Open source AI at AWS and Apache MXNet
A wide variety of open source frameworks and tools support artificial intelligence and deep learning. Adrian Cockcroft explains how AWS has packaged a number of themincluding deep learning frameworks such as Caffe, CNTK, Keras, MXNet, TensorFlow, Theano, and Torch and supporting tools like Jupyter and Anacondainto an Amazon Machine Image with optimized GPU support.
| Talk Title | Open source AI at AWS and Apache MXNet |
| Speakers | Adrian Cockcroft (Amazon Web Services) |
| Conference | O’Reilly Open Source Convention |
| Conf Tag | Making Open Work |
| Location | Austin, Texas |
| Date | May 8-11, 2017 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
A wide variety of open source frameworks and tools support artificial intelligence and deep learning. Adrian Cockcroft explains how AWS has packaged a number of them—including deep learning frameworks such as Caffe, CNTK, Keras, MXNet, TensorFlow, Theano, and Torch and supporting tools like Jupyter and Anaconda—into an Amazon Machine Image with optimized GPU support. (Amazon committers also contribute to key technologies, including Linux, Xen, and many of the Apache Hadoop related projects.) AWS decided to concentrate investment in MXNet and working with the other contributors, sponsored the project into the Apache incubator process. Adrian discusses why AWS picked Apache MXNet, explores the main features of the project, and provides a project status update. This session is sponsored by AWS.
