Patents by Inventor David Andre

David Andre 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).

  • Patent number: 11693637
    Abstract: Using a natural language (NL) latent presentation in the automated conversion of source code from a base programming language (e.g., C++) to a target programming language (e.g., Python). A base-to-NL model can be used to generate an NL latent representation by processing a base source code snippet in the base programming language. Further, an NL-to-target model can be used to generate a target source code snippet in the target programming language (that is functionally equivalent to the base source code snippet), by processing the NL latent representation. In some implementations, output(s) from the NL-to-target model indicate canonical representation(s) of variables, and in generating the target source code snippet, technique(s) are used to match those canonical representation(s) to variable(s) of the base source code snippet. In some implementations, multiple candidate target source code snippets are generated, and a subset (e.g., one) is selected based on evaluation(s).
    Type: Grant
    Filed: May 13, 2021
    Date of Patent: July 4, 2023
    Assignee: GOOGLE LLC
    Inventors: Rishabh Singh, Hanjun Dai, Manzil Zaheer, Artem Goncharuk, Karen Davis, David Andre
  • Publication number: 20230188940
    Abstract: The technology enables locating asset tracking tags based on a ramped sequence of signals from one or more beacon tracking tags. The sequence includes at least one minimum power signal and at least one maximum power signal. Each signal in the sequence has a tag identifier and an initial signal strength value. Each beacon signal in the ramped sequence is associated with the time at which that beacon signal was received by a reader. Each beacon signal is also associated with a received signal strength at reception. A location of the beacon tracking tag is estimated according to the signals in the sequence based on the difference between the initial and received signal strengths. A position of the reader device is identified based on the beacon tag's location. An asset tracking tag location is identified based on the reader's location and packets received by the reader from the asset tag.
    Type: Application
    Filed: April 22, 2022
    Publication date: June 15, 2023
    Applicant: X DEVELOPMENT LLC
    Inventors: David Andre, Erich Karl Nachbar
  • Patent number: 11669098
    Abstract: Autonomous control of a subject vehicle including a longitudinal motion control system includes determining states of parameters associated with a trajectory for the subject vehicle and parameters associated with a control reference determined for the subject vehicle. A range control routine is executed to determine a first parameter associated with a range control command based upon the states of the plurality of parameters, and a speed control routine is executed to determine a second parameter associated with a speed control command based upon the states of the plurality of parameters. An arbitration routine is executed to evaluate the range control command and the speed control command, and operation of the subject vehicle is controlled to achieve a desired longitudinal state, wherein the desired longitudinal state is associated with a minimum of the range control command and the speed control command.
    Type: Grant
    Filed: February 7, 2019
    Date of Patent: June 6, 2023
    Assignee: GM Global Technology Operations LLC
    Inventors: Nikolai K. Moshchuk, Kausalya Singuru, David Andrés Pérez Chaparro
  • Patent number: 11656867
    Abstract: Implementations are described herein for using machine learning to perform various tasks related to migrating source code based on relatively few (“few shots”) demonstrations. In various implementations, an autoregressive language model may be conditioned based on demonstration tuple(s). In some implementations, a demonstration tuple may include a pre-migration version of a first source code snippet and a post-migration version of the first source code snippet. In other implementations, demonstration tuples may include other data, such as intermediate forms (e.g., natural language descriptions or pseudocode), input-output pairs demonstrating intended behavior, etc. The autoregressive language model may be trained on corpora of source code and natural language documentation on the subject of computer programming.
    Type: Grant
    Filed: September 15, 2022
    Date of Patent: May 23, 2023
    Assignee: GOOGLE LLC
    Inventors: Rishabh Singh, David Andre, Bin Ni, Owen Lewis
  • Publication number: 20230144113
    Abstract: Methods and systems including receiving a plurality of shipping bids from a plurality of shipping entities, each entity having goods to ship from locations to destinations, wherein each bid represents an option to ship goods at a shipping price, and wherein each bid comprises a plurality of shipping parameters; receiving a plurality of carrier bids from a plurality of carrier entities, each entity transporting the goods, wherein each bid represents an option to transport the goods at a price, and wherein each bid comprises a plurality of carrier parameters; performing a matching process to generate a plurality of pair-wise partial matches, wherein each match associates a shipping and carrier bid at a modified price, wherein the modified price is based on a deviation between the parameters; providing information representing the matches to the shipping and carrier entities; and generating training data representing which matches were exercised.
