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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. This streamlines the ML workflows, enables better visibility and governance, and accelerates the adoption of ML models across the organization.

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Amazon Bedrock launches Session Management APIs for generative AI applications (Preview)

AWS Machine Learning

Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Building generative AI applications requires more than model API calls.

APIs 121
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic.

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. This tool not only supports responsible AI practices, but also fosters trust and reliability in the use of AI-generated content.

APIs 112
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Using natural language in Amazon Q Business: From searching and creating ServiceNow incidents and knowledge articles to generating insights

AWS Machine Learning

Use natural language in your Amazon Q web experience chat to perform read and write actions in ServiceNow such as querying and creating incidents and KB articles in a secure and governed fashion. This involves creating an OAuth API endpoint in ServiceNow and using the web experience URL from Amazon Q Business as the callback URL.

APIs 97
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Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

AWS Machine Learning

The new ApplyGuardrail API enables you to assess any text using your preconfigured guardrails in Amazon Bedrock, without invoking the FMs. In this post, we demonstrate how to use the ApplyGuardrail API with long-context inputs and streaming outputs. For example, you can now use the API with models hosted on Amazon SageMaker.

APIs 131
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Generative AI operating models in enterprise organizations with Amazon Bedrock

AWS Machine Learning

Large organizations often have many business units with multiple lines of business (LOBs), with a central governing entity, and typically use AWS Organizations with an Amazon Web Services (AWS) multi-account strategy. Failure to scale the team can negate the governance benefits of a centralized approach.