Patents by Inventor Bowen Baker

Bowen Baker 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).

  • USING MACHINE LEARNING TO TRAIN AND USE A MODEL TO PERFORM AUTOMATIC INTERFACE ACTIONS BASED ON VIDEO AND INPUT DATASETS
    Publication number: 20240355120
    Abstract: Disclosed herein are methods, systems, and computer-readable media for training a machine learning model to label unlabeled data and/or perform automated actions. In an embodiment, a method comprises receiving unlabeled digital video data, generating pseudo-labels for the unlabeled digital video data, the generating comprising receiving labeled digital video data, training an inverse dynamics model (IDM) using the labeled digital video data, and generating at least one pseudo-label for the unlabeled digital video data, wherein the at least one pseudo-label is based on a prediction, generated by the IDM, of one or more actions that mimic at least one timestep of the unlabeled digital video data. In some embodiments, the method further comprises adding the at least one pseudo-label to the unlabeled digital video data and further training the IDM or a machine learning model using the pseudo-labeled digital video data.
    Type: Application
    Filed: December 19, 2023
    Publication date: October 24, 2024
    Applicant: OpenAl Opco, LLC
    Inventors: Bowen BAKER, llge AKKAYA, Peter ZHOKHOV, Joost HUIZINGA, Jie TANG, Adrien ECOFFET, Brandon HOUGHTON, Raul Sampedro GONZALEZ, Jeffrey CLUNE
  • Using machine learning to train and use a model to perform automatic interface actions based on video and input datasets
    Patent number: 11887367
    Abstract: Disclosed herein are methods, systems, and computer-readable media for training a machine learning model to label unlabeled data and/or perform automated actions. In an embodiment, a method comprises receiving unlabeled digital video data, generating pseudo-labels for the unlabeled digital video data, the generating comprising receiving labeled digital video data, training an inverse dynamics model (IDM) using the labeled digital video data, and generating at least one pseudo-label for the unlabeled digital video data, wherein the at least one pseudo-label is based on a prediction, generated by the IDM, of one or more actions that mimic at least one timestep of the unlabeled digital video data. In some embodiments, the method further comprises adding the at least one pseudo-label to the unlabeled digital video data and further training the IDM or a machine learning model using the pseudo-labeled digital video data.
    Type: Grant
    Filed: April 19, 2023
    Date of Patent: January 30, 2024
    Assignee: OpenAI Opco, LLC
    Inventors: Bowen Baker, Ilge Akkaya, Peter Zhokhov, Joost Huizanga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro Gonzalez, Jeffrey Clune