Patents by Inventor Jeffrey Adgate Dean

Jeffrey Adgate Dean 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: 20220351091
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a distilled machine learning model. One of the methods includes training a cumbersome machine learning model, wherein the cumbersome machine learning model is configured to receive an input and generate a respective score for each of a plurality of classes; and training a distilled machine learning model on a plurality of training inputs, wherein the distilled machine learning model is also configured to receive inputs and generate scores for the plurality of classes, comprising: processing each training input using the cumbersome machine learning model to generate a cumbersome target soft output for the training input; and training the distilled machine learning model to, for each of the training inputs, generate a soft output that matches the cumbersome target soft output for the training input.
    Type: Application
    Filed: July 13, 2022
    Publication date: November 3, 2022
    Inventors: Oriol Vinyals, Jeffrey Adgate Dean, Geoffrey E. Hinton
  • Patent number: 11455514
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices includes receiving data specifying machine learning operations, and determining a placement that assigns each of the operations specified by the data to a respective device from the multiple hardware devices.
    Type: Grant
    Filed: August 28, 2019
    Date of Patent: September 27, 2022
    Assignee: Google LLC
    Inventors: Benoit Steiner, Anna Darling Goldie, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le
  • Patent number: 11423337
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a distilled machine learning model. One of the methods includes training a cumbersome machine learning model, wherein the cumbersome machine learning model is configured to receive an input and generate a respective score for each of a plurality of classes; and training a distilled machine learning model on a plurality of training inputs, wherein the distilled machine learning model is also configured to receive inputs and generate scores for the plurality of classes, comprising: processing each training input using the cumbersome machine learning model to generate a cumbersome target soft output for the training input; and training the distilled machine learning model to, for each of the training inputs, generate a soft output that matches the cumbersome target soft output for the training input.
    Type: Grant
    Filed: April 7, 2020
    Date of Patent: August 23, 2022
    Assignee: Google LLC
    Inventors: Oriol Vinyals, Jeffrey Adgate Dean, Geoffrey E. Hinton
  • Publication number: 20220222219
    Abstract: A method of accessing data includes storing a table that includes a plurality of tablets corresponding to distinct non-overlapping table portions. Respective pluralities of tablet access objects and application objects are stored in a plurality of servers. A distinct application object and distinct tablet are associated with each tablet access object. Each application object corresponds to a distinct instantiation of an application associated with the table. The tablet access objects and associated application objects are redistributed among the servers in accordance with a first load-balancing criterion. A first request directed to a respective tablet is received from a client. In response, the tablet access object associated with the respective tablet is used to perform a data access operation on the respective tablet, and the application object associated with the respective tablet is used to perform an additional computational operation to produce a result to be returned to the client.
    Type: Application
    Filed: February 14, 2022
    Publication date: July 14, 2022
    Inventors: Jeffrey Adgate Dean, Sanjay Ghemawat, Andrew Fikes, Yasushi Saito
  • Patent number: 11367112
    Abstract: The usefulness of content (target content), such as advertisements, may be increased by determining additional content and providing such additional content in association with the content. The target content may be text, a Web page, a URL, a search query, etc. The additional content might be related suggested queries (e.g. “Try a search for ______”), news articles (or excerpts or summaries thereof), reviews (or excerpts or summaries thereof), advertisements, user group messages, etc.
    Type: Grant
    Filed: January 15, 2020
    Date of Patent: June 21, 2022
    Assignee: Google LLC
    Inventors: Jeffrey Adgate Dean, Krishna Bharat, Paul Buchheit
  • Publication number: 20220108058
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Application
    Filed: December 17, 2021
    Publication date: April 7, 2022
    Inventors: Anna Darling Goldie, Azalia Mirhoseini, Ebrahim Songhori, Wenjie Jiang, Shen Wang, Roger David Carpenter, Young-Joon Lee, Mustafa Nazim Yazgan, Chian-min Richard Ho, Quoc V. Le, James Laudon, Jeffrey Adgate Dean, Kavya Srinivasa Setty, Omkar Pathak
  • Publication number: 20220043951
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip floorplan. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip floorplan, comprising placing a respective node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Application
    Filed: August 23, 2021
    Publication date: February 10, 2022
    Inventors: Chian-min Richard Ho, William Hang, Mustafa Nazim Yazgan, Anna Darling Goldie, Jeffrey Adgate Dean, Azalia Mirhoseini, Emre Tuncer, Ya Wang, Anand Babu
  • Publication number: 20220019896
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for modifying a computational graph to include send and receive nodes. Communication between unique devices performing operations of different subgraphs of the computational graph can be handled efficiently by inserting send and receive nodes into each subgraph. When executed, the operations that these send and receive nodes represent may enable pairs of unique devices to conduct communication with each other in a self-sufficient manner. This shifts the burden of coordinating communication away from the backend, which affords the system that processes this computational graph representation the opportunity to perform one or more other processes while devices are executing subgraphs.
