AWS And Microsoft Double Down On Deep Learning With Gluon, A Simplified ML Model Builder

AWS and Microsoft may be arch rivals when it comes to competing for business in cloud storage and services, but when it comes to breaking ground in newer areas where volumes of data make a difference to how well the services work and creating systems that are easier to use, collaboration is key. 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.

Gluon is one of the big steps ahead in taking out some of the grunt work in developing AI systems by bringing together training algorithms and neural network models, two of the key components in a deep learning system.

“The potential of machine learning can only be realized if it is accessible to all developers. 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, in a statement. “We created the Gluon interface so building neural networks and training models can be as easy as building an app. We look forward to our collaboration with Microsoft on continuing to evolve the Gluon interface for developers interested in making machine learning easier to use.”

Gluon was developed by the two as an open-source project and is aimed at prototyping, building, training and deploying machine learning models for the cloud, devices at the edge and mobile apps, the companies said. Gluon is launching today and initially working with the deep learning engine Apache MXNet and Amazon said today that it will support Microsoft Cognitive Toolkit (CNTK), another deep learning engine, “in an upcoming release.”

Machine learning models are crucial to how artificial intelligence systems work today: essentially developers build these models to help run different services, whether they be messaging bots, scripts for voice-based home hubs, face-recognition apps or autonomous driving systems. But then these models need to “learn” what to do by ingesting vast quantities of data, and that is where the collaboration between the two is key: tapping into as wide a range of developers as possible is a way to bring a lot more data into the system. (Notably, there are startups like Mighty AI that are also working on this problem and how to solve it.)

This is not the first time the two have collaborated on AI initiatives. The two work together in the Cloud Native Computing Foundation. And last September, Amazon and Microsoft — along with Facebook, Google and IBM — announced the Partnership on AI to collaborate more on research and best practices in this newly emerging area.

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AWS and Microsoft double down on deep learning with Gluon, a simplified ML model builder