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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning Blog

In this post, we show how to create a multimodal chat assistant on Amazon Web Services (AWS) using Amazon Bedrock models, where users can submit images and questions, and text responses will be sourced from a closed set of proprietary documents. For this post, we recommend activating these models in the us-east-1 or us-west-2 AWS Region.

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How Vidmob is using generative AI to transform its creative data landscape

AWS Machine Learning Blog

In this post, we illustrate how Vidmob , a creative data company, worked with the AWS Generative AI Innovation Center (GenAIIC) team to uncover meaningful insights at scale within creative data using Amazon Bedrock. The chatbot built by AWS GenAIIC would take in this tag data and retrieve insights.

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

In this post, we discuss how the AWS AI/ML team collaborated with the Merck Human Health IT MLOps team to build a solution that uses an automated workflow for ML model approval and promotion with human intervention in the middle. A model developer typically starts to work in an individual ML development environment within Amazon SageMaker.

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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

Expand to generative AI use cases with your existing AWS and Tecton architecture After you’ve developed ML features using the Tecton and AWS architecture, you can extend your ML work to generative AI use cases. You can also find Tecton at AWS re:Invent. This process is shown in the following diagram.

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Automating product description generation with Amazon Bedrock

AWS Machine Learning Blog

This solution is available in the AWS Solutions Library. The system architecture comprises several core components: UI portal – This is the user interface (UI) designed for vendors to upload product images. AWS Lambda – AWS Lambda provides serverless compute for processing.

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Moderate your Amazon IVS live stream using Amazon Rekognition

AWS Machine Learning Blog

You can deploy this solution to your AWS account using the AWS Cloud Development Kit (AWS CDK) package available in our GitHub repo. Using the AWS Management Console , you can create a recording configuration and link it to an Amazon IVS channel. In this section, we briefly introduce the system architecture.

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Rad AI reduces real-time inference latency by 50% using Amazon SageMaker

AWS Machine Learning Blog

Let’s transition to exploring solutions and architectural strategies. Approaches to researcher productivity To translate our strategic planning into action, we developed approaches focused on refining our processes and system architectures. He has a passion for continuous innovation and using data to drive business outcomes.

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