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Real AI success: Search across 20M+ media assets & find what matters in seconds

Micro Focus Contributor
Micro Focus Contributor
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The next program you watch may just be the brainchild of Artificial intelligence (AI). The media industry, with its huge treasure trove of media assets, is aggressively turning to AI for its competitive advantage.

RTVE.jpgThe R&D arm of BBC says “we’re already exploring how AI and machine learning technologies could transform the future of media production” in a recent blog titled, “AI and the Archive - the making of Made by Machine.“

RTVE, the biggest broadcaster in Spain with six national TV channels, two international TV channels, and five radio channels, has a 50+ year old archive of video, image, audio and text data, which is growing by over one million assets yearly.  In addition to the massive data volume and broad range of date formats, these assets are in silos spread across disparate systems, with different databases and programming languages.

In the world of broadcast news where every second counts, RTVE cannot afford days in locating the right assets for its production.  Journalists need to have the image or footage of say, the winner of a major sporting event, at their fingertips without missing a beat. 

With a recent AI initiative to centralize data asset management and enable cognitive search and retrieval, RTVE has successfully reduced their time in finding contextually relevant information, regardless of format, from days to seconds by implementing a new system powered by Micro Focus IDOL.

Going forward, RTVE plans to further its success by expanding its application to leverage other IDOL’s capabilities such as key concept extraction, clustering etc. to gain deeper insight into its data assets for breakthrough advances in media production.

Read this RTVE case study to find out how they have completely revolutionized the way television is produced using Micro Focus IDOL.

About the Author
Joe has over 13 years of experience in technology marketing and is currently focused on the analytics solution portfolio. Prior to this role, he was responsible for product marketing of the enterprise application data management solution.
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