This is just a fun experiment, please listen to some real Beatles songs on the streaming service of your choice, or even better - buy one of their albums.

Music generated with OpenAI Jukebox Art generated with Pytorch Style Transfer

Join the Jukebox community at https://discord.gg/6At7WwM

FAQ:

• What is OpenAI Jukebox? Simply put, it's a neural net that generates music - read more about it on the official blog: https://openai.com/blog/jukebox/

• Can I use Jukebox myself? Yes! If you have a very powerful graphics unit, you can download the program from the official Github. If you don't, you can give Google CoLab a try - https://colab.research.google.com/git...

• Is there a tutorial? Yes, I made a tutorial explaining the basics about generating samples through Google Colab. https://www.youtube.com/watch?v=mNtmg... I'd also recommend checking out this site, it has some useful info towards the bottom: https://github.com/openai/jukebox/iss...

• What has Jukebox been trained on? According to OpenAI, it has been trained on 1.2 million songs. Unfortunately, OpenAI has not publicly disclosed which songs are in this dataset.

• Are there full versions of these samples? No, they would have to be generated first. It would take a long time and the sound quality would likely deteriorate even more.

• What sampling temperature are you using? It varies. But always between .975 and 1.

• What is co-composer mode? The AI usually produces results that are very random, which can be fun! But with co-composer mode you have some limited control over the final result, so you can make your songs a lot more coherent. The AI will generate 3 (or more) short samples and you can choose your favorite one. From this point, the AI generates another 3 samples and so on, until you have a full song.

• Can you do X song/band next? Feel free to suggest anything, but no promises! Also, the AI works best if the artist is on this list: https://github.com/openai/jukebox/blo...

#openaijukebox #jukeboxai

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