NOVEMBER 20, 2024
The relevance of this context directly impacts the model’s ability to generate accurate and contextually appropriate responses. 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.
NOVEMBER 15, 2024
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. First, we explore the option of in-context learning, where the LLM generates the requested metadata without documentation.
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MARCH 4, 2025
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.
AWS Machine Learning Blog
OCTOBER 16, 2024
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. For some content, additional screening is performed to generate subtitles and captions.
MARCH 4, 2025
In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.
MARCH 7, 2025
At the forefront of using generative AI in the insurance industry, Verisks generative AI-powered solutions, like Mozart, remain rooted in ethical and responsible AI use. Security and governance Generative AI is very new technology and brings with it new challenges related to security and compliance.
JANUARY 24, 2025
A common use case with generative AI that we usually see customers evaluate for a production use case is a generative AI-powered assistant. If there are security risks that cant be clearly identified, then they cant be addressed, and that can halt the production deployment of the generative AI application.
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