Patents by Inventor Jared Roesch

Jared Roesch 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: 20240386322
    Abstract: A facility for inserting instrumentation hooks into machine learning models is described. The facility receives an indication of a machine learning model and identifies one or more aspects of the machine leaning model. The facility receives an indication that an instrumentation hook is to be used to collect data for at least one aspect of the one or more aspects. The facility alters the machine learning model by inserting at least one instrumentation hook into the machine learning model and collects data regarding one or more aspects of the machine learning model via the instrumentation hook.
    Type: Application
    Filed: April 26, 2024
    Publication date: November 21, 2024
    Inventors: Jason Knight, Luis Ceze, Itay Neeman, Jared Roesch, Andrew Reusch
  • Publication number: 20240303549
    Abstract: A facility for automatically adapting machine learning models for operation or execution on resources is described. The facility receives an indication of a machine learning model and resource constraints for the machine learning model. The facility determines which resources should be allocated for operation of the machine learning model based on the resource constraints and an indication of two or more resources. The facility causes the determined resources to be provisioned for operation of the machine learning model.
    Type: Application
    Filed: March 5, 2024
    Publication date: September 12, 2024
    Inventors: Jason Knight, Luis Ceze, Itay Neeman, Jared Roesch, Spencer Krum
  • Publication number: 20240112089
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Application
    Filed: December 13, 2023
    Publication date: April 4, 2024
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Patent number: 11886963
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Grant
    Filed: February 23, 2021
    Date of Patent: January 30, 2024
    Assignee: OctoML, Inc.
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Patent number: 11816545
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Grant
    Filed: November 9, 2021
    Date of Patent: November 14, 2023
    Assignee: OCTOML, INC.
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Publication number: 20220172119
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Application
    Filed: November 9, 2021
    Publication date: June 2, 2022
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Publication number: 20220172110
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Application
    Filed: February 23, 2021
    Publication date: June 2, 2022
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Patent number: 11348036
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Grant
    Filed: February 23, 2021
    Date of Patent: May 31, 2022
    Assignee: OctoML, Inc.
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Patent number: 11315042
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Grant
    Filed: February 23, 2021
    Date of Patent: April 26, 2022
    Assignee: OctoML, Inc.
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes
  • Patent number: 11216752
    Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.
    Type: Grant
    Filed: February 23, 2021
    Date of Patent: January 4, 2022
    Assignee: OctoML, Inc.
    Inventors: Matthew Welsh, Jason Knight, Jared Roesch, Thierry Moreau, Adelbert Chang, Tianqi Chen, Luis Henrique Ceze, An Wang, Michal Piszczek, Andrew McHarg, Fletcher Haynes