Gluon will provide developers with a Python API which they can use to prototype, build, and train complex machine learning models.
"Developers who are new to machine learning will find this interface more familiar to traditional code, since machine learning models can be defined and manipulated just like any other data structure", said Matt Wood, general manager of AI and deep learning services at AWS, in a blog post today.
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Neural networks are built on three core components: Training data, a model, and an algorithm, "The algorithm trains the model to understand patterns in the data", the release said.
Supporting both traditional imperative programming and symbolic programming - where computational results are represented in a graph - Gluon is essentially an abstraction layer created to work with deep-learning frameworks Apache MXNet and, soon, Microsoft's Cognitive Toolkit.
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"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. "This means it is much easier to debug, update and reuse neural networks". The interface can be used to develop models running on the cloud, edge devices and mobile apps. Several companies, including Intel, Qualcomm, AMD and ARM, are working with the Open Neural Network Exchange (ONNX) project to help create a shared representation of one popular form of machine learning. "AWS and Microsoft published Gluon's reference specification so other deep learning engines can be integrated with the interface".
This isn't the first time the two tech giants have partnered on AI. The Seattle-based companies are join forces to make deep learning accessible to all developers with the new deep library.
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Amazon and Microsoft on Thursday rolled out open-source software called Gluon in the stated hope of simplifying the implementation of machine learning. Eric Boyd, corporate vice president of Microsoft AI and Research, addressed this in the release, saying it's important for the pair to "pool resources to build technology that benefits the broader community".