wait for those moments where I get to feel the objects closer to me, and a couple of occasions I have even chosen the front seats to check whether the experience doubles up (forgive my naivety). I loved the experience, and I am sure many would agree with me.

HAL became operational in Urbana, Illinois, at the HAL Plant (the University of Illinois' Coordinated Science Laboratory, where the ILLIAC computers were built). The film says this occurred in 1992, while the book gives 1997 as HAL's birth year.[3] In 2001: A Space Odyssey (1968), HAL is initially considered a dependable member of the crew, maintaining ship functions and engaging genially with its human crew-mates on an equal footing. As a recreational activity, Frank Poole plays against HAL in a game of chess. In the film the artificial intelligence is shown to triumph easily.

We touched a lot of gadgets. This week was the annual CES, one of the world's largest consumer electronics show, and WIRED's team was on the ground covering all of the top tech trends to emerge from the show. In this week's episode of the Gadget Lab podcast, Mike, Arielle, and Lauren talk about CES's big security #fail, what all of these connected gadgets mean for the future of healthcare, and robots. Later in the episode, Arielle talks to Jen Wong, the chief operating officer of Reddit, about the company's "growing up" moment and how it plans to monetize its users. Show notes: Check out our best of CES list when you've finished listening to the pod.

LOS ANGELES [USA]: Like every year, the CES 2019 too witnessed a number of interesting innovations one of them being an AI-powered robot called Kiki. Kiki looks like Eva from the movie Wall-E and has cat ears. The robot is powered by artificial intelligence, which basically means it learns human behaviour over time to respond to situations. According to Cnet, Kiki is a companionship robot. It features a camera in its nose to help identify the environment and remember people. Once it locks on a face, it can track the person by moving its head, much like a real pet would.

Millennials are the generation most likely to violate Netflix's terms of service by logging in to use someone else's account, according to a new survey. More than 18 percent of that generation uses someone else's login to stream Netflix, compared to Generation X (9 percent) and Baby Boomers (11 percent). The data comes as Netflix prepares to crackdown on illegal account sharing via new artificial intelligence software, which will be able to analyze which users are logged in and then flag shared accounts. This chart illustrates what proportion of Millennials, Baby Boomers and Generation X stream each of the top three major video streaming services through another person's account The move is expected to recoup major money for the video streaming giant: a separate report from Parks Associates found that by 2021, credentials sharing will account for $9.9 billion of losses in pay-TV revenues and $1.2 billion of over-the-top (OTT) revenues. The survey also found that while 68 percent of people still use traditional cable, nearly 92 percent use video streaming for television, movies, sports or music.