Google LLC patent applications on June 13th, 2024
Patent Applications by Google LLC on June 13th, 2024
Google LLC: 56 patent applications
Google LLC has applied for patents in the areas of G06N20/00 (8), G10L15/08 (3), B25J9/16 (2), G06F40/35 (2), H01L23/00 (2) G06N20/00 (2), B25J9/163 (1), H02J9/062 (1), G06V10/82 (1), G06V40/1318 (1)
With keywords such as: device, data, user, based, input, content, image, include, determining, and respective in patent application abstracts.
Patent Applications by Google LLC
Inventor(s): Keerthana P G of San Francisco CA (US) for google llc, Karol Hausman of San Francisco CA (US) for google llc, Julian Ibarz of Sunnyvale CA (US) for google llc, Brian Ichter of Brooklyn NY (US) for google llc, Alexander Irpan of Palo Alto CA (US) for google llc, Dmitry Kalashnikov of Fair Lawn NJ (US) for google llc, Yao Lu of Palo Alto CA (US) for google llc, Kanury Kanishka Rao of Santa Clara CA (US) for google llc, Michael Sahngwon Ryoo of Mountain View CA (US) for google llc, Austin Charles Stone of San Francisco CA (US) for google llc, Teddey Ming Xiao of Mountain View CA (US) for google llc, Quan Ho Vuong of Palo Alto CA (US) for google llc, Sumedh Anand Sontakke of Los Angeles CA (US) for google llc
IPC Code(s): B25J9/16
CPC Code(s): B25J9/163
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling an agent interacting with an environment. in one aspect, a method comprises: receiving a natural language text sequence that characterizes a task to be performed by the agent in the environment; generating an encoded representation of the natural language text sequence; and at each of a plurality of time steps: obtaining an observation image characterizing a state of the environment at the time step; processing the observation image to generate an encoded representation of the observation image; generating a sequence of input tokens; processing the sequence of input tokens to generate a policy output that defines an action to be performed by the agent in response to the observation image; selecting an action to be performed by the agent using the policy output; and causing the agent to perform the selected action.
20240190004.SIMULATION DRIVEN ROBOTIC CONTROL OF REAL ROBOT(S)_simplified_abstract_(google llc)
Inventor(s): Yunfei Bai of Fremont CA (US) for google llc, Tigran Gasparian of Munich (DE) for google llc, Brent Austin of Munich (DE) for google llc, Andreas Christiansen of Lengdorf (DE) for google llc, Matthew Bennice of San Jose CA (US) for google llc, Paul Bechard of Ogdensburg NY (US) for google llc
IPC Code(s): B25J9/16
CPC Code(s): B25J9/1671
Abstract: active utilization of a robotic simulator in control of one or more real world robots. a simulated environment of the robotic simulator can be configured to reflect a real world environment in which a real robot is currently disposed, or will be disposed. the robotic simulator can then be used to determine a sequence of robotic actions for use by the real world robot(s) in performing at least part of a robotic task. the sequence of robotic actions can be applied, to a simulated robot of the robotic simulator, to generate a sequence of anticipated simulated state data instances. the real robot can be controlled to implement the sequence of robotic actions. the implementation of one or more of the robotic actions can be contingent on a real state data instance having at least a threshold degree of similarity to a corresponding one of the anticipated simulated state data instances.
Inventor(s): Lu Tian of Palo Alto CA (US) for google llc, Wei Jin of Saratoga CA (US) for google llc, Joseph Daniel Lowney of Tucson AZ (US) for google llc, Thomas Mercier of Weston FL (US) for google llc
IPC Code(s): G03F7/20, G03F1/70
CPC Code(s): G03F7/70216
Abstract: systems and methods are provided for generating a two-dimensional pattern on a photoresist layer. a photoresist layer is exposed via a first exposure to a first unidimensional series of features alternatingly providing first minima and maxima of illumination intensity along a first dimension. the photoresist layer is then exposed via a second exposure to a second unidimensional series of features alternatingly providing second minima and maxima of illumination intensity along a second dimension that is angularly separated from the second dimension by an exposure rotation factor.
