Patents by Inventor Alain Charles Briancon

Alain Charles Briancon 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: 20240226863
    Abstract: Provided is a methodology to improve soil performance by dispersing stabilized low C:N non-highly polymerized porous lignocellulose catalytic that improves porosity, carbon capture, and microbial activities.
    Type: Application
    Filed: October 19, 2023
    Publication date: July 11, 2024
    Inventors: Griffin William Roberts, Robert K. Herrington, Trish Lyn Jackson, Alain Charles Briancon
  • Publication number: 20240131500
    Abstract: Provided is a methodology to improve soil performance by dispersing stabilized low C:N non-highly polymerized porous lignocellulose catalytic that improves porosity, carbon capture, and microbial activities.
    Type: Application
    Filed: October 18, 2023
    Publication date: April 25, 2024
    Inventors: Griffin William Roberts, Robert K. Herrington, Trish Lyn Jackson, Alain Charles Briancon
  • Patent number: 11893520
    Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.
    Type: Grant
    Filed: June 7, 2022
    Date of Patent: February 6, 2024
    Assignee: Cerebri AI Inc.
    Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
  • Publication number: 20240013314
    Abstract: Provided is a process including: writing, with a computing system, a first plurality of classes using object-oriented modelling of modelling methods; writing, with the computing system, a second plurality of classes using object-oriented modelling of governance; scanning, with the computing system, a set of libraries collectively containing both modelling object classes among the first plurality of classes and governance classes among the second plurality of classes to determine class definition information; using, with the computing system, at least some of the class definition information to produce object manipulation functions, wherein the object manipulation functions allow a governance system to access methods and attributes of classes among first plurality of classes or the second plurality of classes to manipulate objects of at least some of the modelling object classes; and using at least some of the class definition information to effectuate access to the object manipulation functions.
    Type: Application
    Filed: August 28, 2023
    Publication date: January 11, 2024
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Thejas Narayana Prasad, Mirza Safiullah Baig
  • Publication number: 20230334580
    Abstract: Provided is a process including: writing modelling-object classes using object-oriented modelling of the modelling methods, the modelling-object classes being members of a set of class libraries; writing quality-management classes using object-oriented modelling of quality management, the quality-management classes being members of the set of class libraries; scanning modelling-object classes in the set of class libraries to determine modelling-object class definition information; scanning quality-management classes in the set of class libraries to determine quality-management class definition information; using the modelling-object class definition information and the quality-management class definition information to produce object manipulation functions that allow a quality management system to access methods and attributes of modelling-object classes to manipulate objects of the modelling-object classes; and using the modelling-object class definition information and the quality-management class definitio
    Type: Application
    Filed: January 6, 2023
    Publication date: October 19, 2023
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Travis Stanton Penn, Divya Karumuri, Valisis Sotiris
  • Patent number: 11783375
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Grant
    Filed: July 8, 2022
    Date of Patent: October 10, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • Patent number: 11776060
    Abstract: Provided is a process including: writing, with a computing system, a first plurality of classes using object-oriented modelling of modelling methods; writing, with the computing system, a second plurality of classes using object-oriented modelling of governance; scanning, with the computing system, a set of libraries collectively containing both modelling object classes among the first plurality of classes and governance classes among the second plurality of classes to determine class definition information; using, with the computing system, at least some of the class definition information to produce object manipulation functions, wherein the object manipulation functions allow a governance system to access methods and attributes of classes among first plurality of classes or the second plurality of classes to manipulate objects of at least some of the modelling object classes; and using at least some of the class definition information to effectuate access to the object manipulation functions.
    Type: Grant
    Filed: June 3, 2020
    Date of Patent: October 3, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Thejas Narayana Prasad, Mirza Safiullah Baig
  • Publication number: 20230287271
    Abstract: Provided is a class of functional soil amendment a C:N ratio that does require a cascading effect to produce solid organic matter and improve porosity. This results in superior carbon capture.
    Type: Application
    Filed: February 13, 2023
    Publication date: September 14, 2023
    Applicant: Prairiechar, Inc.
    Inventors: Trish Lyn Jackson, Robert K. Herrington, Griffin William Roberts, Alain Charles Briancon
  • Publication number: 20230265021
    Abstract: Provided is a process and material including the operation of a reactor that applies kinetic energy, heat, and pressure are performed nearly concurrently to biomass feeding of biomass to create functional soil amendment with superior SOM creation and carbon capture.
    Type: Application
    Filed: February 13, 2023
    Publication date: August 24, 2023
    Inventors: Griffin William Roberts, Robert K Herrington, Trish Lyn Jackson, Alain Charles Briancon
  • Publication number: 20230257955
    Abstract: Provided is a methodology to improve soil performance by dispersing stabilized low C:N non highly polymerized porous soil amendment that improves porosity, carbon capture, and microbial activities.
    Type: Application
    Filed: February 13, 2023
    Publication date: August 17, 2023
    Applicant: Prairiechar, Inc.
    Inventors: Robert K. Herrington, Griffin William Roberts, Trish Lyn Jackson, Alain Charles Briancon
  • Publication number: 20230222387
    Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given duration of time in the future; and storing the trained predictive machine learning model in memory.
    Type: Application
    Filed: March 7, 2023
    Publication date: July 13, 2023
    Inventors: Sathish Kumar Lakshmipathy, Eyal Ben Zion, David Alexander Curry, Alain Charles Briancon, Michael Henry Engeling, Dmitrii Aleksandrovich Boldyrev, Sara Amini
  • Publication number: 20230206124
    Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.
