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Amazon’s DSSTNE machine learning tech is now open source

amazon open source product recommendation tech prime price increase
Machine learning isn’t just about researchers digging into hypotheticals in sterile labs. Major corporations use this kind of artificial intelligence to help with the complexities of serving a massive, often international audience — and now Amazon is making its machine learning software open source.

The company’s Deep Scalable Sparse Tensor Network Engine — otherwise known as DSSTNE and pronounced “destiny” — is now available to anyone who’s interested in tinkering with it. Amazon hopes that outside influences will help make the platform even more powerful than it already is, according to a report from Engadget.

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“DSSTNE is built for production deployment of real-world deep learning applications, emphasizing speed and scale over experimental flexibility,” reads documentation that accompanies the files released by Amazon.

Internally, DSSTNE is used to deliver purchase recommendations to consumers based on their order histories. Product recommendations are big business for Amazon, as having such a daunting catalog of merchandise is really rather worthless unless customers are able to discover items that are relevant to their interests.

Making DSSTNE open source might allow a third party to offer up improvements that slipped under the nose of the developers at Amazon. However, it also allows the retailer to demonstrate an ability to compete with some of the biggest names in tech.

Last November, Google announced plans to make its proprietary TensorFlow deep learning system open source. Between Amazon implementing a similar tactic with DSSTNE and the company’s continued interest in IoT devices, it’s clear that technology is a huge focus for the 20-year-old online retail giant.

DSSTNE is available now from the Amazon Labs account on GitHub for anyone looking to put a powerful machine learning tool through its paces. Novices are advised to dip their toe in the water by checking out the accompanying setup guide.

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