    Type: Application
    Filed: August 3, 2021
    Publication date: January 20, 2022
    Inventors: Vijay Vasudevan, Jeffrey Adgate Dean, Sanjay Ghemawat
  • Patent number: 11216609
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Grant
    Filed: April 22, 2021
    Date of Patent: January 4, 2022
    Assignee: Google LLC
    Inventors: Anna Darling Goldie, Azalia Mirhoseini, Ebrahim Songhori, Wenjie Jiang, Shen Wang, Roger David Carpenter, Young-Joon Lee, Mustafa Nazim Yazgan, Chian-Min Richard Ho, Quoc V. Le, James Laudon, Jeffrey Adgate Dean, Kavya Srinivasa Setty, Omkar Pathak
  • Publication number: 20210334445
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip placement. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip placement, comprising placing a respective macro node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the macro node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Application
    Filed: April 22, 2021
    Publication date: October 28, 2021
    Inventors: Anna Darling Goldie, Azalia Mirhoseini, Ebrahim Songhori, Wenjie Jiang, Shen Wang, Roger David Carpenter, Young-Joon Lee, Mustafa Nazim Yazgan, Chian-min Richard Ho, Quoc V. Le, James Laudon, Jeffrey Adgate Dean, Kavya Srinivasa Setty, Omkar Pathak
  • Publication number: 20210311909
    Abstract: A method for deleting obsolete files from a file system is provided. The method includes receiving a request to delete a reference to a first target file of a plurality of target files stored in a file system, the first target file having a first target file name. A first reference file whose file name includes the first target file name is identified. The first reference file is deleted from the file system. The method further includes determining whether the file system includes at least one reference file, distinct from the first reference file, whose file name includes the first target file name. In accordance with a determination that the file system does not include the at least one reference file, the first target file is deleted from the file system.
    Type: Application
    Filed: June 17, 2021
    Publication date: October 7, 2021
    Inventors: Yasushi Saito, Sanjay Ghemawat, Jeffrey Adgate Dean
  • Patent number: 11100266
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip floorplan. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip floorplan, comprising placing a respective node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Grant
    Filed: June 1, 2020
    Date of Patent: August 24, 2021
    Assignee: Google LLC
    Inventors: Chian-min Richard Ho, William Hang, Mustafa Nazim Yazgan, Anna Darling Goldie, Jeffrey Adgate Dean, Azalia Mirhoseini, Emre Tuncer, Ya Wang, Anand Babu
  • Patent number: 11087216
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for modifying a computational graph to include send and receive nodes. Communication between unique devices performing operations of different subgraphs of the computational graph can be handled efficiently by inserting send and receive nodes into each subgraph. When executed, the operations that these send and receive nodes represent may enable pairs of unique devices to conduct communication with each other in a self-sufficient manner. This shifts the burden of coordinating communication away from the backend, which affords the system that processes this computational graph representation the opportunity to perform one or more other processes while devices are executing subgraphs.
    Type: Grant
    Filed: September 9, 2020
    Date of Patent: August 10, 2021
    Assignee: Google LLC
    Inventors: Vijay Vasudevan, Jeffrey Adgate Dean, Sanjay Ghemawat
  • Patent number: 10991005
    Abstract: The relevance of advertisements to a user's interests is improved. In one implementation, the content of a web page is analyzed to determine a list of one or more topics associated with that web page. An advertisement is considered to be relevant to that web page if it is associated with keywords belonging to the list of one or more topics. One or more of these relevant advertisements may be provided for rendering in conjunction with the web page or related web pages.
    Type: Grant
    Filed: January 28, 2019
    Date of Patent: April 27, 2021
    Assignee: Google LLC
    Inventors: Jeffrey Adgate Dean, Georges Harik, Paul Buchheit
  • Patent number: 10949881
    Abstract: Targeting information (also referred to as ad “serving constraints”) or candidate targeting information for an advertisement is identified. Targeting information may be identified by extracting topics or concepts from, and/or generating topics or concepts based on, ad information, such as information from a Web page to which an ad is linked (or some other Web page of interest to the ad or advertiser). The topics or concepts may be relevant queries associated with the Web page of interest, clusters, etc.
