AWS, Microsoft Collaborate on Deep Learning with 'Gluon'
Amazon Web Services (AWS) and Microsoft this week put their long-running cloud rivalry on hold to unveil a new joint project: an open source deep learning library called "Gluon."
Gluon is an API that lets developers, even those with little experience in machine learning, use the Python programming language and some pre-included deep learning templates to build the models that run neural networks in less time and with less coding complexity. In their respective announcements on Tuesday announcing the project, AWS and Microsoft described Gluon as "an open source deep learning interface [that] allows developers to more easily and quickly build machine learning models without compromising training performance."
Typically, the process of building a neural network can take as long as a week or more, as developers train network models to finely parse large volumes of data. Besides being time-consuming, it's also labor-intensive, often requiring developers to write long lines of complex code that are hard to modify, debug and reuse.
Altogether, the requirements of building a neural network are taxing for even experienced developers and can be prohibitively complicated for beginners. AWS and Microsoft developed Gluon in an effort to remove these barriers.
"At AWS, we've been experimenting with some ideas in MXNet around new, flexible, more approachable ways to define and train neural networks. Microsoft is also a contributor to the open source MXNet project, and were interested in some of these same ideas. Based on this, we got talking, and found we had a similar vision: to use these techniques to reduce the complexity of machine learning, making it accessible to more developers," said Matt Wood, AWS general manager of AI, in a blog post.
According to the two companies, there are four attributes that set Gluon apart from other deep learning tools. First, the Gluon interface lets developers use "simple, clear, concise" code to build networks, according to Wood. Second, it lets them create more "dynamic" networks that are easier to debug and adapt. Third, it enables developers to create "more sophisticated algorithms and models." Fourth, it provides these benefits without slowing down the training process.
Gluon is not the first time that AWS and Microsoft have collaborated around AI; in August, the two companies agreed to let their respective voice-responsive digital assistants, Alexa and Cortana, interact with each other in a bid to improve productivity for their customers. "The collaboration between Microsoft and Amazon reflects our belief that when people and technology work together, everybody wins," Microsoft said of the Cortana-Alexa integration at the time.
The Gluon project appears to have sprung from that same philosophy. "We believe it is important for the industry to work together and pool resources to build technology that benefits the broader community. This is why Microsoft has collaborated with AWS to create the Gluon interface and enable an open AI ecosystem where developers have freedom of choice," said Eric Boyd, corporate vice president of AI and Research at Microsoft, in an announcement.
Available on GitHub here, Gluon currently supports Apache MXNet. A future release will add support for the Microsoft Cognitive Toolkit, as well as other frameworks, according to the two companies.
Gladys Rama (@GladysRama3) is the editor of Redmondmag.com, RCPmag.com and AWSInsider.net, and the editorial director of Converge360.