Auto-adjusting display time of slides based on content intelligence

A system comprising:

• one or more hardware processors;
• and
• a memory storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
• training one or more machine learning models to determine weights applicable to different content types;
• accessing media comprising a plurality of media items, a media item of the plurality of media items comprising a first content type;
• based on the first content type, performing machine analysis associated with the first content type;
• applying a weight determined by the one or more machine learning models to a result of the machine analysis to determine a first display time for the first content type of the media item;
• determining a second display time for a second content type that is video, the determining the second display time comprising:
• for each frame of the video, identifying a motion and activity filter value;
• based on the motion and activity filter value for each frame, determining an average motion and activity filter value for the video;
• and
• deriving the second display time by applying a duration of the video to the average motion and activity filter value;
• deriving a total display time for the media item based on the first display time and the second display time;
• causing a machine action based on the total display time for the media item;
• receiving feedback based on the machine action;
• and
• retraining at least one of the one or more machine learning models using the feedback.

A computer-storage medium comprising instructions which, when executed by one or more hardware processors of a machine, cause the machine to perform operations comprising:

• training one or more machine learning models to determine weights applicable to different content types;
• accessing media comprising a plurality of media items, a media item of the plurality of media items comprising a first content type;
• based on the first content type, performing machine analysis associated with the first content type;
• applying a weight determined by the one or more machine learning models to a result of the machine analysis to determine a first display time for the first content type of the media item;
• determining a second display time for a second content type that is video, the determining the second display time comprising:
• for each frame of the video, identifying a motion and activity filter value;
• based on the motion and activity filter value for each frame, determining an average motion and activity filter value for the video;
• and
• deriving the second display time by applying a duration of the video to the average motion and activity filter value;
• deriving a total display time for the media item based on the first display time and the second display time;
• causing a machine action based on the total display time for the media item;
• receiving feedback based on the machine action;
• and
• retraining at least one of the one or more machine learning models using the feedback.