For cases where someone’s computer or device might not be fast enough to run the Doodle using TensorFlow.js, the Doodle is also served with Google’s new Tensor Processing Units (TPUs), a way of quickly handling machine learning tasks in data centers- yet another Doodle first! Next came our partners at PAIR who used TensorFlow.js to allow machine learning to happen entirely within the web browser (versus it running utilizing tons of servers, as machine learning traditionally does). This concise structure made them good training data for a machine learning model. Specifically, Coconet was trained on 306 of Bach’s chorale harmonizations. His chorales always have four voices, each carrying their own melodic line, while creating a rich harmonic progression when played together. The model used in today's Doodle was developed by Magenta Team AI Resident Anna Huang, who developed Coconet: a versatile model that can be used in a wide range of musical tasks-such as harmonizing melodies or composing from scratch (check out more of these technical details in today’s Magenta blog post). Machine learning is the process of teaching a computer to come up with its own answers by showing it a lot of examples, instead of giving it a set of rules to follow as is done in traditional computer programming.
The first step in developing the Doodle? Creating a machine learning model to power it. With the press of a button, the Doodle then uses machine learning to harmonize the custom melody into Bach’s signature music style (or a Bach 80's rock style hybrid if you happen to find a very special easter egg in the Doodle.:)).
Today we celebrate world renowned German composer and musician Johann Sebastian Bach with our first ever AI-powered Doodle! Made in partnership with the Google Magenta and Google PAIR teams, the Doodle is an interactive experience encouraging players to compose a two measure melody of their choice. Go behind-the-scenes of today’s Doodle below!
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