20240192734.DISPLAY ASSISTANT DEVICE_simplified_abstract_(google llc)
Inventor(s): James Castro of San Jose CA (US) for google llc, Marc Davidson of Sunnyvale CA (US) for google llc, Chih-Min Chien of Taipei City (TW) for google llc, Daniel Corbalan of San Francisco CA (US) for google llc, Carl Cepress of Los Altos CA (US) for google llc, Liang Ching Tseng of Taipei City (TW) for google llc
IPC Code(s): G06F1/16, G02F1/1333, G02F1/1337, G06F3/16, G06F21/83, G10L15/28, H04L12/28, H04R1/02, H04R1/34
CPC Code(s): G06F1/166
Abstract: this application is directed to a display assistant device that acts as a voice-activated user interface device. the display assistant device includes a base, a screen and a speaker. the base is configured for sitting on a surface. the screen has a rear surface and is supported by the base at the rear surface. a bottom edge of the screen is configured to be held above the surface by a predefined height, and the base is substantially hidden behind the screen from a front view of the display assistant device. the speaker is concealed inside the base and configured to project sound substantially towards the front view of the display assistant device.
Inventor(s): Shumin Zhai of Los Altos CA (US) for google llc, Scott Jenson of Palo Alto CA (US) for google llc, Hong Z. Tan of Lafayette IN (US) for google llc
IPC Code(s): G06F3/01
CPC Code(s): G06F3/016
Abstract: a computing device may determine a haptic effect to be produced by a haptic device of the computing device. the computing device may select, based at least in part on the haptic effect, a modulation frequency. the computing device may determine a combination of a carrier frequency and the modulation frequency to produce the haptic effect. the computing device may drive the haptic device according to the combination of the carrier frequency and the modulation frequency to output a vibration pattern associated with the haptic effect.
Inventor(s): Dongeek Shin of San Jose CA (US) for google llc
IPC Code(s): G06F3/043, G06F1/16, G10L15/22, G10L21/0208
CPC Code(s): G06F3/043
Abstract: implementations set forth herein relate to facilitating control of an automated assistant or other application by rendering an ultrasonic signal that can be modulation through tactile interaction with physical portions of a computing device. the computing device can provide an acoustic signal via a speaker of the computing device, and the acoustic signal can be received by one or more microphones of the computing device. during transmission, a portion of the acoustic signal can travel through a housing of the computing device, which the user can tap or otherwise use to provide a gesture. audio data generated using the microphone can reflect changes to the acoustic signal, and those changes can be indicative of a particular gesture received at the housing. when a particular gesture is detected, the automated assistant or other application can respond to the gesture by initiating one or more particular operations.
Inventor(s): Christopher Charles Burns of Santa Clara CA (US) for google llc, George Alban Heitz, III of Mountain View CA (US) for google llc, James Edward Stewart of Mountain View CA (US) for google llc, Cameron Hill of San Francisco CA (US) for google llc, Seungho Yang of Mountain View CA (US) for google llc, Joe Delone Venters of Alameda CA (US) for google llc, William Alex Finlayson of San Francisco CA (US) for google llc, Carsten Hinz of Sunnyvale CA (US) for google llc, Timothy Samuel Psiaki of Duvall WA (US) for google llc, Nathan Scott Klee of Kirkland WA (US) for google llc, Gregory Rourk Nelson of San Bruno CA (US) for google llc, Kevin James Avery of San Francisco CA (US) for google llc, Lawrence W. Neal of Oakland CA (US) for google llc, Martin Davidsson of Redwood City CA (US) for google llc
IPC Code(s): G06F3/0482, G05B15/02, G06F3/04817, G06F16/738, G06F40/35, G11B27/30, H04L65/403, H04L65/61, H04N7/18, H04N21/2387, H04N21/4223, H04N21/431, H04N21/472, H04N21/488, H04N21/63, H04N21/845, H04N21/8549, H04N21/858
CPC Code(s): G06F3/0482
Abstract: a method at an electronic device with a display includes: displaying a user interface having a first region and a second region; receiving, and displaying in the first region of the user interface, a live video stream of a physical environment captured by a remote video camera; displaying, in the second region, a timeline corresponding to a timespan for a first portion of a duration during which the live video stream may have been recorded; in response to receiving a user interaction to move the timespan to a second portion of the duration, transitioning the displayed timeline to a new timeline that corresponds to the timespan for the second portion, and while transitioning, displaying, in the first region, a subset of video frames representing the first and/or second portion of the duration.
