Abstract: Systems and methods for providing machine-learning enabled user-specific evaluations are disclosed. Implementations include obtaining a first set of evaluation data from a user interface, obtaining a first set of target-descriptive data including target-specific characteristics objectively describing the evaluation targets, and training, with a machine-learning algorithm, a user-specific evaluation profile indicating evaluation patterns relative to the first set of evaluation data and the first set of target-specific characteristics. Implementations include applying the user-specific evaluation profile to a second set of target-descriptive data to predict a user-specific evaluation.

Abstract: Systems and methods described herein are directed to enhancing a virtual reality (VR) or augmented reality (AR) experience by using one or more unmanned vehicles to generate effects around a user of a headmounted display (HMD). The generated effects may be synchronized with VR/AR content presented to the user of the HMD. Particular systems and methods described herein are directed to enhancing a VR/AR experience by using one or more unmanned aerial vehicles (UAV) to generate air flow effects around a user of a HMD. The air flow effects generated by UAV may simulate a physical and/or olfactory sensation corresponding to a VR/AR environment presented to the user using the HMD.

Abstract: Implementations of the disclosure describe AI systems that offer an improvisational story telling AI agent that may interact collaboratively with a user. In one implementation, a story telling device may be implemented using i) a natural language understanding (NLU) component to process human language input (e.g., digitized speech or text input); ii) a natural language processing (NLP) component to parse the human language input into a story segment or sequence; iii) a component for storing/recording the story as it is created by collaboration; iv) a component for generating AI-suggested story elements; and v) a natural language generation (NLG) component to transform the AI-generated story segment into natural language that may be presented to the user.

Abstract: Systems and methods for providing machine-learning enabled user-specific evaluations are disclosed. Implementations include obtaining a first set of evaluation data from a user interface, obtaining a first set of target-descriptive data including target-specific characteristics objectively describing the evaluation targets, and training, with a machine-learning algorithm, a user-specific evaluation profile indicating evaluation patterns relative to the first set of evaluation data and the first set of target-specific characteristics. Implementations include applying the user-specific evaluation profile to a second set of target-descriptive data to predict a user-specific evaluation.

Abstract: There is provided a system comprising a non-transitory memory and a hardware processor configured to determine elements of a performance in a video, identify one or more people to feature in the video based on the elements of the performance in the video, receive a user input selecting a person from the one or more people to feature in the video, retrieve performance data for featuring the selected person in the video based on actions performed by the actor in the video, create a personalized video by featuring the selected person in the video using the performance data, and display the personalized video on a user device.

Abstract: Systems and methods described herein are directed to enhancing a virtual reality (VR) or augmented reality (AR) experience by using one or more unmanned vehicles to generate effects around a user of a headmounted display (HMD). The generated effects may be synchronized with VR/AR content presented to the user of the HMD. Particular systems and methods described herein are directed to enhancing a VR/AR experience by using one or more unmanned aerial vehicles (UAV) to generate air flow effects around a user of a HMD. The air flow effects generated by UAV may simulate a physical and/or olfactory sensation corresponding to a VR/AR environment presented to the user using the HMD.

Abstract: There is provided a system comprising a non-transitory memory and a hardware processor configured to determine elements of a performance in a video, identify one or more people to feature in the video based on the elements of the performance in the video, receive a user input selecting a person from the one or more people to feature in the video, retrieve performance data for featuring the selected person in the video based on actions performed by the actor in the video, create a personalized video by featuring the selected person in the video using the performance data, and display the personalized video on a user device.