Patents by Inventor Alex C. Tozzo

Alex C. Tozzo has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240403649
    Abstract: In an example, a system includes processing circuitry in communication with storage media. The processing circuitry is configured to execute a machine learning system including at least a first module, a second module and a third module. The machine learning system is configured to train one or more machine learning models. The first module is configured to generate augmented input data based on the streaming input data. The second module includes a machine learning model configured to perform a specific task based at least in part on the augmented input data. The third module configured to adapt a network architecture of the one or more machine learning models based on changes in the streaming input data.
    Type: Application
    Filed: November 28, 2023
    Publication date: December 5, 2024
    Inventors: Han-Pang Chiu, Yi Yao, Zachary Seymour, Alex Krasner, Bradley J. Clymer, Michael A. Cogswell, Cecile Eliane Jeannine Mackay, Alex C. Tozzo, Tixiao Shan, Philip Miller, Chuanyong Gan, Glenn A. Murray, Richard Louis Ferranti, Uma Rajendran, Supun Samarasekera, Rakesh Kumar, James Smith
  • Patent number: 10825227
    Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.
    Type: Grant
    Filed: December 21, 2018
    Date of Patent: November 3, 2020
    Assignee: SRI International
    Inventors: Mohamed R. Amer, Alex C. Tozzo, Dejan Jovanovic, Timothy J. Meo
  • Patent number: 10789755
    Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.
    Type: Grant
    Filed: December 21, 2018
    Date of Patent: September 29, 2020
    Assignee: SRI International
    Inventors: Mohamed R. Amer, Timothy J. Meo, Aswin Nadamuni Raghavan, Alex C. Tozzo, Amir Tamrakar, David A. Salter, Kyung-Yoon Kim
  • Publication number: 20190304157
    Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.
    Type: Application
    Filed: December 21, 2018
    Publication date: October 3, 2019
    Inventors: Mohamed R. Amer, Timothy J. Meo, Aswin Nadamuni Raghavan, Alex C. Tozzo, Amir Tamrakar, David A. Salter, Kyung-Yoon Kim
  • Publication number: 20190304156
    Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.
    Type: Application
    Filed: December 21, 2018
    Publication date: October 3, 2019
    Inventors: Mohamed R. Amer, Alex C. Tozzo, Dejan Jovanovic, Timothy J. Meo