20240192842.Rate-Adaptive Content Container_simplified_abstract_(google llc)
Inventor(s): Ramprasad Sedouram of Bangalore (IN) for google llc, Safia Ali of Lahore (PK) for google llc, Shailly Kishtawal of Bangalore (IN) for google llc, Merlyn Fraga Francis Xavier of Bengaluru (IN) for google llc, Bhavinee Vyas of Bengaluru (IN) for google llc, Jaunani Sriramachandran of Chennai (IN) for google llc, Manasi Rajan Kothari of Bengaluru (IN) for google llc, Apoorv Gupta of Lucknow (IN) for google llc
IPC Code(s): G06F3/0485, G06F3/0481, H04N23/695
CPC Code(s): G06F3/0485
Abstract: embodiments according to examples aspects of the present disclosure provide for an example computer-implemented method. the example method can include obtaining a data structure configured for rendering a plurality of content containers on a user device, the plurality of content containers providing a collapsed configuration and an expanded configuration. the example method can include rendering, based on a first rate parameter descriptive of a user input associated with the user device, one or more of the plurality of content containers according to the collapsed configuration. the example method can include rendering, based on a second rate parameter, at least one of the plurality of content containers according to the expanded configuration.
Inventor(s): Oliver Deiss of Mountain View CA (US) for google llc, Grigory Borisovich Lyakhovitskiy of Redmond WA (US) for google llc, Dan Kimmel of Mountain View CA (US) for google llc
IPC Code(s): G06F3/06
CPC Code(s): G06F3/0608
Abstract: a method for garbage-collection includes obtaining a request to compact a plurality of log files of a log-structured volume. each log file includes fresh block runs in use and stale block runs no longer in use. the log-structured volume includes a plurality of snapshots. for each respective snapshot, the method includes determining, using a plurality of interval maps, the fresh block runs of the plurality of log files used by the respective snapshot. for each respective log file, the method includes writing the fresh block runs of the respective log file to a respective compacted log file and generating a respective per-log diff file. the method includes, for each respective snapshot, generating a respective checkpoint based on respective per-log diff files and deleting each respective log file of the plurality of log files.
Inventor(s): Lukasz Lew of Sunnyvale CA (US) for google llc, Wren Romano of Mountain View CA (US) for google llc
IPC Code(s): G06F3/06, G06F9/50, G06N20/00
CPC Code(s): G06F3/0679
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for scheduling operations on a machine-learning accelerator having multiple tiles. the apparatus includes a processor having a plurality of tiles and scheduling circuitry that is configured to select a respective input activation for each tile of the plurality of tiles from either an activation line for the tile or a delay register for the activation line.
Inventor(s): Justin Santa Barbara of Atlanta GA (US) for google llc, Brian Grant of Mountain View CA (US) for google llc, Martin Maly of Mountain View CA (US) for google llc
IPC Code(s): G06F9/50, G06F8/65, G06F8/71
CPC Code(s): G06F9/5055
Abstract: operations of a method include receiving a configuration request requesting configuration management of a base configuration package that describes infrastructure of an application. the operations include determining, for the base configuration package, a plurality of package functions. each package function of the plurality of package functions extends functionality of the base configuration package. the operations include determining, for the base configuration package and the plurality of package functions, a change-proposal function. the change-proposal function proposes one or more of the plurality of package functions to extend the functionality of the base configuration package. the operations include transmitting, to a user device, the change-proposal function and receiving, from the user device, approval of the change-proposal function. in response to receiving approval of the change-proposal function, the operations include configuring the base configuration package using the one or more of the plurality of package functions proposed by the change-proposal function.
