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Condé Nast leverages AWS Bedrock for AI-powered multimodal video discovery

Condé Nast has partnered with AWS to develop a new AI-powered system for discovering video content. This solution, built on Amazon Bedrock and Amazon OpenSearch Service, utilizes the TwelveLabs Marengo embedding model to perform semantic searches across video transcripts, visuals, and audio. The new system significantly reduces content discovery time from an average of 250 minutes to under 2 minutes per task, improving operational efficiency for brands like Vogue, GQ, Vanity Fair, and Wired. AI

IMPACT Accelerates content discovery and operational efficiency for media companies by enabling semantic search across video modalities.

RANK_REASON This is a case study of a company using AI tools for a specific business problem, not a release of a new AI model or research.

Read on AWS Machine Learning Blog →

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Condé Nast leverages AWS Bedrock for AI-powered multimodal video discovery

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  1. AWS Machine Learning Blog TIER_1 English(EN) · Mariah Miller ·

    How Condé Nast built multimodal video discovery with Amazon Bedrock

    Condé Nast's editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions. Working with the AWS Generative AI Innovation Center, they built a multimodal video discovery solution on Amazon Bedrock and A…