The library gives developers an interface where they can prototype, build, train and deploy machine learning models for cloud and mobile apps, the companies explained in a joint press release.
The claim is that Gluon is a more concise, easy-to-understand programming interface compared to other offerings, and that it gives developers a chance to quickly prototype and experiment with neural network models without sacrificing performance.
"Today's reality is that building and training machine learning models requires a great deal of heavy lifting and specialized expertise," said Swami Sivasubramanian, VP of Amazon AI. "We created the Gluon interface so building neural networks and training models can be as easy as building an app."
The Gluon interface currently works with Apache MXNet and will also support Microsoft Cognitive Toolkit in an upcoming release. Developers can build machine learning models using a Python API and a range of pre-built, neural network components.
AWS and Microsoft also published Gluon's reference specification on GitHub to allow other deep learning engines to integrate with the interface.
"We believe it is important for the industry to work together and pool resources to build technology that benefits the broader community," added Eric Boyd, corporate VP of Microsoft AI and Research. "Machine learning has the ability to transform the way we work, interact and communicate. To make this happen we need to put the right tools in the right hands, and the Gluon interface is a step in this direction."
The Cortana Skills Kit allows developers to make use of services and/or bots created with the Microsoft Bot Framework and publish them to Cortana as a new skill. Developers using the kit also will have the option of repurposing code from existing Alexa skills.