Patents by Inventor Geoffrey Irving

Geoffrey Irving 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: 20240152740
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of receiving a request to perform computations for a neural network on a hardware circuit having a matrix computation unit, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions that when executed by the hardware circuit cause the hardware circuit to transpose the first neural network matrix by performing first operations, wherein the first operations include repeatedly performing the following second operations: for a current subdivision of the first neural network matrix that divides the first neural network matrix into one or more current submatrices, updating the first neural network matrix by swapping an upper right quadrant and a lower left quadrant of each current submatrix, and subdividing each current submatrix into respective new submatrices to update the current subdivision.
    Type: Application
    Filed: June 5, 2023
    Publication date: May 9, 2024
    Inventors: Reginald Clifford Young, Geoffrey Irving
  • Publication number: 20240104336
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enabling a user to conduct a dialogue. Implementations of the system learn when to rely on supporting evidence, obtained from an external search system via a search system interface, and are also able to generate replies for the user that align with the preferences of a previously trained response selection neural network. Implementations of the system can also use a previously trained rule violation detection neural network to generate replies that take account of previously learnt rules.
    Type: Application
    Filed: September 20, 2023
    Publication date: March 28, 2024
    Inventors: Geoffrey Irving, Amelia Marita Claudia Glaese, Nathaniel John McAleese-Park, Lisa Anne Marie Hendricks
  • Publication number: 20230237826
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adjusting a target neural network using automatically generated test cases before deployment of the target neural network in a deployment environment. One of the methods may include generating a plurality of test inputs by using a test case generation neural network; processing the plurality of test inputs using a target neural network to generate one or more test outputs for each test input; and identifying, from the one or more test outputs generated by the target neural network for each test input, failing test inputs that result in generation of test outputs by the target neural network that fail one or more criteria.
    Type: Application
    Filed: January 27, 2023
    Publication date: July 27, 2023
    Inventors: Ethan Josean Perez, Saffron Shan Huang, Nathaniel John McAleese-Park, Geoffrey Irving
  • Patent number: 11704547
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of receiving a request to perform computations for a neural network on a hardware circuit having a matrix computation unit, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions that when executed by the hardware circuit cause the hardware circuit to transpose the first neural network matrix by performing first operations, wherein the first operations include repeatedly performing the following second operations: for a current subdivision of the first neural network matrix that divides the first neural network matrix into one or more current submatrices, updating the first neural network matrix by swapping an upper right quadrant and a lower left quadrant of each current submatrix, and subdividing each current submatrix into respective new submatrices to update the current subdivision.
    Type: Grant
    Filed: January 29, 2021
    Date of Patent: July 18, 2023
    Assignee: Google LLC
    Inventors: Reginald Clifford Young, Geoffrey Irving
  • Patent number: 11203157
    Abstract: Embodiments disclosed herein provide systems and methods for preparing geometry for 3D printing. In one embodiment, a 3D printing preparation application receives 3D geometry and repairs non-manifold edges and non-manifold vertices, producing a topological manifold geometry. The 3D printing preparation application then welds coincident edges without coincident faces and fills holes in the geometry. The 3D printing preparation application may further perform resolution-aware thickening of the geometry by estimating distances to a medial axis based on distances to distance field shocks, and advecting the distance field using a velocity field. A similar approach may be used to perform resolution-aware separation enforcement. Alternatively, one component may be globally thickened and subtracted from another for separation enforcement. The 3D printing preparation application may also split large models and add connectors for connecting the split pieces after printing.
    Type: Grant
    Filed: April 2, 2019
    Date of Patent: December 21, 2021
    Assignee: AUTODESK, INC.
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Sam Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Publication number: 20210224641
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of receiving a request to perform computations for a neural network on a hardware circuit having a matrix computation unit, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions that when executed by the hardware circuit cause the hardware circuit to transpose the first neural network matrix by performing first operations, wherein the first operations include repeatedly performing the following second operations: for a current subdivision of the first neural network matrix that divides the first neural network matrix into one or more current submatrices, updating the first neural network matrix by swapping an upper right quadrant and a lower left quadrant of each current submatrix, and subdividing each current submatrix into respective new submatrices to update the current subdivision.
