Facebook Inc (FB.O) is working on automatically flagging offensive material in live video streams, building on a growing effort to use artificial intelligence to monitor content, said Joaquin Candela, the company's director of applied machine learning. The social media company has been embroiled in a number of content moderation controversies this year, from facing international outcry after removing an iconic Vietnam War photo due to nudity, to allowing the spread of fake news on its site. Facebook has historically relied mostly on users to report offensive posts, which are then checked by Facebook employees against company "community standards." Decisions on especially thorny content issues that might require policy changes are made by top executives at the company. Candela told reporters that Facebook increasingly was using artificial intelligence to find offensive material.

Haven't I read this before? Academics have used artificial intelligence program to map books content Researchers found each fell into six plot types based on the protagonist'Oedipus', 'Man in a Hole' and'Cinderella' were more popular with readers'Oedipus', 'Man in a Hole' and'Cinderella' were more popular with readers Revealed: Florence Henderson's own family was a far cry from... Simply magic! Harry Potter superfan, 29, spends eight hours... Revealed: Florence Henderson's own family was a far cry from... Simply magic! Harry Potter superfan, 29, spends eight hours... Rags to Riches: Pride and Prejudice; Great Expectations; Charlie and the Chocolate Factory Riches to Rags: King Lear; The Mayor of Casterbridge; Gone With the Wind; The Picture of Dorian Gray Man in a Hole (fall then rise): Robinson Crusoe; The Adventures of Tom Sawyer; The Ugly Duckling Rise Then Fall: Icarus; The Man Who Would be King; Wuthering Heights Cinderella (rise, fall then rise): Oliver Twist; King Solomon's Mines; Ben Hur; A Christmas Carol Oedipus (fall then rise then fall): The Tale of Robin Hood; Bridget Jones's Diary Moment judge gets slapped in the face at 2016 IFBB Diamond Cup Motorcyclist gets revenge when handing back driver's dropped wallet Mob storm police station and lynch suspected paedophile Watch the deadly battle between a squirrel and snake Panic as phone is submerged in WATER during condom challenge Woman who ranted in store also yelled at staff in Coffee shop Woman in high spirits'entertains' Southern Rail train passengers Police: Thief stole $1.6m in GOLD FLAKES from New York City truck Traveller carrying wooden bat in tense stand-off with bailiffs Angry Trump supporter goes on wild'racist' rant inside store 100 special police agents protect suspected paedophile from mob Tom Ford tells'The View' why he won't dress Melania Trump Motorcyclist gets revenge when handing back driver's dropped wallet Police: Thief stole $1.6m in GOLD FLAKES from New York City truck Angry Trump supporter goes on wild'racist' rant inside store Tom Ford tells'The View' why he won't dress Melania Trump Tom Ford refused to dress Melania Trump when asked in the... Doomed Colombia crash plane had been flying for 20 minutes... Woman who launched a'racist tirade' against two black... Detective claims California supermom may have been abducted... EXCLUSIVE: He's baaack! Serial sexter Anthony Weiner is... Get ready for the big freeze!

Are consciousness and emotion essential components for creating music? Johann Sebastian Bach never completed his 18th-century work "The Art of Fugue," but now a computer might do it for him. University of Washington researchers on Wednesday released MusicNet, a large-scale classical music dataset aimed at helping machines understand the basic structure of classical music -- and even predict the next notes in a recording. The publicly available dataset includes 330 classical music recordings, along with more than a million annotated markers, verified by trained musicians, that indicate the timing of each note, the instrument that plays it and the note's position in a composition's metrical structure. "At a high level, we're interested in what makes music appealing to the ears, how we can better understand composition, or the essence of what makes Bach sound like Bach," Sham Kakade, a UW associate professor of computer science, engineering and statistics, said in a statement.

