AWS Announces 13 New ML Services and Capabilities, Including a Custom Chip

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The announcement was made on Wednesday by Amazon at the Invent conference.

According to an official release statement from Amazon, the new platform operates as "a fully managed service", which means it is designed to make it easy for users to create and then manage their own scalable blockchain networks.

With NeoPulse, organizations can build sophisticated and accurate AI models with as little as 14 lines of code. Ultrain proclaimed that its smart contract developer framework is now available open-sourced.

There's no word yet on the exact prices AWS will demand for its services, and Amazon isn't sharing how much it will cost them to build the satellite stations.

Among the other provider of the public cloud services, Amazon is also following the Google into the chip market.

AWS Security Hub integrates with Amazon CloudWatch and AWS Lambda, allowing customers to execute automated remediation actions based on specific types of findings.

All told, AWS announced 13 new machine learning capabilities and services that run across all layers of the machine learning stack, which will no doubt give developers plenty of space to work and play in.

As such, Amazon Comprehend Medical's proposition to healthcare stakeholders relies not only on its technological backbone but the promise of a simpler, more cost-efficient path toward that data. "With greater connectivity to DigitalGlobe's high-resolution constellation and more downlink capacity, our collection planning teams can now optimize the interval from planning to image collection, downlink, and analysis - especially valuable when time matters", said Jeff Culwell, Chief Operations Officer, DigitalGlobe. Adding a listing to the Marketplace is completely self-service for developers who want to sell through AWS Marketplace.

Amazon SageMaker RL addresses the complexity of reinforcement learning, which uses an algorithm achieve a complex goal that learns from right and wrong decisions as it explores its environment, usually in a simulator.

Amazon Web Services' encroachment into enterprise IT went one step further yesterday with the cloud giant announcing the hardware it uses to power its own cloud is available to purchase. Amazon Textract allows developers to quickly automate document workflows, processing millions of document pages in a few hours.

Amazon said the QLDB is a new class of database that provides a transparent, immutable, and cryptographically verifiable ledger that customers can use to build applications that act as a system of record, where multiple parties are transacting within a centralised, trusted entity. A new process called AutoML, which automates complicated ML tasks, "performs and accelerates the hard work required to design, train, and deploy a machine learning model", the company says. Called AWS Outposts, it's the same EC2 hardware AWS uses in its own datacentres. You pay only for what you use and there are no minimum fees or upfront commitments. Users provide the historical and "causal" (eg, the weather, or any special offers) data, and Forecast creates, trains and optimises a model that can generate forecasts.