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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

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One effective way to improve context relevance is through metadata filtering, which allows you to refine search results by pre-filtering the vector store based on custom metadata attributes. By combining the capabilities of LLM function calling and Pydantic data models, you can dynamically extract metadata from user queries.

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Dynamic metadata filtering for Amazon Bedrock Knowledge Bases with LangChain

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Amazon Bedrock Knowledge Bases has a metadata filtering capability that allows you to refine search results based on specific attributes of the documents, improving retrieval accuracy and the relevance of responses. These metadata filters can be used in combination with the typical semantic (or hybrid) similarity search.

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AWS Glue for Handling Metadata

Analytics Vidhya

The post AWS Glue for Handling Metadata appeared first on Analytics Vidhya. The managed service offers a simple and cost-effective method of categorizing and managing big data in an enterprise. It provides organizations with […].

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Enrich your AWS Glue Data Catalog with generative AI metadata using Amazon Bedrock

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Metadata can play a very important role in using data assets to make data driven decisions. Generating metadata for your data assets is often a time-consuming and manual task. This post shows you how to enrich your AWS Glue Data Catalog with dynamic metadata using foundation models (FMs) on Amazon Bedrock and your data documentation.

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How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines

AWS Machine Learning Blog

With a growing library of long-form video content, DPG Media recognizes the importance of efficiently managing and enhancing video metadata such as actor information, genre, summary of episodes, the mood of the video, and more. Video data analysis with AI wasn’t required for generating detailed, accurate, and high-quality metadata.

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LAION AI Unveils LAION-DISCO-12M: Enabling Machine Learning Research in Foundation Models with 12 Million YouTube Audio Links and Metadata

Marktechpost

Introduction to LAION-DISCO-12M To address this gap, LAION AI has released LAION-DISCO-12M—a collection of 12 million links to publicly available YouTube samples, paired with metadata designed to support foundational machine learning research in audio and music.

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Using the metadata service to identify disks in your VSI with IBM Cloud VPC

IBM Journey to AI blog

If we log in to the VSI, we can see the volume disks: [root@test-metadata ~]# ls -la /dev/disk/by-id total 0 drwxr-xr-x. vdb If we want to find the data volume named test-metadata-volume , we see that it is the vdd disk. Recently, IBM Cloud VPC introduced the metadata service. 2 root root 200 Apr 7 12:58. drwxr-xr-x.

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