Abstract: A system and method for generating trivia questions in artificial intelligence (AI)-driven gameplay. The system and method incorporate a trivia application with a user interface connected to a generative AI model. Upon receiving a trivia topic from the user interface, the system displays and reserves select responses based on expected user interactivity time. The system and method also include automatic input triggers for subsequent response generation, minimizing any latency between displaying responses to the user interface.

Abstract: The technology discloses a system for validation of generative AI model operators using preloaded query context connected to independent AI models in generative AI-driven trivia gameplay. The system includes a user interface connected to a generative AI model that generates trivia responses based on user input. A model superstructure between the user interface, the generative AI model, and independent validation model(s) facilitates the evaluation of the user input or trivia response by the validation model(s). The validation model(s) are provided with a pre-loaded query context to detect adherence to predetermined conditions. A consensus module receives the validation model's output and delivers the user input or trivia response to the generative AI model or user interface, respectively, based on the evaluation.

Abstract: Disclosed herein are systems and methods for synchronizing bucketized animations with AI-driven responses in interactive toys and animatronic objects. The systems include toys equipped with multiple motors enabled to control movement of different segments, where each motor is associated with a corresponding movement path. Input content is received and used to construct prompts that operate as an input in an AI model to generate narrative responses along with metadata defining sequences of movements. The metadata is mapped to bucketized animations that are executed using the motors for specific time periods. The systems and methods enable concurrent/synchronized presentation of AI-generated narratives through speakers and the bucketized animations.

Abstract: Disclosed herein are systems and associated methods for constructing dynamic artificial intelligence (AI)-driven narratives for interactive synthetic characters. The systems and methods include one or more synthetic users, which include characters and/or objects. The figurines are identified by a stage through Near Field Communication (NFC) tags, audio inputs, image inputs, and/or video inputs. Users place the identified characters and/or objects on the stage. The AI model processes the identified characters and/or objects on the stage to dynamically generate personalized and evolving narratives between the identified characters and/or objects on the stage. The generated narratives incorporate dialogue, motorized animations, and/or character interactions.

Abstract: Systems and methods herein are provided for delivering personalized trivia content in an interactive game using tangible game elements and a digital companion application. Players are enabled to select and scan multiple tangible game elements (e.g., via quick-response codes, ArUco markers, tags, or other identifiers), each representing a game parameter value (e.g., a topic or category), through a client-side user interface of the digital application to create different combinations. The user interface is coupled to a backend host that controls communications between the user interface and a database storing cache records including game content for particular combinations. The backend host queries the database to check for available game content for the selected combination (subject to certain constraints, such as game content not already previously presented to a user). If not, the backend host transmits a query to a generative artificial intelligence model trained to generate new game content.

Abstract: A digital model generation platform populates an image repository with digital representations of physical clay-based models by generating one or more candidate images based on a combination of clay model features. The digital model generation platform integrates imaginative product displays where users engage with a program on a touch screen, allowing them to combine both pre-generated and user-requested categories to generate image models of suggested clay-based models. The displayed image, either preconfigured (i.e., in the populated image repository) or AI-generated in real time, guides users by indicating the required elements, such as colors, to recreate the model. Additionally, the mobile application introduces AI image upscaling, categorizing user-provided images (e.g., dinosaurs, superheroes) and generating more detailed upscaled images and 3D models based on the chosen category. The application outputs a 3D printer file, enabling users to create molds of upscaled 3D models.

Abstract: A system and method for generating trivia questions in artificial intelligence (AI)-driven gameplay. The system and method incorporate a trivia application with a user interface connected to a generative AI model. Upon receiving a trivia topic from the user interface, the system displays and reserves select responses based on expected user interactivity time. The system and method also include automatic input triggers for subsequent response generation, minimizing any latency between displaying responses to the user interface.

Abstract: The technology discloses a system for validation of generative AI model operators using preloaded query context connected to independent AI models in generative AI-driven trivia gameplay. The system includes a user interface connected to a generative AI model that generates trivia responses based on user input. A model superstructure between the user interface, the generative AI model, and independent validation model(s) facilitates the evaluation of the user input or trivia response by the validation model(s). The validation model(s) are provided with a pre-loaded query context to detect adherence to predetermined conditions. A consensus module receives the validation model's output and delivers the user input or trivia response to the generative AI model or user interface, respectively, based on the evaluation.

Abstract: The technology discloses a system for validation of generative AI model operators using preloaded query context connected to independent AI models in generative AI-driven trivia gameplay. The system includes a user interface connected to a generative AI model that generates trivia responses based on user input. A model superstructure between the user interface, the generative AI model, and independent validation model(s) facilitates the evaluation of the user input or trivia response by the validation model(s). The validation model(s) are provided with a pre-loaded query context to detect adherence to predetermined conditions. A consensus module receives the validation model's output and delivers the user input or trivia response to the generative AI model or user interface, respectively, based on the evaluation.