Remove Auto-complete Remove IDP Remove Large Language Models
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Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization

AWS Machine Learning Blog

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific terms or words. This post focuses on the Cost Optimization pillar of the IDP solution.

IDP 112
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Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS Machine Learning Blog

However, they’re unable to gain insights such as using the information locked in the documents for large language models (LLMs) or search until they extract the text, forms, tables, and other structured data. When the script ends, a completion status along with the time taken will be returned to the SageMaker studio console.

IDP 121
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Implement secure API access to your Amazon Q Business applications with IAM federation user access management

AWS Machine Learning Blog

Amazon Q Business is a conversational assistant powered by generative AI that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access. This step is performed by the IAM or security administrator in your organization.

IDP 100
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Discover insights from your Amazon Aurora PostgreSQL database using the Amazon Q Business connector

AWS Machine Learning Blog

Next, you need to index this data to make it available for a Retrieval Augmented Generation (RAG) approach, where relevant passages are delivered with high accuracy to a large language model (LLM). You also need to hire and staff a large team to build, maintain, and manage such a system. Choose Create application.