by Angela Guess

According to a recent press release, “Today, Amazon Web Services Inc., an Amazon.com company, and Microsoft Corp. announced a new deep learning library, called Gluon, that allows developers of all skill levels to prototype, build, train and deploy sophisticated machine learning models for the cloud, devices at the edge and mobile apps. The Gluon interface currently works with Apache MXNet and will support Microsoft Cognitive Toolkit (CNTK) in an upcoming release. With the Gluon interface, developers can build machine learning models using a simple Python API and a range of pre-built, optimized neural network components. This makes it easier for developers of all skill levels to build neural networks using simple, concise code, without sacrificing performance. AWS and Microsoft published Gluon’s reference specification so other deep learning engines can be integrated with the interface.”

The release goes on, “Developers build neural networks using three components: training data, a model and an algorithm. The algorithm trains the model to understand patterns in the data. Because the volume of data is large and the models and algorithms are complex, training a model often takes days or even weeks. Deep learning engines like Apache MXNet, Microsoft Cognitive Toolkit, and TensorFlow have emerged to help optimize and speed the training process. However, these engines require developers to define the models and algorithms up-front using lengthy, complex code that is difficult to change. Other deep learning tools make model-building easier, but this simplicity can come at the cost of slower training performance.”

Read more at Business Wire.

Photo credit: AWS