https://github.com/msieg/deep-music-visualizer
https://www.instagram.com/deep_music_visualizer/
https://www.youtube.com/watch?v=L7R-yBZ5QYc
Want to make a deep music video? Wrap your mind around BigGAN. Developed at Google by Brock et al. (2018)¹, BigGAN is a recent chapter in a brief history of generative adversarial networks (GANs). GANs are AI models trained by two competing neural networks: a generator creates new images based on statistical patterns learned from a set of example images, and a discriminator tries to classify the images as real or fake. By training the generator to fool the discriminator, GANs learn to create realistic images.
This guide favors authenticity over accuracy, and it aims to entertain before it informs. It is only as accurate as it feels it needs to be. It is constantly changing and it is infinitely mutable, so the map, the music, and my self-righteous opinions are all subject to change as I discover, investigate, and incorporate new knowledge and more music. Nothing is definitive.
This is an educational resource, not a music sharing service. There are no complete songs here. All tracks are low quality sub-2 minute samples. If you want the music, do the artists a solid and buy it from them through legitimate channels.
This is an ongoing attempt at an algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 1211 genres by The Echo Nest. The calibration is fuzzy, but in general down is more organic, up is more mechanical and electric; left is denser and more atmospheric, right is spikier and bouncier.
Literary elites love to rep Shakespeare’s vocabulary: across his entire corpus, he uses 28,829 words, suggesting he knew over 100,000 words and arguably had the largest vocabulary, ever. I decided to compare this data point against the most famous artists in hip hop. I used each artist’s first 35,000 lyrics. That way, prolific artists, such as Jay-Z, could be compared to newer artists, such as Drake.
Music Theory for Musicians and Normal People by Toby W. Rush
This collection is a work in progress, but if you would prefer, you can download all the current pages as a single PDF.
How Aphex Twin hid pictures in his music
Digital harmony of the motion graphics of him
Search engine and discovery engine