    Type: Application
    Filed: November 9, 2022
    Publication date: May 11, 2023
    Inventors: Salil Vijaykumar Pradhan, Grigory Bronevetsky, Ryan Butterfoss, Rebecca Radkoff, David Andre, Randolph Preston McAfee, John Michael Stivoric, Grace Taixi Brentano, Sze Man Lee
  • Publication number: 20230117297
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatic generation of a supply chain simulation. The methods, systems, and apparatus include actions of obtaining supply chain data of a supply chain, generating a supply chain network graph that represents relationships between locations indicated by the supply chain data, determining classifications of the locations indicated by the supply chain data, determining agent rule models based on the supply chain data, and generating a supply chain simulation based on the supply chain network graph, the classifications of the locations, and the agent rule models.
    Type: Application
    Filed: October 18, 2022
    Publication date: April 20, 2023
    Inventors: Ryan Butterfoss, David Andre, Salil Vijaykumar Pradhan, Rebecca Radkoff
  • Publication number: 20230076994
    Abstract: A container for a plurality of articles comprising a main body, a hollow member fixedly coupled to an end of the main body and a cup member movably coupled to the hollow member. When the cup member is in an open position the cup member and the hollow member are spaced defining an opening. A slider is movably coupled to the cup member. The slider has a spring, such that when the slider is moved relative to the cup member in a radial direction the slider carries an article towards the opening and the spring on the slider is flexed. After dispensing, the spring gradually relaxes, resetting the slider.
    Type: Application
    Filed: September 8, 2022
    Publication date: March 9, 2023
    Inventors: Scott David Hochberg, Brian David Andres, Kyle William Harris, Nicole Alisa Renee Lockett Turner, Matthew John Boehm, Christian Alexander Zipperer, Geoffrey Allen King
  • Publication number: 20230018088
    Abstract: Implementations are described herein for using machine learning to perform various tasks related to migrating source code based on relatively few (“few shots”) demonstrations. In various implementations, an autoregressive language model may be conditioned based on demonstration tuple(s). In some implementations, a demonstration tuple may include a pre-migration version of a first source code snippet and a post-migration version of the first source code snippet. In other implementations, demonstration tuples may include other data, such as intermediate forms (e.g., natural language descriptions or pseudocode), input-output pairs demonstrating intended behavior, etc. The autoregressive language model may be trained on corpora of source code and natural language documentation on the subject of computer programming.
    Type: Application
    Filed: September 15, 2022
    Publication date: January 19, 2023
    Inventors: Rishabh Singh, David Andre, Bin Ni, Owen Lewis
  • Publication number: 20220414419
    Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus for selecting actions to be performed by an agent interacting with an environment, the method including, at each of multiple time steps, receiving an observation characterizing a current state of the environment at the time step, providing an input including the observation to an action selection neural network having a brain emulation sub-network with an architecture that is based on synaptic connectivity between biological neurons in a brain of a biological organism, processing the input including the observation characterizing the current state of the environment at the time step using the action selection neural network having the brain emulation sub-network to generate an action selection output, and selecting an action to be performed by the agent at the time step based on the action selection output.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 29, 2022
    Inventors: Sarah Ann Laszlo, David Andre, Rednar Rosique Rodriquez
  • Publication number: 20220405489
    Abstract: Implementations are described herein for formulating natural language descriptions based on temporal sequences of digital images. In various implementations, a natural language input may be analyzed. Based on the analysis, a semantic scope to be imposed on a natural language description that is to be formulated based on a temporal sequence of digital images may be determined. The temporal sequence of digital images may be processed based on one or more machine learning models to identify one or more candidate features that fall within the semantic scope. One or more other features that fall outside of the semantic scope may be disregarded. The natural language description may be formulated to describe one or more of the candidate features.
