Magenta is a research project analyzing the function of machine learning in creating art and music.
Magenta focuses on developing new deep learning and reinforcement learning algorithms for generating songs, images, drawings and other materials. It also constructs smart tools and interfaces allowing artists and musicians to extend their processes using these models.
The started in 2016 by researchers and engineers from the Google Brain team. It is led by Doug Eck, a research scientist. They use TensorFlow and release their models and tools in open source on GitHub.
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People
Further reading
Aaron van den Oord, Nal Kalchbrenner and Koray Kavukcuoglu
Pixel Recurrent Neural Networks
Academic paper
Alex Graves
Generating Sequences With Recurrent Neural Networks
Academic paper
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende and Daan Wierstra
DRAW: A Recurrent Neural Network For Image Generation
Academic paper
Leon A. Gatys, Alexander S. Ecker and Matthias Bethge
A Neural Algorithm of Artistic Style
Academic paper
Nicolas Boulange, Yoshua Bengio and Pascal Vincent
Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription
Academic paper
Documentaries, videos and podcasts
Magenta: Music and Art Generation (TensorFlow Dev Summit 2017)
15 February 2017
Companies
Categories
Related Topics
Machine learningA field of computer science enabling computers to learn.
Deep learningBranch of machine learning based on learning data representations.
Reinforcement LearningAn area of machine learning focusing on how machines and software agents react in a specific context to maximize performance and achieve reward known as reinforcement signal
