Nov 28, 2019: Amazon Web Services (AWS) announced that it will release detailed features designed to make adding AI predictions to apps and services easier than before. Amazon says that machine learning predictions will soon run on relational or unstructured data in Aurora or Amazon S3, AWS’ cloud-hosted PostgreSQL and MySQL- compatible relational database service.
Using Athena or Aurora, customers will specifically be able to train models in Amazon’s SageMaker platform and run predictions against those models with SQL, Amazon’s interactive query service for analyzing data in Amazon S3.
The benefits extend to the AWS component, QuickSight, that lets customers create and publish dashboards that spotlight AI insights. QuickSight will visualize and report all model predictions from SageMaker and other AWS machine learning offerings, with the addition and configuration of a few statements to SQL queries, like Amazon’s Comprehend natural language processing service.
The idea behind the enhancements is to reduce the amount of custom code that must be written, managed, and supported in production, which boil down to direct calls from Aurora, Athena, and QuickSight to machine learning services. According to AWS principal Matt Asay, copying data from stores while transforming it between formats and feeding it to models not only sucks up time, but it complicates security and governance.
AI Driving AWS Revenues:
Chasing after an AI infrastructure market that’s anticipated to be worth $50.6 billion by 2025, Amazon’s investments in AI and machine learning services have accelerated in recent years. Including the NFL, AstraZeneca, and Celgene, the Seattle Company says that tens of thousands of customers now use its fully managed products like SageMaker and Comprehend, and it says it launched more than 200 machine learning capabilities and features in 2018 alone.
If you ask analysts like Jason Helstein at Oppenheimer, it’s a wise business direction. He noted in a recent report that AI can drive AWS revenues and margins as its capabilities are gradually embedded into cloud services. In the third fiscal quarter of 2019, AWS grew 45% in sales to $9 billion to this end, maintaining pole position ahead of Google Cloud and Microsoft Azure and accounting for 13% of Amazon’s total revenue.
About Amazon Web Services:
Amazon Web Services (AWS) is a line of on-demand cloud computing solutions designed for app developers, software engineers, and IT professionals, which enable users to power a variety of workloads including web and mobile applications, game development, data processing and warehousing, storage, as well as increase agility, and lower IT costs.
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