    Type: Application
    Filed: March 29, 2022
    Publication date: December 22, 2022
    Inventors: Rebecca Radkoff, David Andre
  • Patent number: 11524836
    Abstract: A container for a plurality of articles comprising a main body, a hollow member fixedly coupled to an end of the main body, a cup member rotatably coupled to the hollow member, and a cam arm received within the hollow member and the cup member. The hollow member and the cup member define a dispensing opening. The cup member comprises a base portion defining a grooved track facing the end of the main body. The cam arm is configured to engage a bottom article from the plurality of articles and comprises a protrusion movably engaged with the grooved track. The cam arm moves relative to the hollow member, due to a relative rotation between the hollow member and the cup member, to a dispensing position in which the bottom article at least partially extends through the dispensing opening and is removable from the container.
    Type: Grant
    Filed: September 9, 2021
    Date of Patent: December 13, 2022
    Assignee: The Procter & Gamble Company
    Inventors: Scott David Hochberg, Brian David Andres, Kyle William Harris, Nicole Alisa Renee Lockett Turner, Matthew John Boehm, Christian Alexander Zipperer
  • Publication number: 20220366533
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating high-resolution fire distribution maps. In some implementations, a computer-implemented system obtains a low-resolution distribution map indicating fire distribution of an area with fire burning and a reference map indicating features of the same area. The system processes the low-resolution distribution map and the reference map using a generator neural network to generate output data including a high-resolution synthesized distribution map indicating fire distribution of the area. The generator neural network is trained, based on a plurality of training examples, with a discriminator neural network that outputs a prediction of whether an input to the discriminator neural network is a real distribution map or a synthesized distribution map.
    Type: Application
    Filed: May 17, 2021
    Publication date: November 17, 2022
    Inventors: Eliot Julien Cowan, David Andre, Benjamin Goddard Mullet
  • Patent number: 11487522
    Abstract: Training and/or utilization of a neural decompiler that can be used to generate, from a lower-level compiled representation, a target source code snippet in a target programming language. In some implementations, the lower-level compiled representation is generated by compiling a base source code snippet that is in a base programming language, thereby enabling translation of the base programming language (e.g., C++) to a target programming language (e.g., Python). In some of those implementations, output(s) from the neural decompiler indicate canonical representation(s) of variables. Technique(s) can be used to match those canonical representation(s) to variable(s) of the base source code snippet. In some implementations, multiple candidate target source code snippets are generated using the neural decompiler, and a subset (e.g., one) is selected based on evaluation(s).
    Type: Grant
    Filed: May 12, 2021
    Date of Patent: November 1, 2022
    Assignee: X DEVELOPMENT LLC
    Inventors: Rishabh Singh, Nisarg Vyas, Jayendra Parmar, Dhara Kotecha, Artem Goncharuk, David Andre
  • Patent number: 11481210
    Abstract: Implementations are described herein for using machine learning to perform various tasks related to migrating source code based on relatively few (“few shots”) demonstrations. In various implementations, an autoregressive language model may be conditioned based on demonstration tuple(s). In some implementations, a demonstration tuple may include a pre-migration version of a first source code snippet and a post-migration version of the first source code snippet. In other implementations, demonstration tuples may include other data, such as intermediate forms (e.g., natural language descriptions or pseudocode), input-output pairs demonstrating intended behavior, etc. The autoregressive language model may be trained on corpora of source code and natural language documentation on the subject of computer programming.
    Type: Grant
    Filed: December 29, 2020
    Date of Patent: October 25, 2022
    Assignee: X DEVELOPMENT LLC
    Inventors: Rishabh Singh, David Andre, Bin Ni, Owen Lewis
  • Patent number: 11440813
    Abstract: A faucet-mounted filter system includes a body forming a fluid chamber having a water inlet, a quick connect device positioned adjacent the water inlet for mounting the filter system to a water faucet, a filtered water flow path disposed within the body and in fluid communication with the water inlet, an unfiltered water flow path disposed within the body and in fluid communication with the water inlet, a diverter valve disposed within the fluid chamber and operable to open and close the filtered and unfiltered water flow paths, a seal, an actuator engaging the diverter valve to open and close the filtered and unfiltered water flow paths, a flow meter connected to the body and in fluid communication with the filter flow path, a filter housing connected to the body and having a reservoir, and a filter cartridge disposed within the reservoir.
