Patents by Inventor Jacob Daniel Devlin

Jacob Daniel Devlin 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).

  • ATTENTION NEURAL NETWORKS WITH PARALLEL ATTENTION AND FEED-FORWARD LAYERS
    Publication number: 20240386257
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing a machine learning task on a network input to generate a network output. One of the systems comprises an attention neural network configured to perform the machine learning task, the attention neural network comprising a plurality of attention layers, each attention layer comprising an attention sub-layer that is arranged in parallel with a feed-forward sub-layer.
    Type: Application
    Filed: July 29, 2024
    Publication date: November 21, 2024
    Inventors: Aakanksha Chowdhery, Jacob Daniel Devlin, Sharan Narang
  • Attention neural networks with parallel attention and feed-forward layers
    Patent number: 12050983
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing a machine learning task on a network input to generate a network output. One of the systems comprises an attention neural network configured to perform the machine learning task, the attention neural network comprising a plurality of attention layers, each attention layer comprising an attention sub-layer that is arranged in parallel with a feed-forward sub-layer.
    Type: Grant
    Filed: April 3, 2023
    Date of Patent: July 30, 2024
    Assignee: Google LLC
    Inventors: Aakanksha Chowdhery, Jacob Daniel Devlin, Sharan Narang
  • ATTENTION NEURAL NETWORKS WITH PARALLEL ATTENTION AND FEED-FORWARD LAYERS
    Publication number: 20230316055
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing a machine learning task on a network input to generate a network output. One of the systems comprises an attention neural network configured to perform the machine learning task, the attention neural network comprising a plurality of attention layers, each attention layer comprising an attention sub-layer that is arranged in parallel with a feed-forward sub-layer.
    Type: Application
    Filed: April 3, 2023
    Publication date: October 5, 2023
    Inventors: Aakanksha Chowdhery, Jacob Daniel Devlin, Sharan Narang, Jr.