{"id":1171,"date":"2017-10-25T11:53:07","date_gmt":"2017-10-25T08:53:07","guid":{"rendered":"https:\/\/community.virtono.com\/?p=1171"},"modified":"2020-06-10T16:45:57","modified_gmt":"2020-06-10T13:45:57","slug":"aws-and-microsoft-introduce-a-source-driven-ai-interface","status":"publish","type":"post","link":"https:\/\/www.virtono.com\/community\/internet-and-technology-news\/aws-and-microsoft-introduce-a-source-driven-ai-interface\/","title":{"rendered":"AWS and Microsoft introduce a source-driven AI interface"},"content":{"rendered":"
Gluon is another step towards standardized\u00a0APIs\u00a0for neural networks.\u00a0The interface is compatible with both\u00a0Microsoft’s\u00a0Cognitive Toolkit and\u00a0Apache\u00a0Mxnet.\u00a0It scales with more than 500 GPUs and is intended to deal with little rather than much data.<\/p>\n<\/header>\n
\n

Microsoft\u00a0and\u00a0Amazon Web Services (AWS)\u00a0co-operate and jointly present the deep-learning interface Gluon.\u00a0Both companies have issued an online report.\u00a0Gluon will be source for both the Microsoft Cognitive Toolkit and Apache Mxnet.<\/p>\n

Gluon is intended to be used for instructional, imperative programming and self-manipulable symbolic programming.\u00a0The second programming paradigm is particularly interesting in the development of artificial intelligence.\u00a0According to AWS, networks are made up of easy-to-understand nodes.\u00a0Developers should get an easy introduction to the programming of neural networks.<\/p>\n<\/div>\n

In addition, the API is designed for dynamically extensible neural networks.\u00a0A Gluon network should be able to train while it is running.\u00a0This is not possible with many other networks, which must always be stopped.\u00a0Developers can also directly influence a running network using standard algorithms, branches, and loops.<\/p>\n

Scalability and handling of sparse data<\/h3>\n

Gluon is closely linked to the backends of Mxnet and the Cognitive Toolkit, thus enabling the automatic distribution of compute load on several graphics processors.\u00a0Microsoft states that a training service can scale linearly to more than 500 GPUs.<\/p>\n

The API also supports models that can deal with sparse data rather than big data.\u00a0In addition, a trained model can be exported to local devices, such as smartphones or notebooks, and used there – hardware, on which usually only a small amount of data is available.<\/p>\n

Gluon is already available for Apache Amxnet\u00a0on the developer\u00a0portal\u00a0Github\u00a0.\u00a0Later, the support for Microsoft’s Cognitive Toolkit follows.\u00a0The API can be used on platforms such as Azure Data Science Virtual Machine or Azure Machine Learning.<\/p>\n

Gluon is not the first collaboration between Microsoft and another great partner.\u00a0Together with Facebook\u00a0, the company introduced ONNX\u00a0, an open-source AI framework.\u00a0KI and Machine Learning are supposed to be made available to everyone in general.<\/p>\n","protected":false},"excerpt":{"rendered":"

Gluon is another step towards standardized\u00a0APIs\u00a0for neural networks.\u00a0The interface is compatible with both\u00a0Microsoft’s\u00a0Cognitive Toolkit and\u00a0Apache\u00a0Mxnet.\u00a0It scales with more than 500 GPUs and is intended to deal with little rather than much data. Microsoft\u00a0and\u00a0Amazon Web Services (AWS)\u00a0co-operate and jointly present the deep-learning interface Gluon.\u00a0Both companies have issued an online report.\u00a0Gluon will<\/p>\n","protected":false},"author":4,"featured_media":1172,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[25],"tags":[],"class_list":["post-1171","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-internet-and-technology-news"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2017\/10\/20130906170823-0_0_0.jpg?fit=980%2C560&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p7ISfL-iT","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":143,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/difference-between-apache-http-and-apache-tomcat\/","url_meta":{"origin":1171,"position":0},"title":"Difference between Apache http and Apache Tomcat","author":"Daniel Draga","date":"July 23, 2016","format":false,"excerpt":"This article is part of series of articles on Apache. 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