AWS, Microsoft launch deep learning library

AWS, Microsoft Team on 'Open AI'

With Gluon, developers can build machine learning models using a simple Python API and a range of pre-built, optimised neural network components. "We created the Gluon interface so building neural networks and training models can be as easy as building an app". Today, the two companies announced a new deep learning interface called Gluon, designed for developers of all abilities (not just AI specialists) to build and run machine learning models for their apps and other services. Third, such dynamism means the neural network model and its training algorithm can inform one another during the definition process and the training process.

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.

Eric Boyd, corporate veep of AI data and infrastructure at Microsoft, described the code as a way to - wait for it - democratize access to AI, both for researchers and for corporate customers. "It can be a fairly daunting and specialized practice for most data professionals".

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"The potential of machine learning can only be realized if it is accessible to all developers". Additionally, it will allow them to debug and update neural networks much more smoothly.

Gluon could be a good entry point for companies and developers to get started with deep learning, integrating machine learning into their other products. The approach allows users to reuse existing building blocks in the library. Speaking of the cloud, it's interesting that AWS and Microsoft-perhaps the top two players in the IaaS market-have partnered on such an endeavor. Note that deep learning engines such as Apache MXNet, Microsoft Cognitive Toolkit and TensorFlow do optimize the training processes to some extent, but often require a lot of time and complex coding, on the developer's part. AWS and Microsoft are positioning their "friendly API" as helping developers avoid arcane methods for defining networks "and their associated weighted scoring functions", Wood of AWS noted.

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. Microsoft and Amazon said in a joint press release today that building machine learning models can be very hard, requires a lot of time and processing power.

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