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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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Configure fine-grained access to Amazon Bedrock models using Amazon SageMaker Unified Studio

AWS Machine Learning Blog

SageMaker Unified Studio brings together the functionality and tools from existing AWS analytics and AI/ML services, including Amazon EMR , AWS Glue , Amazon Athena , Amazon Redshift , Amazon Bedrock, and Amazon SageMaker AI. To learn more, refer to Amazon Bedrock in SageMaker Unified Studio.

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Unlock cost savings with the new scale down to zero feature in SageMaker Inference

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Today at AWS re:Invent 2024, we are excited to announce a new feature for Amazon SageMaker inference endpoints: the ability to scale SageMaker inference endpoints to zero instances. This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

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Best practices and lessons for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock

AWS Machine Learning Blog

These tasks include summarization, classification, information retrieval, open-book Q&A, and custom language generation such as SQL. Sovik Kumar Nath is an AI/ML and Generative AI Senior Solutions Architect with AWS. Outside of work, she enjoys reading books and watching tennis games. Sonnet across various tasks.

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Advanced fine-tuning methods on Amazon SageMaker AI

AWS Machine Learning Blog

This process typically involves training from scratch on diverse datasets, often consisting of hundreds of billions of tokens drawn from books, articles, code repositories, webpages, and other public sources. Fine-tuning methods on AWS Fine-tuning transforms a pre-trained model into one that excels at specific tasks or domains.

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Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

AWS Machine Learning Blog

Prerequisites To use this feature, make sure that you have satisfied the following requirements: An active AWS account. model customization is available in the US West (Oregon) AWS Region. Sovik Kumar Nath is an AI/ML and Generative AI senior solution architect with AWS. Applied Scientist in AWS Agentic AI. Meta Llama 3.2

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