20240193035.Point Anomaly Detection_simplified_abstract_(google llc)
Inventor(s): Zichuan Ye of Mountain View CA (US) for google llc, Jiashang Liu of Kirkland WA (US) for google llc, Forest Elliott of Mountain View CA (US) for google llc, Amir Hormati of Mountain View CA (US) for google llc, Xi Cheng of Kirkland WA (US) for google llc, Mingge Deng of Kirkland WA (US) for google llc
IPC Code(s): G06F11/07
CPC Code(s): G06F11/0793
Abstract: a method includes receiving a point data anomaly detection query from a user. the query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. the method includes training a model using the set of point data values. for at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. based on the variance value satisfying the threshold value, the method includes determining that the respective point data value includes an anomalous point data value. the method includes reporting the determined anomalous point data value to the user.
20240193057.AUTOMATED TESTING OF DIGITAL KEYS FOR VEHICLES_simplified_abstract_(google llc)
Inventor(s): Adam M. Bar-Niv of Los Altos CA (US) for google llc
IPC Code(s): G06F11/27
CPC Code(s): G06F11/27
Abstract: a method of testing a digital key is described that provides, from a digital key test manager device, standard digital key instructions for a computing device to send messages to a device under test; communicates, from the digital key test manager device, with the device under test to determine operations of the device under test as a result of the messages; and evaluates, at the digital key test manager device, the operations of the device under test to assess functionality of the digital key.
20240193093.Packet Cache System and Method_simplified_abstract_(google llc)
Inventor(s): Jiazhen Zheng of Santa Clara CA (US) for google llc, Srinivas Vaduvatha of San Jose CA (US) for google llc, Hugh McEvoy Walsh of Los Gatos CA (US) for google llc, Prashant R. Chandra of San Jose CA (US) for google llc, Abhishek Agarwal of Santa Clara CA (US) for google llc, Weihuang Wang of Los Gatos CA (US) for google llc, Weiwei Jiang of Santa Clara CA (US) for google llc
IPC Code(s): G06F12/0895, G06F12/0864, G06F12/121
CPC Code(s): G06F12/0895
Abstract: a packet cache system includes a cache memory allocator for receiving a memory address corresponding to a non-cache memory and allocated to a packet, and associating the memory address with a cache memory address; a hash table for storing the memory address and the cache memory address, with the memory address as a key and the cache memory address as a value; a cache memory for storing the packet at a location indicated by the cache memory address; and an eviction engine for determining one or more cached packets to remove from the cache memory and place in the non-cache memory when occupancy of the cache memory is high.
20240193141.Parameter-Based Versioning For Log-Based Block Devices_simplified_abstract_(google llc)
Inventor(s): Sandeep Bhatia of Bothell WA (US) for google llc, Justyna Ilczuk of Dublin (IE) for google llc, Andrey Arkharov of Kirkland WA (US) for google llc, Anik Sarker of Dublin (IE) for google llc, Sergey Korostelev of Redmond WA (US) for google llc, Andrew Kadatch of Redmond WA (US) for google llc
IPC Code(s): G06F16/21, G06F16/23, G06F16/2457
CPC Code(s): G06F16/219
Abstract: data log-base logical block devices are used to control parameter-based versioning at a block-device level. memory in the block device stores data log indicating data and corresponding metadata, the metadata indicating a particular historical time. the block device may receive a request, such as a remote procedure call (rpc), for data from the logical block device, and identify data included in the data log having metadata that matches or satisfies a historical time parameter included in and extracted from the request.
