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How GenAI is boosting video streaming experiences at the consumer and business level

By DigiconAsia Editors | Thursday, April 11, 2024, 5:16 PM Asia/Singapore

How GenAI is boosting video streaming experiences at the consumer and business level

While firms exploit generative AI to auto-generate personalized movie blurbs and previews, consumers are enjoying more accurate recommendations and fewer disruptions

With generative AI (GenAI) making its way into the entertainment industry, the way consumers discover content is undergoing a massive shift.

With so many alternative entertainment channels vying for our attention, entertainment media firms have been trying out and embracing a wave of innovation through new AI tools and partnerships.

For example, global streaming technology and entertainment company Cineverse has developed a conversational GenAI search and discovery tool designed to make deciding what to watch “as entertaining as the entertainment itself.”

The firm’s subscribers chat with a “cinephile” (a portmanteau of the terms “cinema” and “lover”) chatbot called Ava, which analyzes subscribers’ viewing preferences and trends to suggest personalized movie recommendations. GenAI combs through metrics of viewer activities to fine-tune how thumbnails and previews of movies are automatically generated; machine-learning fingerprints of past viewership metadata for improving recommendation accuracy; and even data on the least disruptive cue points to insert advertisements in order not to compromise viewing experiences.

Depending on the key words of the chat, Ava will then use the voluminous contextual data to display links to all the streaming services that feature the recommended film titles. 

In another instance, streaming service provider Quickplay is utilizing next-generation AI for video streaming discovery via its Curator Assistant. By analyzing various data points and historical performance, this bot provides intelligence to promote more seamless content discovery by clients, ultimately enhancing viewer experience.

Additionally, the bot’s content management system features also allow media content curators to create dynamic storefronts with personalized recommendations that change based on the time of day or month, geographical location, content popularity, viewer’s preferences, and movie promotion strategies or targets. Result: better recommendations, traction and view loyalty.

The two case studies above were examples cited in press materials from the Google Cloud Next ’24 event running from 9 – 11 April 2024.

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