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12 October 2017, 10:20 | Casey Mitchell
Gluon is now compatible with Apache MXNet, AWS's preferred machine learning framework, and Microsoft is working to enable its compatibility with its Cognitive Toolkit. This makes it easier for developers of all skill levels to build neural networks using simple, concise code, without sacrificing performance.
Although Amazon and Microsoft are rivals in the cloud business, it's great to see the two collaborate on a project which can end up bettering humanity.
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The Gluon interface, announced in a joint press release on Thursday, lets developers use a Python API and pre-built neural network components to build machine learning models. Optimising the processMicrosoft and Amazon said Gluon addresses one of the biggest trade-offs in neural network creation. AWS and Microsoft published Gluon's reference specification so other deep learning engines can be integrated with the interface.
Further, they said Gluon code could be used to build deep learning components such as convolutional networks for applications ranging from object detection and speech recognition. New models have to be trained with large datasets, a process which can take days or weeks to complete. Aimed at programmers "of all skill levels", it enables new machine learning models to be created with "simple, concise" Python code. "We created the Gluon interface so building neural networks and training models can be as easy as building an app".
Essentially, the two companies built Gluon "so building neural networks and training models can be as easy as building an app", Swami Sivasubramanian, vice president of Amazon AI, said in the release. The Seattle-based companies are join forces to make deep learning accessible to all developers with the new deep library.
Gluon is available today, and you can check it out on GitHub here. Integrating with Apache MXNet and Microsoft Cognitive Services is a start but for now teams using architecture from Google or Amazon are unable to access Gluon's benefits.
AI development, "especially deep learning models, isn't easy", added Microsoft's Eric Boyd. Developers can learn how to get started using Gluon with MXNet by viewing tutorials for both beginners and experts available by visiting: https://mxnet.incubator.apache.org/gluon/.
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