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BLOCKCHAIN | BUSINESS | CLOUD | MOBILE |
Cloud leader, Amazon Web Services or AWS, is taking yet another major reinvention that will help further revolutionize machine Learning and cloud computing structure over the web.
Machine learning has become increasingly pervasive. In recent years, more and more business organizations are realizing the benefits of advanced analytics and Artificial Intelligence in terms of boosting their productivity and market value and increasing their profit as a whole.
Strengthening the Path to a Machine Learning-Driven Era
Machine learning has become a favorite topic by most companies during conversations. At an event’s press briefing Andy Jassy, AWS CEO, stated that he believes that the world is entering the golden age of what is going to be possible in applications. According to him, in five or ten years from now virtually every application will embrace machine learning and AI.
Machine learning has remarkably remained as AWS’s major growth area. In the realm of automation and tech-driven era, AWS has announced their launching of additional 13 completely new products and services in their already rich portfolio of smart applications and deep analytics tools. In his keynote speech, Jassy made some announcements of the company working on significantly expanding its reach in the machine learning market.
AWS is rallying towards enhancing the value of AWS to enterprise customers. In their latest developments, AWS is putting reinforcement learning on the spotlight.
As part of the AWS reinvention, AWS features the expansion of their SageMaker development platform. In just a year since the SageMaker was introduced in the industry, Jassy said that the platform has been used by more than 10,000 of their customers already. A managed service for data scientists and developers, SageMaker is slated to help quickly build, deploy, manage, and train AWS Machine Learning models. Among the features added in the improved SageMaker service include cost-effective, automatic data labelling and reinforcement learning.
Here are some of the AWS developments recently introduced by Amazon as part of their efforts in pushing Machine Learning in the market:
Textract – Amazon Textract is a service that allows for easier data and text extraction from virtually any document.
Amazon Comprehend Medical – This is an AWS service feature that provides natural language processing for medical information.
Amazon Personalize – Today’s consumers prefer customized and more personalized solutions, Amazon Personalize allow customers to configure, customize, and personalize various cloud services to suit their unique needs.
Amazon Forecast – This machine Learning tool will enable developers to generate forecasts based on time-series data easily. The service utilizes the same technology being used by Amazon.com, its parent company.
Amazon Timestream – A fully manageable time series database service for IoT and operational applications, Timestream is big on speed and scalability and allows for an easier and more cost-effective way of processing and storing massive amounts of data.
AWS Inferentia – This is a machine learning inference chip which is designed to deliver excellent performance at a lower cost. The chip is designed specifically to support the deployment of large models of GPU with AI and is scheduled to be released in 2019.