Swim Takes ‘Open Core’ Route, Releases Machine Learning Platform for Edge Computing

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By open sourcing the core technology, Swim is hoping to attract developers who will take the platform in new directions

San Jose-based startup Swim has announced an open source version of its machine learning platform for edge computing.

Licensed under the Apache 2.0 license, the Open Source Edge Intelligence Platform, as it is now called, is a Java Virtual Machine extension that’s used in place of a traditional stack to analyse streaming data on the fly.

The software works through mesh-connected “digital twins” that utilize machine learning to predict changes in the data being created. It’s used by enterprises, equipment manufacturers, and Internet of Things (IoT) businesses to locally process and analyze large amounts of streaming data, according to Data Center Knowledge.

“In the Swim world, instead of having a data scientist build a model … the data builds the model automatically,” Simon Crosby, Swim’s co-founder and CTO, told Data Center Knowledge.

The open source version of Swim includes the digital twin platform and runtime for building and running apps, as well as a user interface framework, a software development kit, and a client for building streaming visualizations and embedding streaming UI components into existing apps.

It also includes streaming APIs for integrating data streams and analytical insights with existing UIs or external applications.

By open sourcing the core technology, Swim is hoping to attract developers who will take the platform in new directions. The company is also working to build and nurture a community of open source developers and users through its website.

 

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