Machine learning is a powerful tool used for a variety of tasks in modern life, from fraud detection and sorting spam in Google, to making movie recommendations on Netflix. Now a team of researchers from the University of Toronto Scarborough have developed a novel approach in using it to determine whether planetary systems are stable or not. "Machine learning offers a powerful way to tackle a problem in astrophysics, and that's predicting whether planetary systems are stable," says Dan Tamayo, lead author of the research and a postdoctoral fellow in the Centre for Planetary Science at U of T Scarborough. Machine learning is a form of artificial intelligence that gives computers the ability to learn without having to be constantly programmed for a specific task. The benefit is that it can teach computers to learn and change when exposed to new data, not to mention it's also very efficient.

Question: can AI vision systems from Microsoft and Google, which are available for free to anybody, identify NSFW (not safe for work, nudity) images? Can this identification be used to automatically censor images by blacking out or blurring NSFW areas of the image? Method: I spent a few hours creating in some rough code in Microsoft office to find files on my computer and send them to Google Vision and Microsoft Vision so they could be analysed. I spent a few hours over the weekend just knocking some very rough code. Yes, they did reasonably well at (a) identifying images that could need censoring and (b) identifying where on the image things should be blocked out. Follow on question: Why aren't sites like Facebook and Instagram automatically deploying this technology to identify images and allowing users to choose whether they wish to see such images? How do we know how much of our internet is already censored invisibly?

What makes Bach sound like Bach? MusicNet is a new publicly available dataset from UW researchers that labels each note of 330 classical compositions in ways that can teach machine learning algorithms about the basic structure of music.Yngve Bakken Nilsen, flickr The composer Johann Sebastian Bach left behind an incomplete fugue upon his death, either as an unfinished work or perhaps as a puzzle for future composers to solve. A classical music dataset released Wednesday by University of Washington researchers -- which enables machine learning algorithms to learn the features of classical music from scratch -- raises the likelihood that a computer could expertly finish the job. MusicNet is the first publicly available large-scale classical music dataset with curated fine-level annotations. It's designed to allow machine learning researchers and algorithms to tackle a wide range of open challenges -- from note prediction to automated music transcription to offering listening recommendations based on the structure of a song a person likes, instead of relying on generic tags or what other customers have purchased. "At a high level, we're interested in what makes music appealing to the ears, how we can better understand composition, or the essence of what makes Bach sound like Bach. It can also help enable practical applications that remain challenging, like automatic transcription of a live performance into a written score," said Sham Kakade, a UW associate professor of computer science and engineering and of statistics.

The social media company has been embroiled in a number of content moderation controversies this year, from facing international outcry after removing an iconic Vietnam War photo due to nudity, to allowing the spread of fake news on its site. Facebook has historically relied mostly on users to report offensive posts, which are then checked by Facebook employees against company "community standards." Decisions on especially thorny content issues that might require policy changes are made by top executives at the company. Candela told reporters that Facebook increasingly was using artificial intelligence to find offensive material. It is "an algorithm that detects nudity, violence, or any of the things that are not according to our policies," he said.

You've seen it in the movies: super smart robots finally come to the conclusion that we humans are making a mess of things. Still think that's the stuff of science fiction? We're building machines that are smarter than we are, that can do our jobs for us, and that we will very soon come to depend on to maintain our technology-saturated lifestyles. With so much going on in the world of AI, we are becoming all but desensitized to the technology. So let's pause for a moment and look at the slightly creepy, but really cool advances taking place in AI today.

Though movies and TV shows would have us believe that artificial intelligence means machines rising up against us, the truth is much more benign. Indeed, many of us use AI on a regular basis: Just ask Siri for directions to a restaurant or tell Shazam to name a song. This is certainly true of Facebook too, which uses AI and machine learning for a variety of tasks such as identifying images, translating languages and, yes, ranking your News Feed. With such a vested interest in AI, Facebook is releasing a series of videos today to offer a brief introduction to what it is and how it works. "We want to tell people it's not magic," says Yann LeCun, Facebook's director of AI research.