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

AWS Machine Learning

The logic flow for generating an answer to a text-image response pair routes as follows: Steps 1 and 2 – To start, a user query and corresponding image are routed through an Amazon API Gateway connection to an AWS Lambda function, which serves as the processing and orchestrating compute for the overall process. us-east-1 or bash deploy.sh

Chatbots 133
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Transitioning from Amazon Rekognition people pathing: Exploring other alternatives

AWS Machine Learning

Example code The following code example is a Python script that can be used as an AWS Lambda function or as part of your processing pipeline. Here’s a high-level breakdown of how the Python script is executed: Load the YOLOv9 model – This model is used for detecting objects in each frame. cvtColor(frame, cv2.COLOR_RGB2BGR)

Scripts 122
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Bring legacy machine learning code into Amazon SageMaker using AWS Step Functions

AWS Machine Learning

The best practice for migration is to refactor these legacy codes using the Amazon SageMaker API or the SageMaker Python SDK. SageMaker runs the legacy script inside a processing container. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language.

Scripts 145
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Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock

AWS Machine Learning

Traditionally, earnings call scripts have followed similar templates, making it a repeatable task to generate them from scratch each time. On the other hand, generative artificial intelligence (AI) models can learn these templates and produce coherent scripts when fed with quarterly financial data.

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Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation

AWS Machine Learning

At Deutsche Bahn, a dedicated AI platform team manages and operates the SageMaker Studio platform, and multiple data analytics teams within the organization use the platform to develop, train, and run various analytics and ML activities.

APIs 136
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Derive meaningful and actionable operational insights from AWS Using Amazon Q Business

AWS Machine Learning

In this post, we’re using the APIs for AWS Support , AWS Trusted Advisor , and AWS Health to programmatically access the support datasets and use the Amazon Q Business native Amazon Simple Storage Service (Amazon S3) connector to index support data and provide a prebuilt chatbot web experience. Synchronize the data source to index the data.

Scripts 134
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Deploy a Slack gateway for Amazon Bedrock

AWS Machine Learning

The Slack application sends the event to Amazon API Gateway , which is used in the event subscription. API Gateway forwards the event to an AWS Lambda function. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

APIs 141