    Type: Application
    Filed: January 29, 2021
    Publication date: July 22, 2021
    Inventors: Reginald Clifford Young, Geoffrey Irving
  • Patent number: 10909447
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of receiving a request to perform computations for a neural network on a hardware circuit having a matrix computation unit, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions that when executed by the hardware circuit cause the hardware circuit to transpose the first neural network matrix by performing first operations, wherein the first operations include repeatedly performing the following second operations: for a current subdivision of the first neural network matrix that divides the first neural network matrix into one or more current submatrices, updating the first neural network matrix by swapping an upper right quadrant and a lower left quadrant of each current submatrix, and subdividing each current submatrix into respective new submatrices to update the current subdivision.
    Type: Grant
    Filed: March 9, 2017
    Date of Patent: February 2, 2021
    Assignee: Google LLC
    Inventors: Reginald Clifford Young, Geoffrey Irving
  • Patent number: 10783289
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Grant
    Filed: September 15, 2017
    Date of Patent: September 22, 2020
    Assignee: AUTODESK, INC.
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Samuel Eli Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Publication number: 20190228114
    Abstract: Embodiments disclosed herein provide systems and methods for preparing geometry for 3D printing. In one embodiment, a 3D printing preparation application receives 3D geometry and repairs non-manifold edges and non-manifold vertices, producing a topological manifold geometry. The 3D printing preparation application then welds coincident edges without coincident faces and fills holes in the geometry. The 3D printing preparation application may further perform resolution-aware thickening of the geometry by estimating distances to a medial axis based on distances to distance field shocks, and advecting the distance field using a velocity field. A similar approach may be used to perform resolution-aware separation enforcement. Alternatively, one component may be globally thickened and subtracted from another for separation enforcement. The 3D printing preparation application may also split large models and add connectors for connecting the split pieces after printing.
    Type: Application
    Filed: April 2, 2019
    Publication date: July 25, 2019
    Inventors: Saul GRIFFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Sam CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Patent number: 10248740
    Abstract: Embodiments disclosed herein provide systems and methods for preparing geometry for 3D printing. In one embodiment, a 3D printing preparation application receives 3D geometry and repairs non-manifold edges and non-manifold vertices, producing a topological manifold geometry. The 3D printing preparation application then welds coincident edges without coincident faces and fills holes in the geometry. The 3D printing preparation application may further perform resolution-aware thickening of the geometry by estimating distances to a medial axis based on distances to distance field shocks, and advecting the distance field using a velocity field. A similar approach may be used to perform resolution-aware separation enforcement. Alternatively, one component may be globally thickened and subtracted from another for separation enforcement. The 3D printing preparation application may also split large models and add connectors for connecting the split pieces after printing.
    Type: Grant
    Filed: April 9, 2013
    Date of Patent: April 2, 2019
    Assignee: AUTODESK, INC.
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Sam Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Publication number: 20180260690
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of receiving a request to perform computations for a neural network on a hardware circuit having a matrix computation unit, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions that when executed by the hardware circuit cause the hardware circuit to transpose the first neural network matrix by performing first operations, wherein the first operations include repeatedly performing the following second operations: for a current subdivision of the first neural network matrix that divides the first neural network matrix into one or more current submatrices, updating the first neural network matrix by swapping an upper right quadrant and a lower left quadrant of each current submatrix, and subdividing each current submatrix into respective new submatrices to update the current subdivision.
    Type: Application
    Filed: March 9, 2017
    Publication date: September 13, 2018
    Applicant: Google Inc.
    Inventors: Reginald Clifford Young, Geoffrey Irving
  • Publication number: 20180004871
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Application
    Filed: September 15, 2017
    Publication date: January 4, 2018
    Inventors: Saul GRIFFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Samuel Eli CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Patent number: 9767233
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Grant
    Filed: November 14, 2016
    Date of Patent: September 19, 2017
    Assignee: AUTODESK, INC.
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Samuel Eli Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Patent number: 9619587
    Abstract: Embodiments disclosed herein provide techniques for decomposing 3D geometry into developable surface patches and cut patterns. In one embodiment, a decomposition application receives a triangulated 3D surface as input and determines approximately developable surface patches from the 3D surface using a variant of k-means clustering. Such approximately developable surface patches may have undesirable jagged boundaries, which the decomposition application may eliminate by generating a data structure separate from the mesh that contains patch boundaries and optimizing the patch boundaries or, alternatively, remeshing the mesh such that patch boundaries fall on mesh edges. The decomposition application may then flatten the patches into truly developable surfaces by re-triangulating the patches as ruled surfaces. The decomposition application may further flatten the ruled surfaces into 2D shapes and lay those shapes out on virtual sheets of material.
