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

AWS Machine Learning - AI

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. An Amazon OpenSearch Serverless collection.

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

AWS Machine Learning - AI

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. You can use AWS services such as Application Load Balancer to implement this approach.

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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions. sync) pattern, which automatically waits for the completion of asynchronous jobs.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Mozart, the leading platform for creating and updating insurance forms, enables customers to organize, author, and file forms seamlessly, while its companion uses generative AI to compare policy documents and provide summaries of changes in minutes, cutting the change adoption time from days or weeks to minutes.

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Boost productivity by using AI in cloud operational health management

AWS Machine Learning - AI

It uses Amazon Bedrock , AWS Health , AWS Step Functions , and other AWS services. Some examples of AWS-sourced operational events include: AWS Health events — Notifications related to AWS service availability, operational issues, or scheduled maintenance that might affect your AWS resources.

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Responsible AI in action: How Data Reply red teaming supports generative AI safety on AWS

AWS Machine Learning - AI

At Data Reply and AWS, we are committed to helping organizations embrace the transformative opportunities generative AI presents, while fostering the safe, responsible, and trustworthy development of AI systems. Post-authentication, users access the UI Layer, a gateway to the Red Teaming Playground built on AWS Amplify and React.

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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning - AI

Seamless integration of latest foundation models (FMs), Prompts, Agents, Knowledge Bases, Guardrails, and other AWS services. Reduced time and effort in testing and deploying AI workflows with SDK APIs and serverless infrastructure. They have no way to ensure that responses comply with company policies and regulatory requirements.