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.
It took 200,000 years for our human population to reach 1 billion—and only 200 years to reach 7 billion. But growth has begun slowing, as women have fewer babies on average. When will our global population peak? And how can we minimize our impact on Earth’s resources, even as we approach 11 billion?
Le logiciel Lignes de temps met à profit les possibilités d’analyse et de synthèse offertes par le support numérique. Inspirées par les «timelines» ordinairement utilisées sur les bancs de montage numérique,
A Video Report on Data Visualization by Geoff McGhee
This piece of work is a bird's eye view of the history by scaling down a month length of time into one second. No letter is used for equal messaging to all viewers without language barrier. The blinking light, sound and the numbers on the world map show
C++ library designed to assist the creative process by providing a simple and intuitive framework for experimentation.
Videos of processing example
The language for intuitive relationships between humans and machines