What is AWS DeepComposer Chartbusters?
Chartbusters is a global challenge where developers use AWS DeepComposer to create original compositions and compete in monthly challenges to showcase their machine learning and generative AI skills.
Every month, AWS will release a Chartbusters challenge that has a unique theme such as building a custom genre model, or extending a melody using machine learning. These monthly themes span a breadth of generative AI techniques such as GANs, autoregressive models, and transformers.
Developers will use AWS DeepComposer to create their original compositions and submit them to a Chartbusters playlist on SoundCloud. SoundCloud Terms and Conditions may apply.
Listeners from around the world will be invited to vote on the compositions. After the judges select the top 10 compositions based on the judging criteria, the sum of customer ‘likes’ and 'playcount’ on SoundCloud will be used as tie-breakers.
The winner of this month’s challenge will receive a one-hour mentorship session with an AWS ML expert and will be interviewed and featured in an AWS ML blog post. The winner will also receive an AWS DeepComposer Chartbusters gold record mailed to their physical address.
November 5, 2020 – January 31, 2021
You can now extend a melody beyond 8 bars by up to 20 seconds and create an original piece of music using the new generative Artificial Intelligence (AI) technique we have added: Transformers! Use Transformers and compete in our next Chartbuster challenge, Keep Calm and Model On! It is easy to compete: pick one of the sample melodies on the AWS DeepComposer Music Studio, choose Transformers from the list of techniques, adjust hyperparameters, and extend the melody. Create as many compositions as you like; once you like the melody, download, choose “Chartbusters” in the navigation bar, and submit your composition to SoundCloud via the AWS DeepComposer console. Although you don’t need a physical keyboard to compete, take advantage of a limited-time offer and purchase the AWS DeepComposer keyboard at a special price of $79.20 (20% off) on amazon.com. The pricing includes the keyboard and a 3-month free trial of AWS DeepComposer service.
AWS AI Vice President and Distinguished Scientist
Alex is Vice President and Distinguished Scientist in AWS AI. He is responsible for deep learning research, algorithm design, open source libraries and education. In his role Alex leads the Machine Learning University team whose role it is to teach everyone about ML. He manages teams working on AutoGluon (an easy to use high quality AutoML tool), DGL (deep learning on graphs), the D2L.ai (Dive into Deep Learning) project, toolkits on Computer Vision, NLP, Deep Learning Compilers and the MXNet Framework team. Prior to joining Amazon in 2016 Alex was professor in Machine Learning at Carnegie Mellon University, UC Berkeley and the Australian National University. He worked at Yahoo, Google and founded Marianas Labs. Alex has published over 200 papers and 6 books.
AWS AI Senior Applied Scientist
Sahika Genc is a senior applied scientist at Amazon artificial intelligence (AI). Her research interests are in smart automation, robotics, predictive control and optimization, and reinforcement learning (RL), and she serves in the industrial committee for the International Federation of Automatic Control. She leads science teams in scalable autonomous driving and automation systems, including consumer products such as AWS DeepRacer and SageMaker RL. She has more than 30 patents and 50 conference, journal, and technical report publications. She earned her MS and PhD degrees in electrical engineering systems from the University of Michigan-Ann Arbor.
AWS ML Hero
Alex works in the Innovation Labs at Advanced Solutions where he develops machine-learning enabled products and solutions for the biomedical and product distribution industries. As an active advocate for AWS, and as an AWS ML hero, he runs the Fort Wayne AWS User Group and loves to share his knowledge and experience with other developers. He especially enjoys teaching others how they utilize tools like AWS SageMaker, AWS DeepLens, AWS DeepRacer, and AWS DeepComposer to get started with Machine Learning.