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Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

This post describes how Agmatix uses Amazon Bedrock and AWS fully featured services to enhance the research process and development of higher-yielding seeds and sustainable molecules for global agriculture. AWS generative AI services provide a solution In addition to other AWS services, Agmatix uses Amazon Bedrock to solve these challenges.

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

AWS Machine Learning Blog

Generative artificial intelligence (AI) can be vital for marketing because it enables the creation of personalized content and optimizes ad targeting with predictive analytics. Use case overview Vidmob aims to revolutionize its analytics landscape with generative AI.

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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. This may be useful for later chat assistant analytics. us-east-1 or bash deploy.sh

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

AWS Machine Learning Blog

ML Engineer at Tiger Analytics. 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. This post is co-written with Jayadeep Pabbisetty, Sr.

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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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Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

AWS Machine Learning Blog

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud. at a minimum).

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. OpenSearch Dashboard also enables users to search and run analytics with this dataset.

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