    Type: Application
    Filed: December 21, 2022
    Publication date: June 29, 2023
    Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
  • Patent number: 11689233
    Abstract: A circuit for direct current (DC) offset estimation comprises a quantile value circuit and a signal processor. The quantile value circuit determines a plurality of quantile values of an input signal and includes a plurality of quantile filters. Each quantile filter includes a comparator, a level shifter, a monotonic transfer function component, and a latched integrator. The comparator compares the input signal and a quantile value. The level shifter shifts the output of the comparator. The monotonic transfer function component determines the magnitude of the shifted signal and provide a transfer function signal. The latched integrator suppresses transient characteristics of the transfer function signal and provide the quantile value. The signal processor is configured to calculate a weighted average of the quantile values to yield a DC offset estimate.
    Type: Grant
    Filed: October 18, 2021
    Date of Patent: June 27, 2023
    Assignee: Alarm.com Incorporated
    Inventors: Alain Charles Briancon, Marc Anthony Epard, Robert Leon Lutes, John Berns Lancaster, Jerald Frederic Johnson, Ronald Byron Kabler
  • Publication number: 20230135619
    Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given geographic locale in the future; and storing the training the trained predictive machine learning model in memory.
    Type: Application
    Filed: October 7, 2022
    Publication date: May 4, 2023
    Inventors: Alain Charles Briancon, Eyal Ben Zion, Sumant Sudhir Kawale, Sara Amini
  • Patent number: 11636393
    Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given duration of time in the future; and storing the trained predictive machine learning model in memory.
    Type: Grant
    Filed: May 6, 2020
    Date of Patent: April 25, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Sathish Kumar Lakshmipathy, Eyal Ben Zion, David Alexander Curry, Alain Charles Briancon, Michael Henry Engeling, Dmitrii Aleksandrovich Boldyrev, Sara Amini
  • Patent number: 11620477
    Abstract: Provided is a process including: writing classes using object-oriented modelling of modeling topics; scanning the classes to determine class definition information; receiving from a subscribing modeling object a request for a subscription to a given modeling topic in a given modeling topic class, the subscription request including a modeling topic filter to select the given modeling topic from a plurality of modeling topics described by the given modeling topic class; registering a modeling topic accessor associated with the subscribing modeling object and a modeling topic mutator associated with the subscribing modeling object; processing, through the modeling topic filter a modeling topic that is accessed through an accessor and is described by the modeling topic class, the modeling topic being received from a modeling publisher object; notifying the subscribing object of the received modeling topic through a registered modeling topic listener; and mutating the received modeling topic.
    Type: Grant
    Filed: June 3, 2020
    Date of Patent: April 4, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Bryan Wayne Collins, Eric Paver Simon, Alain Charles Briancon, Mirza Safiullah Baig, Yarden Arane, Wenjie Wu, Divya Karumuri, Kevin Bryce
  • Publication number: 20230101487
    Abstract: Provided is a process, including: obtaining a first training dataset, training a first machine-learning model on the first training dataset, obtaining a set of candidate question sequences, forming virtual subject-entity records, forming a second training dataset, training a second machine-learning model, and storing the adjusted parameters of the second machine-learning model in memory.
    Type: Application
    Filed: July 8, 2022
    Publication date: March 30, 2023
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, James Cvetan Stojanov, Christopher Michael Coovrey, Pranav Mahesh Makhijani, Gregory Klose, Max Changchun Huang, Mounib Mohamad Ismail, Michael Henry Engeling, Hongshi Li
  • Patent number: 11615271
    Abstract: Provided is a process of modeling methods organized in racks of a machine learning pipeline to facilitate optimization of performance using modelling methods for implementation of machine learning design in an object-oriented modeling (OOM) framework, the process including: writing classes using object-oriented modelling of optimization methods, modelling methods, and modelling racks; writing parameters and hyper-parameters of the modeling methods as attributes as the modeling methods; scanning modelling racks classes to determine first class definition information; selecting a collection of rack and selecting modeling method objects; scanning modelling method classes to determine second class definition information; assigning racks and locations within the racks to modeling method objects; and invoking the class definition information to produce object manipulation functions that allow access the methods and attributes of at least some of the modeling method objects, the manipulation functions being configur
    Type: Grant
    Filed: June 3, 2020
    Date of Patent: March 28, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Eyal Ben Zion, Alain Charles Briancon, Pranav Mahesh Makhijani, Thejas Narayana Prasad, Sara Amini, Jian Deng, Ngoc Thu Nguyen, Jean Joseph Belanger
  • Publication number: 20230080773
    Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.
    Type: Application
    Filed: June 7, 2022
    Publication date: March 16, 2023
    Inventors: Gabriel Mauricio Silberman, Alain Charles Briancon, Lee David Harper, Luke Philip Reding, David Alexander Curry, Jean Joseph Belanger, Michael Thomas Wegan, Thejas Narayana Prasad
  • Patent number: 11599752
    Abstract: Provided is a process including: writing modelling-object classes using object-oriented modelling of the modelling methods, the modelling-object classes being members of a set of class libraries; writing quality-management classes using object-oriented modelling of quality management, the quality-management classes being members of the set of class libraries; scanning modelling-object classes in the set of class libraries to determine modelling-object class definition information; scanning quality-management classes in the set of class libraries to determine quality-management class definition information; using the modelling-object class definition information and the quality-management class definition information to produce object manipulation functions that allow a quality management system to access methods and attributes of modelling-object classes to manipulate objects of the modelling-object classes; and using the modelling-object class definition information and the quality-management class definitio
    Type: Grant
    Filed: June 3, 2020
    Date of Patent: March 7, 2023
    Assignee: Cerebri AI Inc.
    Inventors: Alain Charles Briancon, Jean Joseph Belanger, Chris Michael Coovrey, Travis Stanton Penn, Divya Karumuri, Valisis Sotiris