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Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

AWS Machine Learning Blog

To address this need, AWS generative AI best practices framework was launched within AWS Audit Manager , enabling auditing and monitoring of generative AI applications. Figure 1 depicts the systems functionalities and AWS services. Select AWS Generative AI Best Practices Framework for assessment. Choose Create assessment.

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Architect a mature generative AI foundation on AWS

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Scaling and load balancing The gateway can handle load balancing across different servers, model instances, or AWS Regions so that applications remain responsive. The AWS Solutions Library offers solution guidance to set up a multi-provider generative AI gateway. Leave us a comment and we will be glad to collaborate.

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How Anomalo solves unstructured data quality issues to deliver trusted assets for AI with AWS

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Transforming unstructured files, maintaining compliance, and mitigating data quality issues all become critical hurdles when an organization moves from AI pilots to production deployments. This helps your data teams deliver high-value AI applications faster and with less risk.

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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

It allows data scientists and machine learning engineers to interact with their data and models and to visualize and share their work with others with just a few clicks. SageMaker Canvas has also integrated with Data Wrangler , which helps with creating data flows and preparing and analyzing your data.

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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

It seems straightforward at first for batch data, but the engineering gets even more complicated when you need to go from batch data to incorporating real-time and streaming data sources, and from batch inference to real-time serving. You can also find Tecton at AWS re:Invent.

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Data integration

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Data integration plays a key role in achieving this by incorporating data cleansing techniques, ensuring that the information used is accurate and consistent. Reduction of data silos Breaking down data silos is essential for enhancing collaboration across different departments within an organization.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

SageMaker Unified Studio combines various AWS services, including Amazon Bedrock , Amazon SageMaker , Amazon Redshift , Amazon Glue , Amazon Athena , and Amazon Managed Workflows for Apache Airflow (MWAA) , into a comprehensive data and AI development platform. Navigate to the AWS Secrets Manager console and find the secret -api-keys.

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