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MXNet now chosen by Amazon as Deep Learning Framework

Amazon has announced that it has chosen MXNet as its deep learning framework of choice for its web services(AWS). Amazon extensively uses machine learning in areas like fraud detection, abusive review detection, and book classification. Amazon also uses it in application areas such as text and speech recognition, autonomous drones etc… Amazon did not opt for some of the popular machine learning frameworks such as TensorFlow and Torch because they stated that MXNet scales and runs better than any other framework which is out there. The notable features of the MXNet were stated as its cross-platform portability and compact size. Amazon also stated that they will be further working with other organizations to advance the MXNet. How these frameworks are selected? According to the blog post by Amazon, the deep learning framework is selected depending on three major factors: Ability to scale, Development speed, and Portability. The main reason for Amazon to choose MXNet seems to be for its scalability. Werner Vogels,  chief technology officer and Vice President of Amazon.com stated that the speedup gained by running MXNet across multiple GPUs was highly linear and according to the benchmarks conducted across 128 GPUs, it performed 109 times faster compared to the single GPU setup. MXNet can mix both programming models(declarative and imperative) and also can be coded with a wider range of programming languages such as C++, Python, Javascript etc… making development with MXNet much easier. The portability of the MXNet is also praised for its ability to run across platforms, core library able to fit into single C++ source file which can then be compiled both on iOS and Android. It was also stated that it can be run on the browsers too, by using Javascript extensions.
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MXNet now chosen by Amazon as Deep Learning Framework

Geneva Clark
What's New
24th Nov, 2016
MXNet now chosen by Amazon as Deep Learning Framework

Amazon has announced that it has chosen MXNet as its deep learning framework of choice for its web services(AWS). Amazon extensively uses machine learning in areas like fraud detection, abusive review detection, and book classification. Amazon also uses it in application areas such as text and speech recognition, autonomous drones etc…

Amazon did not opt for some of the popular machine learning frameworks such as TensorFlow and Torch because they stated that MXNet scales and runs better than any other framework which is out there. The notable features of the MXNet were stated as its cross-platform portability and compact size. Amazon also stated that they will be further working with other organizations to advance the MXNet.

How these frameworks are selected?

According to the blog post by Amazon, the deep learning framework is selected depending on three major factors: Ability to scale, Development speed, and Portability.

The main reason for Amazon to choose MXNet seems to be for its scalability. Werner Vogels,  chief technology officer and Vice President of Amazon.com stated that the speedup gained by running MXNet across multiple GPUs was highly linear and according to the benchmarks conducted across 128 GPUs, it performed 109 times faster compared to the single GPU setup.

How these frameworks are selected?

MXNet can mix both programming models(declarative and imperative) and also can be coded with a wider range of programming languages such as C++, Python, Javascript etc… making development with MXNet much easier.

The portability of the MXNet is also praised for its ability to run across platforms, core library able to fit into single C++ source file which can then be compiled both on iOS and Android. It was also stated that it can be run on the browsers too, by using Javascript extensions.

Geneva

Geneva Clark

Blog Author
Geneva specializes in back-end web development and has always been fascinated by the dynamic part of the web. Talk to her about modern web applications and she and loves to nerd out on all things Ruby on Rails.

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