Amazon brings AWS hardware and services direct to the data centre

AWS goes deep and wide with machine learning services and capabilities

AWS caters to customers who want to build from the ground up, while also adding services over time like AWS Elastic Beanstalk, Amazon Lightsail, and Amazon SageMaker that are created to serve the needs of this second type of builder.

Amazon Comprehend Medical uses natural language processing to simplify the process of using machine learning to extract pertinent information from unstructured medical text, such as medical notes, prescriptions, interview transcripts, and pathology and radiology reports.

AWS Native is for those preferring to use the same APIs on-prem that they're already running in AWS's cloud - allowing users to run AWS services in their own data centres. For advanced developers and scientists who are comfortable building, tuning, training, deploying, and managing models themselves, AWS offers P2 and P3 instances at the bottom of the stack-which provide up to six times better performance than any other GPU instances available in the cloud today-together with AWS's deep learning AMI that embeds all the major frameworks, such as TensorFlow and MXNet.

Shawn Bice, Vice President, Nonrelational Databases at AWS said, "Earlier this year, when we started talking to customers about what they needed from a blockchain solution, we realised that the Amazon QLDB's ledger technology met a lot of their requirements".

"There are still some countries in the world where there are issues around data sovereignty and data residency", he said, meaning a true hybrid option could be of keen interest to certain clients residing in geographies where AWS doesn't have a region, like Switzerland for example. The new plugins include the most popular Amazon services such as Amazon Simple Email Service (Amazon SES), Amazon Simple Storage (Amazon S3), Amazon Elastic Compute Cloud (Amazon EC2), Amazon Virtual Private Cloud (Amazon VPC), Amazon Simple Queue Service (Amazon SQS), Amazon Relational Database Service (Amazon RDS) and AWS CloudTrail. "The process of developing clinical trials and connecting them with the right patients requires research teams to sift through and label mountains of unstructured medical record data".

Amazon is diving deeper into healthcare with the launch of Amazon Comprehend Medical, a machine-learning service created to help providers and other healthcare stakeholders extract information from unstructured data in electronic health records (EHRs).

AWS will reportedly allow its customers to rent access to the ground stations the same way that access to its data centers is leased.

Apple grilled on App Store pricing
But the suit said Apple collected the payments from iPhone users, keeping a 30 percent commission on each transaction. Apple has denied it engaged in anti-competitive behaviour, saying the prices for apps were set by app developers.


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How the machine learning service will fit in with Amazon's other healthcare endeavors remains to be seen, but there is little question that the company is gunning for a level of insight into personal health that will place it head and shoulders above any other competitors.

AWS also announced a related partnership with Lockheed Martin Corp.to integrate Ground Stations with the aerospace giant's new Verge antenna network. They can also process their data using AWS services, like for analytics, storage, processing, and streaming.

Yet another new Amazon SageMaker offering, SageMaker Neo, optimizes machine learning models to run faster and use less resources.

The winners of each race will advance to the AWS DeepRacer 2019 Championship Cup at next year's Re:invent conference.

However, it seems Amazon no longer perceive the blockchain as it used to in the past.

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