Remove Information Remove Metadata Remove ML
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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. Don’t Forget to join our 55k+ ML SubReddit.

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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

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This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. The data mesh architecture aims to increase the return on investments in data teams, processes, and technology, ultimately driving business value through innovative analytics and ML projects across the enterprise.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

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Amazon Q Business , a new generative AI-powered assistant, can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in an enterprises systems. Furthermore, it might contain sensitive data or personally identifiable information (PII) requiring redaction.

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Process formulas and charts with Anthropic’s Claude on Amazon Bedrock

AWS Machine Learning Blog

Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data. Generate metadata for the page.

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Unstructured data management and governance using AWS AI/ML and analytics services

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Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

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