    Type: Grant
    Filed: April 4, 2017
    Date of Patent: March 16, 2021
    Assignee: Google LLC
    Inventors: Jeffrey Adgate Dean, Georges Harik, Paul Buchheit
  • Publication number: 20210019604
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting likelihoods of conditions being satisfied using recurrent neural networks. One of the systems is configured to process a temporal sequence comprising a respective input at each of a plurality of time steps and comprises: one or more recurrent neural network layers; one or more logistic regression nodes, wherein each of the logistic regression nodes corresponds to a respective condition from a predetermined set of conditions, and wherein each of the logistic regression nodes is configured to, for each of the plurality of time steps: receive the network internal state for the time step; and process the network internal state for the time step in accordance with current values of a set of parameters of the logistic regression node to generate a future condition score for the corresponding condition for the time step.
    Type: Application
    Filed: July 27, 2020
    Publication date: January 21, 2021
    Inventors: Gregory Sean Corrado, Ilya Sutskever, Jeffrey Adgate Dean
  • Publication number: 20200401897
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for modifying a computational graph to include send and receive nodes. Communication between unique devices performing operations of different subgraphs of the computational graph can be handled efficiently by inserting send and receive nodes into each subgraph. When executed, the operations that these send and receive nodes represent may enable pairs of unique devices to conduct communication with each other in a self-sufficient manner. This shifts the burden of coordinating communication away from the backend, which affords the system that processes this computational graph representation the opportunity to perform one or more other processes while devices are executing subgraphs.
    Type: Application
    Filed: September 9, 2020
    Publication date: December 24, 2020
    Inventors: Vijay Vasudevan, Jeffrey Adgate Dean, Sanjay Ghemawat
  • Patent number: 10860925
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving a request from a client to process a computational graph; obtaining data representing the computational graph, the computational graph comprising a plurality of nodes and directed edges, wherein each node represents a respective operation, wherein each directed edge connects a respective first node to a respective second node that represents an operation that receives, as input, an output of an operation represented by the respective first node; identifying a plurality of available devices for performing the requested operation; partitioning the computational graph into a plurality of subgraphs, each subgraph comprising one or more nodes in the computational graph; and assigning, for each subgraph, the operations represented by the one or more nodes in the subgraph to a respective available device in the plurality of available devices for operation.
    Type: Grant
    Filed: October 28, 2016
    Date of Patent: December 8, 2020
    Assignee: Google LLC
    Inventors: Paul A. Tucker, Jeffrey Adgate Dean, Sanjay Ghemawat, Yuan Yu
  • Publication number: 20200380023
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes obtaining data that associates each term in a vocabulary of terms with a respective high-dimensional representation of the term; obtaining classification data for a data object, wherein the classification data includes a respective score for each of a plurality of categories, and wherein each of the categories is associated with a respective category label; computing an aggregate high-dimensional representation for the data object from high-dimensional representations for the category labels associated with the categories and the respective scores; identifying a first term in the vocabulary of terms having a high-dimensional representation that is closest to the aggregate high-dimensional representation; and selecting the first term as a category label for the data object.
    Type: Application
    Filed: August 20, 2020
    Publication date: December 3, 2020
    Inventors: Gregory Sean Corrado, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea L. Frome, Jeffrey Adgate Dean, Mohammad Norouzi
  • Publication number: 20200364389
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a computer chip floorplan. One of the methods includes obtaining netlist data for a computer chip; and generating a computer chip floorplan, comprising placing a respective node at each time step in a sequence comprising a plurality of time steps, the placing comprising, for each time step: generating an input representation for the time step; processing the input representation using a node placement neural network having a plurality of network parameters, wherein the node placement neural network is configured to process the input representation in accordance with current values of the network parameters to generate a score distribution over a plurality of positions on the surface of the computer chip; and assigning the node to be placed at the time step to a position from the plurality of positions using the score distribution.
    Type: Application
    Filed: June 1, 2020
    Publication date: November 19, 2020
    Inventors: Chian-min Richard Ho, William Hang, Mustafa Nazim Yazgan, Anna Darling Goldie, Jeffrey Adgate Dean, Azalia Mirhoseini, Emre Tuncer, Ya Wang, Anand Babu