Inside Advanced Scale Challenges|Wednesday, December 13, 2017
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‘AI Layer’ Seeks to Fill Machine Learning Gaps 

It has been asserted that the algorithm has overtaken traditional software code as the driving force behind the AI Era. On the assumption that assertion is accurate, startups are beginning to offer tools for building what one refers to as "algorithm portfolios" used to deploy AI and machine learning models in enterprise applications.

Among them is application builder Algorithmia, which this week released an "AI Layer" designed to accelerate the development and deployment of machine learning models. The Seattle-based startup claims its AI Layer fills a gap in the current AI infrastructure that prevents AI and machine learning investments from reaching production.

Algorithmia notes that developing and implementing machine learning models has become an arduous and expensive task. Model developers still face a "last mile" to deployment problem for lack of AI infrastructure, it notes.

The company's API is touted as enabling data scientists to automate deployment of machine learning models to production using TensorFlow or other open source machine learning libraries.

Read the full story at sister web site Datanami.

 

About the author: George Leopold

George Leopold has written about science and technology for more than 25 years, focusing on electronics and aerospace technology. He previously served as Executive Editor for Electronic Engineering Times.

One Response to ‘AI Layer’ Seeks to Fill Machine Learning Gaps

  1. Rajesh Nair

    Hi George, I really liked reading this article, great topic! And, you’re very correct that the startups are beginning to offer tools for building “algorithm portfolios” used to deploy AI and machine learning models… Also, the article link given at the end that landed on a page which has very much detailed information on AI layer and cloud computing technologies. Thanks much Geaorge for sharing such an informative article here.

     

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