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

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 110
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Secure a generative AI assistant with OWASP Top 10 mitigation

AWS Machine Learning

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 110
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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts 129
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Best practices for TensorFlow 1.x acceleration training on Amazon SageMaker

AWS Machine Learning

Because many data scientists may lack experience in the acceleration training process, in this post we show you the factors that matter for fast deep learning model training and the best practices of acceleration training for TensorFlow 1.x We discuss best practices in the following areas: Accelerate training on a single instance.

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Training large language models on Amazon SageMaker: Best practices

AWS Machine Learning

In this post, we dive into tips and best practices for successful LLM training on Amazon SageMaker Training. The post covers all the phases of an LLM training workload and describes associated infrastructure features and best practices. Some of the best practices in this post refer specifically to ml.p4d.24xlarge

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Best practices to build generative AI applications on AWS

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon via a single API. This is because such tasks require organization-specific data and workflows that typically need custom programming.

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Best practices for load testing Amazon SageMaker real-time inference endpoints

AWS Machine Learning

This post describes the best practices for load testing a SageMaker endpoint to find the right configuration for the number of instances and size. Note that the model container also includes any custom inference code or scripts that you have passed for inference.