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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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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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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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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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Reduce call hold time and improve customer experience with self-service virtual agents using Amazon Connect and Amazon Lex

AWS Machine Learning Blog

Solution overview To tackle these challenges, the KYTC team reviewed several contact center solutions and collaborated with the AWS ProServe team to implement a cloud-based contact center and a virtual agent named Max. Amazon Lex and the AWS QnABot Amazon Lex is an AWS service for creating conversational interfaces.

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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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