    Type: Grant
    Filed: October 16, 2018
    Date of Patent: September 13, 2022
    Assignee: Helen of Troy Limited
    Inventors: John Tanner, David Emmons, Matthew Lloyd Newman, Brian David Andres, Simon Leung, Steven James Schroeck, Armin Schwarz-Hartmann, Peter Stoeffel, Richard Paul Riedel
  • Publication number: 20220206785
    Abstract: Implementations are described herein for using machine learning to perform various tasks related to migrating source code based on relatively few (“few shots”) demonstrations. In various implementations, an autoregressive language model may be conditioned based on demonstration tuple(s). In some implementations, a demonstration tuple may include a pre-migration version of a first source code snippet and a post-migration version of the first source code snippet. In other implementations, demonstration tuples may include other data, such as intermediate forms (e.g., natural language descriptions or pseudocode), input-output pairs demonstrating intended behavior, etc. The autoregressive language model may be trained on corpora of source code and natural language documentation on the subject of computer programming.
    Type: Application
    Filed: December 29, 2020
    Publication date: June 30, 2022
    Inventors: Rishabh Singh, David Andre, Bin Ni, Owen Lewis
  • Publication number: 20220202348
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing brain emulation neural networks on user devices. One of the methods includes obtaining, by a first component of a user device, a network input; processing, by the first component of the user device, the network input using an artificial neural network to generate a network output, wherein the artificial neural network has a network architecture that has been determined according to a synaptic connectivity graph, wherein the synaptic connectivity graph represents synaptic connectivity between neurons in a brain of a biological organism; and providing the network output for use by one or more second components of the user device.
    Type: Application
    Filed: December 31, 2020
    Publication date: June 30, 2022
    Inventors: Sarah Ann Laszlo, David Andre, Doris Tang, Farooq Ahmad
  • Patent number: 11351880
    Abstract: An automotive vehicle includes a vehicle-based charging unit including a receiving unit configured to receive power from a ground-based charging unit, the receiving unit including a multi-coil receiver, a first actuator operably coupled to the vehicle-based charging unit and configured to adjust a first position of the vehicle-based charging unit relative to the ground-based charging unit, and a controller configured to selectively actuate the first actuator.
    Type: Grant
    Filed: August 28, 2019
    Date of Patent: June 7, 2022
    Assignee: GM Global Technology Operations LLC
    Inventors: Kausalya Singuru, Suresh Gopalakrishnan, Nikolai K. Moshchuk, David Andrés Pérez Chaparro
  • Patent number: 11352533
    Abstract: The invention relates to a method for cooling or heating a fluid or a body by means of a vapour compression circuit containing a heat transfer fluid, said circuit being at least partially contained in an enclosure, and the relative humidity of the air in the enclosure being less than or equal to a threshold value H1 which is less than 50%, the flammability of the heat transfer fluid at relative humidity H1 being less than the flammability of the heat transfer fluid at 50% relative humidity. The invention also relates to a cooling or heating installation suited to the implementation of this method. The invention also relates to a method of protection against the risks of fire or explosion in an enclosure containing at least partially a vapour compression circuit containing a heat transfer fluid, as well as a method for reducing the GWP of a transfer fluid. The invention also relates to heat transfer fluids suited to the implementation of the above methods.
    Type: Grant
    Filed: September 19, 2018
    Date of Patent: June 7, 2022
    Assignee: ARKEMA FRANCE
    Inventors: David Andre, Beatrice Boussand, Wissam Rached
  • Publication number: 20220164177
    Abstract: Methods and apparatuses implement docker containers with an application store involved in deployment of the containers. Implementation of the containers may be performed via remote controlling means, and the containers may be subsequently updated, including firmware updates.
    Type: Application
    Filed: November 24, 2021
    Publication date: May 26, 2022
    Inventors: Daniel Jay WALKES, David Andres Alejandro SOTO MORA