Abstract: A method for training a plurality of task neural networks such that the trained task neural networks are compatible with each other is described. The method includes receiving, for each of the plurality of task neural networks, a respective training data set; forming an auxiliary loss function for the plurality of task neural networks, in which the auxiliary loss function ensures that the trained task neural networks would be compatible with each other; and training the plurality of task neural networks to optimize a combined loss function. The combined loss function is a combination of respective task loss functions for the respective machine learning tasks and an auxiliary loss function that encourages compatibility between the task neural networks.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically extracting and creating an animated Graphics Interchange Format (GIF) file from a media file. The disclosed systems and methods identify a number of GIF candidates from a video file, and based on analysis of each candidate's attributes, features and/or qualities, at least one GIF candidate is automatically selected for rendering.

Abstract: A computer-implemented method includes receiving an input data item including a plurality of data elements, and generating a predicted structured output for the input data item. Generating the predicted structured output includes iteratively performing the following operations: receiving a current structured output that assigns, to each of the data elements, a respective current value for each of the one or more categories; processing the input data item and the current output using a value neural network, in which the value neural network has been trained to process the input data item and the current output to generate a value score that is an estimate of how accurately the current output predicts the likelihoods that the elements belong to the one or more categories; and updating the current structured output by adjusting the current values in the current output to increase the value score generated by the value neural network.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically extracting and creating an animated Graphics Interchange Format (GIF) file from a media file. The disclosed systems and methods identify a number of GIF candidates from a video file, and based on analysis of each candidate's attributes, features and/or qualities, at least one GIF candidate is automatically selected for rendering.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically extracting and creating an animated Graphics Interchange Format (GIF) file from a media file. The disclosed systems and methods identify a number of GIF candidates from a video file, and based on analysis of each candidate's attributes, features and/or qualities, at least one GIF candidate is automatically selected for rendering.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically extracting and creating an animated Graphics Interchange Format (GIF) file from a media file. The disclosed systems and methods identify a number of GIF candidates from a video file, and based on analysis of each candidate's attributes, features and/or qualities, at least one GIF candidate is automatically selected for rendering.