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Intelligent document processing at scale with generative AI and Amazon Bedrock Data Automation

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Generative AI unlocks these possibilities without costly data annotation or model training, enabling more comprehensive intelligent document processing (IDP). Finally, organizations might operate in AWS Regions where Amazon Bedrock Data Automation is not available (available in us-west-2 and us-east-1 as of June 2025).

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate , and Amazon OpenSearch Service. Along the way, it also simplified operations as Octus is an AWS shop more generally.

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Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Service Managed Cluster as vector store

AWS Machine Learning Blog

Complete knowledge base creation and ingest data – Initiate a sync operation in the Amazon Bedrock console to process S3 documents, generate embeddings, and store them in your OpenSearch Service index. Create an IAM admin user The administrative user serves as the principal account for managing the OpenSearch Service configuration.

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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning Blog

Prerequisites To try out this solution using SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. of persons present’ for the sustainability committee meeting held on 5th April, 2012?

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Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock

AWS Machine Learning Blog

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage any infrastructure. Our dataset includes Q&A pairs with reference documents regarding AWS services.

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Large language model inference over confidential data using AWS Nitro Enclaves

AWS Machine Learning Blog

In this post, we discuss how Leidos worked with AWS to develop an approach to privacy-preserving large language model (LLM) inference using AWS Nitro Enclaves. LLMs are designed to understand and generate human-like language, and are used in many industries, including government, healthcare, financial, and intellectual property.

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Build high-performance ML models using PyTorch 2.0 on AWS – Part 1

AWS Machine Learning Blog

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. release, AWS customers can now do same things as they could with PyTorch 1.x 24xlarge with AWS PyTorch 2.0

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