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AWS Glue for Handling Metadata

Analytics Vidhya

The managed service offers a simple and cost-effective method of categorizing and managing big data in an enterprise. The post AWS Glue for Handling Metadata appeared first on Analytics Vidhya. Introduction AWS Glue helps Data Engineers to prepare data for other data consumers through the Extract, Transform & Load (ETL) Process.

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Generate user-personalized communication with Amazon Personalize and Amazon Bedrock

Flipboard

The user and item datasets are not required for Amazon Personalize to generate recommendations, but providing good item and user metadata provides the best results in your trained models. You can request metadata columns only if this feature has been enabled when the recommender was created.

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Rightsify’s GCX: Your Go-To Source for High-Quality, Ethically Sourced, Copyright-Cleared AI Music Training Datasets with Rich Metadata

Marktechpost

These datasets encompass millions of hours of music, over 10 million recordings and compositions accompanied by comprehensive metadata, including key, tempo, instrumentation, keywords, moods, energies, chords, and more, facilitating training and commercial usage. GCX provides datasets with over 4.4

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Autonomous Agents with AgentOps: Observability, Traceability, and Beyond for your AI Application

Unite.AI

The authors categorize traceable artifacts, propose key features for observability platforms, and address challenges like decision complexity and regulatory compliance. These metrics are visualized across dimensions such as user sessions, prompts, and workflows, enabling real-time interventions.

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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning Blog

This capability enables organizations to create custom inference profiles for Bedrock base foundation models, adding metadata specific to tenants, thereby streamlining resource allocation and cost monitoring across varied AI applications. This tagging structure categorizes costs and allows assessment of usage against budgets.

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

AWS Machine Learning Blog

Enterprises may want to add custom metadata like document types (W-2 forms or paystubs), various entity types such as names, organization, and address, in addition to the standard metadata like file type, date created, or size to extend the intelligent search while ingesting the documents.

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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Journey to AI blog

The Ministry of Justice in Baden-Württemberg recommended using AI with natural language understanding (NLU) and other capabilities to help categorize each case into the different case groups they were handling. The courts needed a transparent, traceable system that protected data. Explainability will play a key role.