A primary goal of the Magenta project is to demonstrate that machine learning can be used to enable and enhance the creative potential of all people.

The demos and apps listed on this page illustrate the work of many people--both inside and outside of Google--to build fun toys, creative applications, research notebooks, and professional-grade tools that will benefit a wide range of users.



Web Apps

This section includes hosted browser-based applications, many of which are implemented with TensorFlow.js for WebGL-accelerated inference.

Colab Notebooks

Colaboratory is a Google research project created to help disseminate machine learning education and research. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud.

We provide notebooks for several of our models that allow you to interact with them on a hosted Google Cloud instance for free.

Native Apps

Native applications run on your local machine and typically require you to install additional software, but are sometimes better suited for professonal use.


  • NSynth Super [ blog | code ]

    NSynth Super is an experimental physical interface for the NSynth model.

    NSynth uses deep neural networks to generate sounds at the level of individual samples. Learning directly from data, NSynth provides artists with intuitive control over timbre and dynamics, and the ability to explore new sounds that would be difficult or impossible to produce with a hand-tuned synthesizer.


Community Contributions

Community contributions were all created without the involvment of Google, using Magenta models and libraries. If you have a demo that you think belongs here, please share it via our discussion group.