These pop songs were written by OpenAI’s deep-learning algorithm
BRIGHT, AUSTRALIA - MARCH 11: Katy Perry performs on March 11, 2020 in Bright, Australia. The free Fight On concert was held for for firefighters and communities recently affected by the devastating bushfires in Victoria. (Photo by Daniel Pockett/Getty Images)
The news: In a fresh spin on manufactured pop, OpenAI has released a neural network called Jukebox that can generate catchy songs in a variety of different styles, from teenybop and country to hip-hop and heavy metal. It even sings—sort of.
How it works: Give it a genre, an artist, and lyrics, and Jukebox will produce a passable pastiche in the style of well-known performers, such as Katy Perry, Elvis Presley or Nas. You can also give it the first few seconds of a song and it will autocomplete the rest.
Chatbot sing-alongs: To be honest, it’s not quite there yet. You will notice that the results, while technically impressive, are pretty deep in the uncanny valley. But while we are still a long way from artificial general intelligence (OpenAI’s stated goal), Jukebox shows once again just how good neural networks are getting at imitating humans, blurring the line between what’s real and what’s not.
See the full story here: https://www.technologyreview.com/2020/05/01/1000942/pop-songs-katy-perry-elvis-openai-neural-network-deep-learning-algorithm/