Jukebox aspires one day to fool people with music, as well. Having listened to around 1.2 million songs, categorized by artist, album genre, year, moods and keywords, it has begun composing.

OpenAI today released Jukebox, a machine learning framework that generates music — including rudimentary songs — as raw audio in a range of genres and musical styles. Provided with a genre ...

OpenAI trained convolutional neutral networks with a curated list of 1.2 million songs to generate the raw-sounding music. In the organization’s paper describing Jukebox, the researchers say ...

The Jukebox model was trained on a raw dataset of 1.2 million songs, including 600,000 in English language, and used metadata and lyrics from LyricWiki to recreate singer’s voices.

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 ...

The approach is similar to how OpenAI developed a prior music-making AI called MuseNet, but Jukebox goes a step further by generating its own lyrics in collaboration (the company used the word ...

OpenAI Jukebox – “Pop, in the style of the Beatles” Mysterious artist OpenAI Jukebox is back, and their latest release has me thinking maybe this is just Animal Collective in disguise ...

AI-generated music is a fascinating new field, and deep-pocketed research outfit OpenAI has hit new heights in it, creating recreations of songs in the style of Elvis, 2Pac, and others. The ...