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

As generative artificial intelligence (AI) applications become more prevalent, maintaining responsible AI principles becomes essential. Without proper safeguards, large language models (LLMs) can potentially generate harmful, biased, or inappropriate content, posing risks to individuals and organizations. Applying guardrails helps mitigate these risks by enforcing policies and guidelines that align with ethical principles and legal requirements.…

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As generative artificial intelligence (AI) applications become more prevalent, maintaining responsible AI principles becomes essential. Without proper safeguards, large language models (LLMs) can potentially generate harmful, biased, or inappropriate content, posing risks to individuals and organizations. Applying guardrails helps mitigate these risks by enforcing policies and guidelines that align with ethical principles and legal requirements. […]

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Amazon

Introducing resource control policies (RCPs), a new type of authorization policy in AWS Organizations

New Resource Control Policies let you centrally restrict AWS service access across accounts, bolstering security with preventative controls that supersede permissive policies – even for external users. See how these powerful governance tools complement Service Control Policies and integrate with AWS services. Source

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New Resource Control Policies let you centrally restrict AWS service access across accounts, bolstering security with preventative controls that supersede permissive policies – even for external users. See how these powerful governance tools complement Service Control Policies and integrate with AWS services.

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Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. In this post, we discuss a new feature that supports the integration of model cards with…

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You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks. In this post, we discuss a new feature that supports the integration of model cards with the model registry. We discuss the solution architecture and best practices for managing model cards with a registered model version, and walk through how to set up, operationalize, and govern your models using the integration in the model registry.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

In this post, you will learn how to extract key objects from image queries using Amazon Rekognition and build a reverse image search engine using Amazon Titan Multimodal Embeddings from Amazon Bedrock in combination with Amazon OpenSearch Serverless Service. Source

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In this post, you will learn how to extract key objects from image queries using Amazon Rekognition and build a reverse image search engine using Amazon Titan Multimodal Embeddings from Amazon Bedrock in combination with Amazon OpenSearch Serverless Service.

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