Inventor(s): Justin Lewis of Marina del Rey CA (US) for google llc, Ruxandra Georigana Paun of Santa Monica CA (US) for google llc
IPC Code(s): G06F16/438, G06F16/638
CPC Code(s): G06F16/4387
Abstract: a method may include in response to a user request for a playlist, identifying a plurality of media items from the playlist, determining whether a media item from the playlist is available for a playback on a user device, in response to a determination that the media item is not available for the playback on the user device, causing the use device to play another media item, and in response to a determination that the media item is available for the playback on the user device, causing the user device to play the media item.
20240193219.GENERATING HIGH VISIBILITY SOCIAL ANNOTATIONS_simplified_abstract_(google llc)
Inventor(s): Justin Lewis of Marina del Rey CA (US) for google llc, Gavin James of Los Angeles CA (US) for google llc
IPC Code(s): G06F16/957, G06F16/955, G06Q50/00, H04L67/50
CPC Code(s): G06F16/9577
Abstract: systems and methods for generating social annotations for content that are capable of being seen by a broad audience are provided herein. a system can include a user identification component configured to identify a user that has potential for generating a valuable endorsement of a content item based at least in part on a sharing setting associated with a user. the system further includes an audience component configured to determine an audience associated with the user based at least in part on the sharing setting, a user selection component configured to select the user as a candidate user for generating the endorsement of the content item in response to a determination that a size of the audience exceeds a threshold, and a targeted content component configured to, in response to selection of the user, provide the content item to the user with a capability to endorse the content item.
20240193295.Scalable Dataset Sharing With Linked Datasets_simplified_abstract_(google llc)
Inventor(s): Thibaud Hottelier of Seattle WA (US) for google llc, Brian Lee Welcker of Seattle WA (US) for google llc, Jonah Tang Soon Yuen of Sunnyvale CA (US) for google llc, Neil Martin Devine of Santa Clara CA (US) for google llc
IPC Code(s): G06F21/62, G06F16/2458
CPC Code(s): G06F21/6227
Abstract: aspects of the disclosure relate to managing access to published data by different groups of users through linked datasets. a subscriber system generates a linked dataset that links the subscriber system to a source dataset published by a publisher system. the subscriber system queries the linked dataset. queries to the linked dataset are redirected to the source dataset. the subscriber system manages access control to the linked dataset instead of the publisher system managing access control for the subscriber system directly to the source dataset. the source dataset does not need to be copied to the subscriber system. from the perspective of the subscriber system, changes to the source dataset appear instantly, as subscribers may query the source dataset through the linked dataset without waiting for copies of the source dataset to propagate.
Inventor(s): Craig Douglas Voisin of Mississauga (CA) for google llc, Truc Duc Le of Kitchener (CA) for google llc, Marwan Elsayed Abdelaal Tammam Issa of Waterloo (CA) for google llc, Xiao Yang of Richmond Hill (CA) for google llc, Jianpeng Chao of Waterloo (CA) for google llc, Kalyan Srinivas Pamarthy of Sunnyvale CA (US) for google llc, Robert Lou of Sunnyvale CA (US) for google llc, Milena Bukal of Mountain View CA (US) for google llc
IPC Code(s): G06F21/62, G16H10/60
CPC Code(s): G06F21/6245
Abstract: a method of index searching of consent-protected private healthcare data includes receiving, from a computing device, a search request for access to consent-protected healthcare data stored at a consent-indexed healthcare data store. the request includes one or more consent parameters asserted for a user of the computing device. the method also includes identifying one or more asserted access consent scenarios for accessing the requested consent-protected healthcare data based on the one or more consent parameters, each asserted access consent scenario of the one or more asserted access consent scenarios representing a respective subset of the one or more consent parameters. the method further includes defining a search filter based on the one or more asserted access consent scenarios and determining, via an indexed search of the data store using the search filter, a subset of the requested data. the method includes providing the subset of data to the computing device.
