radiohead


Enjoy the Westworld Season 1 Soundtrack Now

#artificialintelligence

The soundtrack for Season One of HBO's Westworld has been released. The 34-song compilation, Westworld: Season 1 (Music From the HBO Series), includes original music by composer Ramin Djawadi along with his covers of Radiohead, the Rolling Stones, the Cure, Amy Winehouse and others. The set includes previously released covers of Soundgarden, the Rolling Stones and the Cure, which appear on an EP featuring selections from the series. A reworking of Radiohead's "No Surprises" hails from the EP as well and the new soundtrack also features Djawadi's interpretations of "Motion Picture Soundtrack," "Fake Plastic Trees" and "Exit Music (For a Film)." Other covers include Nine Inch Nails' "Something I Can Never Have," Amy Winehouse's "Back to Black" and the Animals' "House of the Rising Sun".


If You Like Radiohead, You Might Like This Article

AI Magazine

With so much music readily available, tools that help a user find new, interesting music that matches his or her taste become increasingly important. In this article we explore one such tool: music recommendation. We describe common music recommendation use cases such as finding new artists, finding others with similar listening tastes, and generating interesting music playlists. We describe the various approaches currently being explored by practitioners to satisfy these use cases. Finally, we show how results of three different music recommendation technologies compare when applied to the task of finding similar artists to a seed artist.


The Robots Cometh

#artificialintelligence

The age of the bot has begun. We just have barely begun to notice. It's only been 10 years, and smartphones have fundamentally changed our world, the bot revolution will come quicker, and have an even greater impact on us. The bots cometh in all shapes and sizes, hardware and software, automations and AI and robot fried and foe. But most likely our most common interaction with them in the very near future will be in the form of messenger/personal assistant and customer service bots.


How Westworld's Music Became Equal Parts Groundhog Day and MTV

WIRED

There aren't many saloons where you can get into a decent pistol duel nowadays. But at the Mariposa in Sweetwater, you can walk in, order a shot of bourbon, and straight-up Aaron Burr a robot--all to the strains of Radiohead and Nine Inch Nails, courtesy of a player piano that happens to be ever so slightly out of tune. "In the show, everything is so real, until you look closely. The music is a subtle layer of that." Djawadi is no stranger to scoring an epic HBO drama; he also composes for Game of Thrones.


Bots are here, they're learning -- and in 2016, they might eat the web

#artificialintelligence

The first bot I ever befriended went by the name of GooglyMinotaur. The Minotaur appeared in 2001 to promote Amnesiac, the latest album from Radiohead, which was and still is my favorite band. I happily chatted with the Minotaur about Radiohead history, information about the band's tour, and the MP3s it offered for download. The Minotaur was popular among fans like me: 1 million people added it as a friend, and in its lifetime it sent more than 60 million messages. But the Minotaur died a few months after it appeared, along with the rest of the era's bots.


If You Like Radiohead, You Might Like This Article

AI Magazine

With the recent dramatic transformations in the world of digital music, a music listener is now just a couple of clicks away from being able to listen to nearly any song that has ever been recorded. With so much music readily available, tools that help a user find new, interesting music that matches her taste become increasingly important. In this article we explore one such tool: music recommendation. We describe common music recommendation use cases such as finding new artists, finding others with similar listening taste, and generating interesting music playlists. We describe the various approaches currently being explored by practitioners to satisfy these use cases. Finally, we show how results of three different music recommendation technologies compare when applied to the task of finding similar artists to a seed artist.