>> has anyone solved the data problem? So MIDI songs were being generated quite "early" on, even with basic text generators (LSTM models), where the "alphabet"

>> has anyone solved the data problem? So MIDI songs were being generated quite "early" on, even with basic text generators (LSTM models), where the "alphabet" was replaced by MIDI symbols. [1] What Jukebox (and other models) did well was work with raw audio, rather than rely on MIDI or similar transcriptions. They break down audio into "blocks" using Fast Fourier Transforms, then each block is "tokenized" and then fed into transformers, similar to GPT-3 or other newer text generation models. This now allows the "subtle" musicalities to be discovered by models without relying on transcription. Wavenet (from Google) [2] I believe was the first one to do this... I tried myself for 6 months, but the processing power required for this is candidly only available for the Google/OpenAIs of the world. >> the data is all locked up behind an impossible quagmire of copyright So my understanding is that the training of Jukebox is similar to Copilot. It was trained on the entire English Spotify catalogue so all that has been digested by the model - under Fair Use. But again - this is probably far from "settled" legally. [1] https://arxiv.org/abs/1612.07837 https://arxiv.org/abs/1612.07837 [2] https://www.deepmind.com/blog/wavenet-a-generative-model-for-raw-audio https://www.deepmind.com/blog/wavenet-a-generative-model-for...