The idea is that with AWS's new service, developers can use machine learning with the applications they build and run on the company's cloud.
In an effort to make it easy for users to work with the data they already have stored in the AWS cloud, the new service is integrated with Amazon Simple Storage Service (Amazon S3), Amazon Redshift and Amazon Relational Database Service (Amazon RDS).
"It's a cool thing and Amazon does know what it's doing when it comes to analytics," said Dan Olds, an analyst with The Gabriel Consulting Group. "Amazon counts on analytics to make its business model work. There are analytics working behind the scenes to predict what people might want to purchase next or to inform users what others have purchased. Plus, there are all of the back office analytics that tell Amazon decision makers how to best set up and stock the Amazon store."
That kind of capability would help a lot of enterprises actually use their data. "The combination of machine learning and big data can result in companies gaining insights that they'd probably never have considered before," added Olds.
Patrick Moorhead, an analyst with Moor Insights & Strategy, noted that while large enterprises could build their own machine learning system, using a cloud-based service would save them the massive expense, time and effort needed to build their own AI tools.
"When you combine the cloud, big data, and machine learning together, you get scalable capabilities to analyze and respond to a myriad of things," he said. "With a service, you don't need to procure, setup, find space for the hardware nor do you have to be an expert in datacenter software. You need to know the correct algorithms for measurement or find a way to get the data to AWS.
"This just makes it a lot easier," said Moorhead.
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