From swooping landscapes to the most dramatic selfie vids ever, a drone can capture it all. These tips will help make your footage extra fly. The first setting to adjust is frame rate: 30 frames per second looks like reality TV, while 24 fps looks like a Hollywood feature--set it to 24. You typically want to shoot in 4K, which will capture the tiniest details and give you flexibility to crop the frame while editing. For action shots, opt for 1080p at 60 or even 120 fps, so you can slow down the footage later.

Netflix's choose-your-own-adventure content will find its audience--first through novelty, then because creators will tease ever more fireworks out of the form. But interactive TV starts at a disadvantage: It is arriving just as we've learned, in so many ways, not to interact at all. Peter Rubin (@provenself) wrote about the Tetris effect in issue 26.11. This article appears in the February issue.

The sequel to the hit indie game Her Story will have a relatively star-studded cast. Creator Sam Barlow and Annapurna Interactive have revealed the main cast for Telling Lies, and you might just recognize some of them even if they aren't mega-stars. Logan Marshall-Green (Charlie Holloway in Prometheus) will play David, while Alexandra Shipp (Storm in X-Men: Apocalypse) takes the role of Ava. Kerry Bishé of Halt and Catch Fire fame will play Emma, and Angela Sarafyan (Clementine from Westworld) will play Max. There's even a trendy casting announcement: Bird Box's Vivien Lyra Blair (the "girl" in Netflix's movie) has a speaking part.

With video streaming services and social media platforms reporting large amounts of traffic, videos are slowly but surely moving front and center as the most popular form of online content. Plus, they are made more accessible by the widespread use of mobile devices and the growing average speed of Internet connectivity. Look no further than sites like Twitch and YouTube to understand how powerful videos can be at keeping people glued to their screens. As a matter of fact, according to YouTube, U.S. residents aged 18-34 watch more videos on mobile devices than they do on any TV broadcast or cable network. Bearing this in mind, performing video optimization has never been as important as it is today. To get more eyeballs looking at your videos, you must do your best to ensure that people can find your videos online and that they choose to watch your video over the vast pool of competition -- something that was covered in the YouTube SEO 101 post. Getting yourself noticed on YouTube can be quite a daunting challenge, but in this post, we've rounded up some of the best tools that can help you optimize your YouTube videos for SEO. Without further ado, let's get started! One of the most crucial parts of producing videos is getting everything ready even before the camera starts rolling.

As AI and machine learning have infused themselves over the last half decade into nearly every corner of our lives, there has been a growing interest in how the biases of these models may be silently impacting society. Much of this focus has been on the issues of biased training data and a homogeneous workforce that lacks sufficient diversity of experience to recognize bias. However, lost in this conversation is the far bigger driving force: the lack of economic incentive to minimize bias in the technologies that increasingly power our lives. The digital world is an incredibly biased place. Geographically, linguistically, demographically, economically and culturally, the technological revolution has skewed heavily towards a small number of very economically privileged slices of society.

Several years ago, you may recall a publication describing our growing dependency upon machines, devices, and "AI." On several occasions, I've attempted to bring awareness to this phenomenon of artificial intelligence's abilities in creating and/or re-creating itself... over and over again. What once was a'science-fiction' story has been brought to bear, in living color, a scientific fact. The article, "Device Machine Dependent," has described instances and descriptions where robots or robotics have been designed to emulate the actions, abilities, and appearance(s) of mankind... "Human-Like"; "The Image of Its' Creator!" How many times have you been in your car and engaged in a shouting match or argumentative interaction with your'GPS' or "onboard interface?" Aw, c'mon now... haven't you gotten angry and screamed at the device when the voice behind it gives you screwed up or wrong directions?

A few years ago, the idea of controlling your lights or even security system remotely through your smartphone would have been deemed so futuristic and only present in the minds of science fiction novelists. Artificial intelligence might conjure images of the latest Sci-fi movie that you recently watched, yet in actual sense, its actual impact in our everyday life is more understated and far-reaching than the science fiction movies and novels might actually suggest. Most of us have encountered AI in our everyday lives. Think about Netflix suggesting to you are a TV to watch. Google maps are already sourcing location data from our smartphone and aiding us with directions.

In fact, I've never been to CES. But after reading the reports on this year's Consumer Electronics Show (CES) in Las Vegas, I feel like I was there 50-years ago via Stanley Kubrick's 1968 motion picture phenomena "2001: A Space Odyssey." The Radio Advertising Bureau (RAB) did a special video they called "Bonus Report of C-Suite Radio Exec's attending CES" and some of the comments those radio executives made is what made me feel like I'd seen this "movie" before. Steve said that what he's marveled at over the years is how media is continually being integrated. He said only a couple of years ago, there was virtually no mention of smart speakers, and this year it's not only a device exploding in the home, but now is coming into the car too.

You sit down to watch a movie and ask Netflix for help. Zoolander 2?") The Netflix recommendation algorithm predicts what movie you'd like by mining data on millions of previous movie-watchers using sophisticated machine learning tools. And then the next day you go to work and every one of your agencies will make hiring decisions with little idea of which candidates would be good workers; community college students will be largely left to their own devices to decide which courses are too hard or too easy for them; and your social service system will implement a reactive rather than preventive approach to homelessness because they don't believe it's possible to forecast which families will wind up on the streets. You'd love to move your city's use of predictive analytics into the 21st century, or at least into the 20th century. You just hired a pair of 24-year-old computer programmers to run your data science team. But should they be the ones to decide which problems are amenable to these tools? Or to decide what success looks like? You're also not reassured by the vendors the city interacts with.

In this video, I've explained - what Machine Learning is, what are the applications of Machine Learning, how you can start learning Machine Learning and what is next after you learn ML.