Abstract: A stream of media eligible to be automatically shared is received. Using a machine learning model trained using engagement information regarding one or more previously shared media, a media included in the stream of media is analyzed to output an engagement analysis. Based on the engagement analysis, a determination is made on whether the media included in the stream of media is desirable to be automatically shared. The media is automatically shared in an event it is determined that the media included in the stream of media is desirable to be automatically shared.

Abstract: A media and a context information associated with the media are received. A first machine learning model and a second machine learning model are trained using different machine learning training data sets. Using the first machine learning model, the media is analyzed to determine a classification result. Using the second machine learning model, the classification result and the context information are analyzed to determine whether the media is likely not desirable to share. In an event the media is not identified as not desirable to share, the media is automatically shared.

Abstract: At a device of a first user, a digital media associated with a second user is received. It is detected that the device has displayed the digital media. It is determined whether the device has displayed the digital media for at least a threshold amount of time. In an event the device has displayed the digital media for at least the threshold amount of time, an indication is provided to the first user and a notification is sent. The notification is utilized to provide to the second user, information associated with an interaction by the first user with the digital media.

Abstract: A plurality of digital media to be sequentially displayed is received. An input gesture is received. A magnitude value associated with the input gesture is determined. In response to the input gesture, at least a portion of the plurality of digital media corresponding to the determined magnitude value is advanced. Based on a property of a first digital media included in the plurality of digital media, a first amount of magnitude value that corresponds to advancing the first digital media included in the plurality of digital media is determined to be larger than a different second amount of magnitude value that corresponds to advancing a second digital media included in the plurality of digital media.

Abstract: Artificial intelligence is utilized to automatically share a digital media. The digital media is detected. The media is analyzed using machine learning to identify whether the digital media is likely not desirable to share. In an event the digital media is not identified as not desirable to share, the digital media is automatically shared.

Abstract: Provided are systems and methods for providing expedited production of compact multi-angle video. Methods include capturing video content of a moving video subject and a background portion that is proximate the moving video subject as digital video data and generating a motion video data file from multiple sequentially numbered transparent background still image data files that correspond to the digital video data.

Abstract: Provided are an associative memory operator system and methods for predictive marketing analysis using a computer implemented social network. A system includes multiple associative memory cells corresponding to multiple computer implemented social network users. A respective one of the associative memory cells corresponds to a user in the computer implemented social network and includes a sink memory of associations corresponding to which ones of the computer implemented social network users have been influenced by the user and a source memory of associations corresponding to which other ones of the computer implemented social network users have influenced the user.