» Greater opportunity for dormant content to find new life – and new money – through repurposing «
be accomplished by armies of humans working 24/7. Moments Lab has been a leader in developing sophisticated image analysis for content owners to monetise their libraries. The company’s AI-powered toolkit mines archives and is able to provide rich metadata about the content and subject matter. One upside to the overwhelming proliferation of content platforms is the greater opportunity for dormant content to find new life – and new money – through content licensing, repurposing programmes for different formats or using existing content to build new shows. Big media companies can have many thousands of hours of content, built up over decades, waiting in storage. “Fresh content is expensive,” says Philippe Petitpont, Moments Lab co- founder and CEO. “There’s now a big interest from companies saying: ‘I’m sitting on a goldmine of content. How can I transform this into revenue?’” Moments Lab has been working with the French media multinational Banijay Entertainment to analyse its content library and get it back out into the world. “They are particularly interested in doing this because they already have the rights,” explains Petitpont. “Before, it was too expensive to produce or repurpose these shows because there was a lot of manual logging and manual editing involved. But if AI can do this for around $20 per clip, then it makes sense.” Another big customer in the US is using Moments Lab not just for repurposing content for social media clips, but for creating an entire FAST channel. “The viewership of a FAST channel is very small, very limited. So again, you don't want to spend time doing the programming and scheduling. You need to scale
than object focused. “In the world of MAM, there are many important, very rigid things you can do with that finished asset, but you don’t want to apply those rules and that rigour to 200 clips sitting in a project you might end up purging 85% of.” In the framework of a production asset management system, files are grouped according to the content goals at hand – ie the project. The benefit is to make it as frictionless as possible for editors to focus only on the files they need in the most efficient workflow to get the completed project delivered. This intense focus on process has the potential to reveal new and better ways of working, rather than reaching for a tech fix to something that isn’t really a tech problem. Barrilleaux points to the tendency to respond to filling storage by buying more storage; or getting hold of an asset problem by buying an asset manager; or solving a remote access problem by buying a remote access tool, without taking into account how the whole workflow is operating. “When you zoom out, you start to see why some facilities have crazy Frankenstein workflows of things that are just bolted together. They would have made decisions to buy individual things that all made sense at the time, but now mean they have all these different things to manage and try to piece together.” Automated assets, automated revenue Machine learning is still in its infancy, but the technology is built on principles of pattern recognition, which makes it especially useful for finding things. Human goal setting and value judgement is not going to be replaced when it comes to asset strategy, but AI can execute processes instantly and at a huge scale that could only
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