An important metric of users' satisfaction and engagement within on-line streaming services is the user session length, i.e. the amount of time they spend on a service continuously without interruption. Being able to predict this value directly benefits the recommendation and ad pacing contexts in music and video streaming services. Recent research has shown that predicting the exact amount of time spent is highly nontrivial due to many external factors for which a user can end a session, and the lack of predictive covariates. Most of the other related literature on duration based user engagement has focused on dwell time for websites, for search and display ads, mainly for post-click satisfaction prediction or ad ranking. In this work we present a novel framework inspired by hierarchical Bayesian modeling to predict, at the moment of login, the amount of time a user will spend in the streaming service. The time spent by a user on a platform depends upon user-specific latent variables which are learned via hierarchical shrinkage. Our framework enjoys theoretical guarantees, naturally incorporates flexible parametric/nonparametric models on the covariates and is found to outperform state-of- the-art estimators in terms of efficiency and predictive performance on real world datasets.

Tired of seeing his friends and family sharing questionable content on his Facebook feed, data scientist Zach Estela decided to take action. He built a tool that scans a website's most recent 100 posts and analyzes it to determine whether it's fake news, heavily biased, or a legit news source. "I see my friends post, sometimes, complete garbage or articles recommended to me that are complete garbage," Estela told me over the phone. As fake new purveyors have become more ubiquitous, they've also gotten more sophisticated. It's sometimes hard to tell if a news source is a small local paper, a Russian-backed propaganda forum, or a semi-accurate hype blog that only reports the facts when they align with its agenda. While companies like Google and Facebook have tried to come up with ways to flag shady content, a lot of stuff can still fall through the cracks, especially when we rely on human judgement.

I've first heard of deepfakes a good week ago. You have been warned) consists of people using an app created by user "deepfakes" to create fake celebrity porn. This has caused a shitstorm on the Internet, media discussing the legality of it all, websites taking down the deepfake creations, and people panicking as they realise AI is going to screw us all up (newsflash: it's already been happening in much less obvious ways). And meanwhile, Nicolas Cage is taking over Hollywood. While everyone's debating whether this is good or bad, I just had to find out more.

Artificial intelligence is appearing in a growing range of products, industries and services, so that even the most traditional markets will be impacted, and any growing company can use AI to help boost their performance. Here are some of the cutting edge areas where AI could make a massive impact and will spill over into other industries. Machines watching other machines is a common thread in the 21st century. The Internet of Things could soon see every piece of technology linked together. For now though AI is being used by many IT companies to improve performance.

We began our journey to predicting this year's best picture winner by collecting and cleaning lots of data. From critic ratings to performance at precursors, we looked for any and all publicly available information about the films that had been nominated for Best Picture over the past X years. This data would help inform our algorithm which we would build using SciKit Learn, one of the most popular learning toolkits in the world.

SenseTime Co., a Chinese artificial intelligence start-up backed by Alibaba Holdings Ltd., has formed an alliance with one of the US' top university to jointly explore human and machine intelligence. The Beijing-based firm will jointly work with the Massachusetts Institute of Technology undertake research into original AI technologies such as computer-vision, human-intelligence-inspired algorithms, medical imaging, and robotics, online news outlet QQ Tech reported. SenseTime recently became the first company to join MIT's Intelligence Quest, which aims to leverage the Institute's strengths in brain and cognitive science and computer science to advance research into human and machine intelligence. Considered the world's leading AI unicorn valued at more than USD3 billion, SenseTime has developed a sophisticated proprietary deep learning platform and built applications for multiple industries. The company has offices in Hong Kong, Beijing, Shenzhen, Hangzhou, Shanghai, Chengdu, Kyoto, Tokyo and Singapore.

For K-pop stars used to Pop Idol-style fame factories, Tuesday's concert at Blue Square Concert Hall in Seoul was still an artificial first. The 3,000 screaming fans were real, as were chart-topping, body-popping girl groups Spica and Produce 101 -- but all of the songs were written by a London-based song-bot. Each of the tunes in the set had been composed by Moorgate-based Jukedeck. The artificial intelligence (AI) start-up was founded by 30-year-old former King's College Cambridge choristers Ed Newton-Rex and Patrick Stobbs (Stobbs is also a Google alumnus). Simply, the technology reads music and learns what notes, chords and combinations work in order to generate good music.

Want to watch this again later? Sign in to add this video to a playlist. Report Need to report the video? Sign in to report inappropriate content. Report Need to report the video?

In preparation for his participation in a panel discussion hosted by Demos about the future of artificial intelligence, The Director of the Media Policy Project and the Director of the LSE Truth, Trust and Technology Commission, Professor Charlie Beckett, prepared the following notes. You can follow read more about the discussion by searching #futureofai on Twitter. I think that AI and machine learning is a big deal for journalism and news information. Possibly as important as the other developments we have seen in the last 20 years such as online platforms, digital tools and social media. My 2008 book on how journalism was being revolutionised by technology was called SuperMedia because these technologies offered extraordinary opportunities to make journalism much more efficient and effective – but also to transform what we mean by news and how we relate to it as individuals and communities.

We see the power of artificial intelligence every day: When Netflix recommends a movie you love, when your bank detects fraud in your account, or when Google routes you around a traffic jam. But outside of examples from mammoth companies with millions to spend on data science initiatives, there's a decided lack of AI success among the rest of us. That's the conclusion that Ali Ghodsi has come to. As the co-founder and CEO of Databricks and an adjunct professor at UC Berkeley, Ghodsi has a direct view into the types the AI projects that organizations are embarking on. It turns out, those organizations are struggling mightily, and he wonders why more people aren't talking about it.