Amazon Web Services (AWS) has announced some changes to its cloud storage services, including price cuts. It reduced the number of pricing tiers for Simple Storage Service (S3) from six to three, and it reduced prices for that service between 16 and 25 percent. The company also added more retrieval options to its Glacier storage and lowered its prices by 43 percent.
AWS announced that it had selected MXNet as its "deep learning framework of choice." The framework is highly scalable, and some observers speculate that that Amazon could integrate MXNet into a cloud-based machine learning offering.
MXNet caught InfoWorld's attention earlier this year as one of the Open Source Rookies of the Year 2016. Among its notable attributes are its compact size and cross-platform portability, both of which Amazon CTO Werner Vogels praised: "The core library (with all dependencies) fits into a single C++ source file and can be compiled for both Android and iOS." Developers can also use a wide variety of languages with the framework -- "Python, C++, R, Scala, Julia, Matlab, and JavaScript," as cited by Vogels.
But Amazon was likely most attracted to MXNet's scalability. Vogels published benchmarks for MXNet's training throughput using the Inception v3 image analysis algorithm and claimed that the speedup obtained by running it across multiple GPUs was highly linear. Across 128 GPUs, MXNet performed 109 times faster than with a single GPU.
It's safe to assume Amazon's long-term plans for MXNet include monetizing it by offering it as a cloud service. This doesn't have to be through Amazon's existing machine learning service; it could come from an officially supported machine image like the existing Deep Learning AMI that Amazon already sells. The former would be suitable for those who want an easily consumed product; the latter, for those who want total hands-on control.