Google's Magenta Seeks to Leverage TensorFlow for Art and Music

As we've noted, artificial intelligence and machine learning are going through aamini-renaissance right now. Google recently made a possibly hugely influential contribution to the field of machine learning. It has open sourced a program called TensorFlow that is freely available. It’s based on the same internal toolset that Google has spent years developing to support its AI software and other predictive and analytics programs.

In a related open project from the Google Brain team, dubbed Magenta, Google is calling for efforts to leverage TensorFlow and machine learning to create compelling art and music. Some of the early examples from this effort are eye-opening.

According to Google Research:

"Can we use machine learning to create compelling art and music? If so, how? If not, why not? We’ll use TensorFlow, and we’ll release our models and tools in open source on our GitHub. We’ll also post demos, tutorial blog postings and technical papers. Soon we’ll begin accepting code contributions from the community at large. If you’d like to keep up on Magenta as it grows, you can follow us on our GitHub and join our discussion group."

"Magenta has two goals. First, it’s a research project to advance the state of the art in machine intelligence for music and art generation. Machine learning has already been used extensively to understand content, as in speech recognition or translation. With Magenta, we want to explore the other side—developing algorithms that can learn how to generate art and music, potentially creating compelling and artistic content on their own."

"Second, Magenta is an attempt to build a community of artists, coders and machine learning researchers. The core Magenta team will build open-source infrastructure around TensorFlow for making art and music. We’ll start with audio and video support, tools for working with formats like MIDI, and platforms that help artists connect to machine learning models."

 Consider an early Magenta performance model here.

To start, Magenta is being developed by a small team of researchers from the Google Brain team. If you’re a researcher or a coder, you can check out the alpha-version code. Once Google has a stable set of tools and models, it will invite external contributors to check in code to GitHub. 

We also reported on how H2O.ai, formerly known as Oxdata, has announced a new funding round that it is getting to the tune of $20 million. The money will go toward advancing its machine learning toolset, and the company is entirely open source-focused. We recently caught up with Oleg Rogynskyy, VP of Marketing & Growth at H2O, for an interview.

Meanwhile, Facebook is open sourcing its machine learning system designed for artificial intelligence (AI) computing at a large scale. It's based on Nvidia hardware. And, IBM announced that its proprietary machine learning program known as SystemML will be freely available to share and modify through the Apache Software Foundation.

And, Yahoo has released its key artificial intelligence software (AI) under an open source license. The company previously developed a library called CaffeOnSpark to perform a popular type of AI called “deep learning” on the big troves of data found in its Hadoop file system. Now CaffeOnSpark is becoming available for community use under an open source Apache license on GitHub.