The Web giant on Wednesday unveiled a 90-second piano melody (mp3), the first piece of art created by machine learning as part of Project Magenta. The project, announced last week at Moogfest, is an artificial intelligence effort to create original music and visual art. Along with creating music and art, another goal of the project is to build a community of artists, coders and machine learning researchers, Douglas Eck, a research scientist working on Project Magenta, wrote in a blog post Wednesday explaining more about the team's ambitions. Eck wrote that the team wants to open-source the infrastructure, beginning with audio and video support. One of the greatest challenges of the project is not only creating art but also telling a compelling story, Eck wrote.

Researchers have been attempting to make robots and artificial intelligence more creative over the past months – from drawing to writing quasi-dystopian poetry. Today we get another piece of work from a Google machine: a 90-second melody. It's the result of Google's Project Magenta, which aims to use machine learning to create music and art, and bridge the communities between those interests with coders and researchers. Magenta is built on top of its TensorFlow system, and you can find the open-sourced materials through its Github. The team says the challenge is not to just get Google machines to create art, but to be able to tell stories from it. After all, that's what artists do with their crafts: to compose a narrative into their work then share them with the world.

Spotify is a household name, with more paying users than any other music-streaming service in the world. But it doesn't make a penny. Those 30 million paid subscribers help it rake in almost half the revenues in the global industry. But most of the money goes to record labels and artists, while the privately owned Swedish company faces growing competition from Apple with its deep pockets and massive iPhone user base. To reduce its dependence on labels and stand apart from rivals, Spotify is broadening beyond its music library.

Streaming video helps sell shoes because Amazon Prime members buy more, Bezos says. Inc. chief executive officer spoke at Recode's Code conference Tuesday night about artificial intelligence, privacy on the internet, his goals with the Washington Post, Amazon's ambitions in entertainment, and more. Amazon is No. 1 in the Internet Retailer 2016 Top 500 Guide. For Netflix, Amazon is a particularly complex competitor because their goals aren't the same. The way Bezos looks at streaming video: "It helps us sell more shoes," he said.

Sony (NYSE:SNE) outlined a cautious outlook for the financial year 2016. However this did not convince the market as the stock price strengthened further on its release. As I pointed out in an article in March Sony has set out a strong position in the youth dynamic. This is headlined by its move into Virtual Reality and further Playstation products, as well as a strengthening position in the fast-growing streaming Music business. Its successful re-organization moves and new products I highlighted in an earlier article. The establishment of their "Business Incubation Group" to brainstorm on new products and new concepts shows that creativity is back at the front of the company's agenda.

According to Pew Research Center's analysis of comScore data, at the start of 2015, 39 of the top 50 digital news websites have more traffic to their sites and associated applications coming from mobile devices than from desktop computers. This fact is self -explanatory why service providers are moving towards news app. More and more apps are being launched worldwide each one claiming to be exclusive and original. But the truth is they are not, especially news apps. With the abundance of data being generated every second, there has been an excess of information.

I am excited to be here today for what is a Reddit first. This will be the first AMA in history to feature an Artificial "Hive Mind" answering your questions. You might have heard about me because I've been challenged by reporters to make lots of predictions. For example, Newsweek challenged me to predict the Oscars (link) and I was 76% accurate, which beat the vast majority of professional movie critics. I'm a Swarm Intelligence that links together lots of people into a real-time system – a brain of brains – that consistently outperforms the individuals who make me up.

Unlike robotic AIs that are being built to emulate the human brain, UNU works with existing human intelligence instead of replicating it. The platform, which is open to public, allows a group of people to come together and converge on an answer in real time. While a swarm of seven predicted the Oscars, the Derby decision came from 20 people. For the AMA at 1pm ET today, the group that will make political predictions is expected to range from 100 to 200 people. The participants will come from UNU's current user base that has already answered fantasy football and cooking queries.

The Web giant on Wednesday unveiled a 90-second piano melody (mp3), the first piece of art created by machine learning as part of Project Magenta. The project, announced last week at Moogfest, is an artificial intelligence effort to create original music and visual art. Along with creating music and art, another goal of the project is to build a community of artists, coders and machine learning researchers, Douglas Eck, a research scientist working on Project Magenta, wrote in a blog post Wednesday explaining more about the team's ambitions. Eck wrote that the team wants to open-source the infrastructure, beginning with audio and video support. One of the greatest challenges of the project is not only creating art but also telling a compelling story, Eck wrote.

Last week, Warner Bros. issued a DMCA takedown notice to the video streaming website Vimeo. Warner Bros. had just made a fascinating mistake. Some of the Blade Runner footage -- which Warner has since reinstated -- wasn't actually Blade Runner footage. Or, rather, it was, but not in any form the world had ever seen. Instead, it was part of a unique machine-learned encoding project, one that had attempted to reconstruct the classic Philip K. Dick android fable from a pile of disassembled data.