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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

Companies face complex regulations and extensive approval requirements from governing bodies like the US Food and Drug Administration (FDA). Users then review and edit the documents, where necessary, and submit the same to the central governing bodies. This post is co-written with Ilan Geller, Shuyu Yang and Richa Gupta from Accenture.

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Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

AWS Machine Learning

Data and model management provide a central capability that governs ML artifacts throughout their lifecycle. Integrations with CI/CD workflows and data versioning promote MLOps best practices such as governance and monitoring for iterative development and data versioning. It enables auditability, traceability, and compliance.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

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Calabrio Charts Record Year-on-Year UK Growth as Demand for Cloud Technology Soars During Lockdown

CSM Magazine

“Coupled with businesses operating solely online, we have also seen strong demand across the board from more traditional sectors such as finance, insurance, retail, consumer goods, local and central government departments. These organisations require an innovative yet reliable solution to help them manage unprecedented levels in demand.”.

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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

We recommend following certain best practices that are highlighted through the concepts detailed in the following resources: Building secure machine learning environments with Amazon SageMaker Setting up secure, well-governed machine learning environments on AWS Clone the GitHub repo into your environment.

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EVERYTHING YOU NEED TO KNOW ABOUT STIR/SHAKEN

Hodusoft

Many government organizations use them to send important and urgent updates. In later years, STIR/SHAKEN was developed jointly by the SIP Forum and the Alliance for Telecommunications Industry Solutions (ATIS) to efficiently implement the Internet Engineering Task Force (IETF). Now, not all robocalls are bad.

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Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

Supply Chain Disruptions The COVID-19 pandemic has highlighted the vulnerability of global supply chains, and the EV industry has not been. Regulatory Frameworks and Incentives Regulatory frameworks and government incentives play a critical role in promoting EV.