    Type: Grant
    Filed: April 9, 2013
    Date of Patent: April 11, 2017
    Assignee: AUTODESK, INC.
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Sam Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Publication number: 20170061051
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Application
    Filed: November 14, 2016
    Publication date: March 2, 2017
    Inventors: Saul GRIFFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Samuel Eli CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Patent number: 9495484
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Grant
    Filed: September 17, 2013
    Date of Patent: November 15, 2016
    Assignee: AUTODESK, LLP
    Inventors: Saul Griffith, Martin Wicke, Keith Pasko, Geoffrey Irving, Samuel Eli Calisch, Tucker Gilman, Daniel Benoit, Jonathan Bachrach
  • Publication number: 20140081603
    Abstract: Embodiments of the invention provide systems and methods for nesting objects in 2D sheets and 3D volumes. In one embodiment, a nesting application simplifies the shapes of parts and performs a rigid body simulation of the parts dropping into a 2D sheet or 3D volume. In the rigid body simulation, parts begin from random initial positions on one or more sides and drop under the force of gravity into the 2D sheet or 3D volume until coming into contact with another part, a boundary, or the origin of the gravity. The parts may be dropped according to a particular order, such as alternating large and small parts. Further, the simulation may be translation- and/or position-only, meaning the parts do not rotate and/or do not have momentum, respectively. Tighter packing may be achieved by incorporating user inputs and simulating jittering of the parts using random forces.
    Type: Application
    Filed: September 17, 2013
    Publication date: March 20, 2014
    Applicant: AUTODESK, Inc.
    Inventors: Saul GRIFFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Samuel Eli CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Publication number: 20130297058
    Abstract: Embodiments disclosed herein provide techniques for decomposing 3D geometry into developable surface patches and cut patterns. In one embodiment, a decomposition application receives a triangulated 3D surface as input and determines approximately developable surface patches from the 3D surface using a variant of k-means clustering. Such approximately developable surface patches may have undesirable jagged boundaries, which the decomposition application may eliminate by generating a data structure separate from the mesh that contains patch boundaries and optimizing the patch boundaries or, alternatively, remeshing the mesh such that patch boundaries fall on mesh edges. The decomposition application may then flatten the patches into truly developable surfaces by re-triangulating the patches as ruled surfaces. The decomposition application may further flatten the ruled surfaces into 2D shapes and lay those shapes out on virtual sheets of material.
    Type: Application
    Filed: April 9, 2013
    Publication date: November 7, 2013
    Inventors: Saul GRIFFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Sam CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Publication number: 20130297059
    Abstract: Embodiments disclosed herein provide systems and methods for preparing geometry for 3D printing. In one embodiment, a 3D printing preparation application receives 3D geometry and repairs non-manifold edges and non-manifold vertices, producing a topological manifold geometry. The 3D printing preparation application then welds coincident edges without coincident faces and fills holes in the geometry. The 3D printing preparation application may further perform resolution-aware thickening of the geometry by estimating distances to a medial axis based on distances to distance field shocks, and advecting the distance field using a velocity field. A similar approach may be used to perform resolution-aware separation enforcement. Alternatively, one component may be globally thickened and subtracted from another for separation enforcement. The 3D printing preparation application may also split large models and add connectors for connecting the split pieces after printing.
    Type: Application
    Filed: April 9, 2013
    Publication date: November 7, 2013
    Inventors: Saul GRIFITH, Martin WICKE, Keith PASKO, Geoffrey IRVING, Sam CALISCH, Tucker GILMAN, Daniel BENOIT, Jonathan BACHRACH
  • Patent number: 8290757
    Abstract: Systems and methods for simulating ballistic motion on an animated object by continuously defining rest poses of the animation object in a motion simulator. Tetrahedral finite element simulation may be used with control mechanisms that target the simulation pose towards the animation. A simulation mesh is generated for two or more animated poses based on a first simulation mesh corresponding to a first pose of the animated object. The simulation meshes of the two or more animated poses are provided to a simulator for use by the simulator such that in the absence of external force and acceleration the simulator output approximates the animated poses. Embodiments of the present invention are particularly useful for fleshy, blobby animation objects such as human characters, although the techniques can be used for other objects having different characteristics.
    Type: Grant
    Filed: December 5, 2008
    Date of Patent: October 16, 2012
    Assignee: Pixar
    Inventors: Geoffrey Irving, Ryan Kautzman, Gordon Cameron, Jiayi Chong