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Hierarchical (and other) Indexes using LlamaIndex for RAG Content Enrichment

Salmon Run

At our weekly This Week in Machine Learning (TWIML) meetings, (our leader and facilitataor) Darin Plutchok pointed out a LinkedIn blog post on Semantic Chunking that has been recently implemented in the LangChain framework.

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Best AI Plugins for WordPress (2023)

Flipboard

WordLift WordLift automates search engine optimization by scanning a website’s content, enriching it with structured data or schema markup, and submitting it to Google. This simple plugin will allow you to provide superior support to your customers by simulating natural conversations with your consumers.

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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

Common stages include data capture, document classification, document text extraction, content enrichment, document review and validation , and data consumption. By clearly defining and separating these stages in your architecture, you create a more resilient system.

IDP 90
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Use custom metadata created by Amazon Comprehend to intelligently process insurance claims using Amazon Kendra

AWS Machine Learning Blog

In this post, we describe a use case for custom content enrichment for insurance providers. Additionally, the complexity of claims processing is also increasing due to the diverse types of insurance documents involved, and custom entities in each of these documents.

Metadata 105
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Build well-architected IDP solutions with a custom lens – Part 3: Reliability

AWS Machine Learning Blog

Although the stages in an IDP workflow may vary and be influenced by use case and business requirements, the stages of data capture, document classification, text extraction, content enrichment, review and validation, and consumption are typically parts of IDP workflow.

IDP 86