Patents by Inventor Anton Ruddock

Anton Ruddock 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).

  • Computer code generation from task descriptions using neural networks
    Patent number: 12675261
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating computer code using neural networks. One of the methods includes receiving data describing a computer programming task; generating a plurality of candidate computer programs by sampling a plurality of output sequences from a set of one or more generative neural networks; clustering the plurality of candidate computer programs; for each cluster in a set of the clusters: processing each of the respective plurality of candidate computer programs in the cluster using a correctness estimation neural network to generate a correctness score for the candidate computer program; and selecting a representative computer program for the cluster using the correctness scores for the respective plurality of candidate computer programs in the cluster; and selecting one or more of the representative computer programs for the clusters as synthesized computer programs for performing the computer programming task.
    Type: Grant
    Filed: December 5, 2024
    Date of Patent: July 7, 2026
    Assignee: GDM Holding LLC
    Inventors: Rémi Leblond, Alaa Saade, Corentin Tallec, Felix Axel Gimeno Gil, Florent Altché, Jean-Bastien François Laurent Grill, Matthias Heinz Lochbrunner, Paul Caron, Anton Ruddock, George Powell, Michael Fabien Serge Mathieu, Maciej Mikula
  • COMPUTER CODE GENERATION FROM TASK DESCRIPTIONS USING NEURAL NETWORKS
    Publication number: 20250181325
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating computer code using neural networks. One of the methods includes receiving data describing a computer programming task; generating a plurality of candidate computer programs by sampling a plurality of output sequences from a set of one or more generative neural networks; clustering the plurality of candidate computer programs; for each cluster in a set of the clusters: processing each of the respective plurality of candidate computer programs in the cluster using a correctness estimation neural network to generate a correctness score for the candidate computer program; and selecting a representative computer program for the cluster using the correctness scores for the respective plurality of candidate computer programs in the cluster; and selecting one or more of the representative computer programs for the clusters as synthesized computer programs for performing the computer programming task.
    Type: Application
    Filed: December 5, 2024
    Publication date: June 5, 2025
    Inventors: Rémi Leblond, Alaa Saade, Corentin Tallec, Felix Axel Gimeno Gil, Florent Altché, Jean-Bastien François Laurent Grill, Matthias Heinz Lochbrunner, Paul Caron, Anton Ruddock, George Powell, Michael Fabien Serge Mathieu, Maciej Mikula