20th Century Fox is working on an AI to predict upcoming movie performances. Read more

In what could be next big step in widening range of implementation of Artificial Intelligence (AI), researchers at film studio 20th Century Fox are said to be working on a deep learning system that would be able to predict performance of a movie in market by analysing its trailer. 

new AI would be able to link visual elements of a trailer (such as faces, landscapes, lighting and colours) and performance of a film for certain demographics. 

research behind invation found that a trailer with more number of people talking and warm colours might appeal to a different group than ones with dull colours and more visual dependence.  

method alrey seems to be working in real world when used on existing movies. company is also said to be testing new method on its upcoming movies. 

" trained model t only makes accurate attendance and audience prediction for existing movies, but also successfully profiles new movies six to eight months prior to ir release." paper said.

However, study and its applications come with a handful of setbacks. For instance, AI does t capture temporal information of screen which involves representing and reasoning spatial-temporal kwledge in mind. applied goal—on computing side—involves developing high-level control systems of robots for navigating and understanding time and . ditionally, it does t distinguish between video and text description in order to achieve a complete sense of movie.

A Collaborative Filtering Model (CFM) that was developed for research was used to predict customer behaviour six to eight months after trailer was released.

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This new project could be useful for entertainment companies which could make a target-oriented preview of movie for its audience that would attract a larger numbers for its movie. This would be good news for all entertainment companies in of streaming where movies are easily available on platforms such as Netflix or Amazon Prime. 

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"Movie-streaming differs from moviegoing. It is cheaper and reversible (one can stop movie), and re is less risk involved. Casual streamers are t penalized for making mistakes when drawing from a broer catalog as casual moviegoers are if y do t like movie" paper suggested.