20240193309.Secure Cryptographic Coprocessor_simplified_abstract_(google llc)
Inventor(s): Philipp Wagner of Cambridge (GB) for google llc, Gregory Andrew Chadwick of Cambridge (GB) for google llc, Timothy Jay Chen of Pleasanton CA (US) for google llc, Michael Stefano Fritz Schaffner of Campbell CA (US) for google llc, Christopher Gori of San Francisco CA (US) for google llc, Rupert James Swarbrick of Cambridge (GB) for google llc
IPC Code(s): G06F21/72, H04L9/08
CPC Code(s): G06F21/72
Abstract: an apparatus with an integrated circuit (ic) chip can provide protection against attacks on a cryptographic coprocessor. an attacker can compromise a cryptographic coprocessor by, for instance, obtaining a private encryption key or instruction code. to combat these attacks, example implementations store information in encrypted form. the information may correspond to data, instruction code, or intermediate values located in state registers. to securely and quickly “erase” such stored information, the cryptographic coprocessor can change the encryption key. in other example implementations, random numbers are provided with two different levels of “randomness quality” that is appropriate for different types of procedures. a cryptographic coprocessor can include two registers that store randomized bits in accordance with the two different quality levels for rapid access during cryptographic operations. to further thwart would-be attacks, a cryptographic coprocessor can verify the contents or usage of instruction code that is executed to perform cryptographic operations.
Inventor(s): Timothy Vis of Firestone CO (US) for google llc, Jesse Sterr of Eerie CO (US) for google llc, Michael Colagrosso of Arvada CO (US) for google llc, Michael Procopio of Boulder CO (US) for google llc, Sandor Dornbush of Boulder CO (US) for google llc
IPC Code(s): G06F40/169, G06F3/0481, G06F16/2457, G06N20/00, H04L51/046, H04L51/42, H04L67/10
CPC Code(s): G06F40/169
Abstract: a method of notifying a user of a cloud-based content management platform of a comment made in a file associated with a user account of the user includes identifying a subset of files with comments to be of interest to a user of cloud-based content management platform, and providing a graphical user interface (gui) of the cloud-based content management platform for presentation to the user, the gui identifying the subset of files and, for each identified file, a respective selected comment included in the identified file, and a date of the respective comment.
Inventor(s): Joseph Lange of Zurich (CH) for google llc, Henry Scott Dlhopolsky of Zurich (CH) for google llc, Vladimir Vuskovic of Zollikerberg (CH) for google llc
IPC Code(s): G06F40/35, G06N20/00, G06Q30/02
CPC Code(s): G06F40/35
Abstract: a method for dynamically generating training data for a model includes receiving a transcript corresponding to a conversation between a customer and an agent, the transcript comprising a customer input and an agent input. the method includes receiving a logic model including a plurality of responses, each response of the plurality of responses representing a potential reply to the customer input. the method further includes selecting, based on the agent input, a response from the plurality of responses of the logic model. the method includes determining that a similarity score between the selected response and the agent input satisfies a similarity threshold, and, based on determining that the similarity score between the selected response and the agent input satisfies the similarity threshold, training a machine learning model using the customer input and the selected response.
20240193418.EFFICIENT MACHINE LEARNING TRAINING ON SPREADSHEET DATA_simplified_abstract_(google llc)
Inventor(s): Mathieu Claude Charles-Marie Guillame-Bert of Bonstetten (CH) for google llc, Jan Pfeifer of Thalwil (CH) for google llc
IPC Code(s): G06N3/08, G06F40/18
CPC Code(s): G06N3/08
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating and displaying outputs conditioned on inputs. one of the methods includes displaying an interactive spreadsheet on a display of a user device; receiving an input from a user that identifies one or more cells to be filled in with respective predicted values; in response to receiving the input: training a machine learning model on the values in the cells of the interactive spreadsheet to predict respective values for the one or more identified cells; generating a respective predicted value for each of the identified cells using the trained machine learning model; and displaying the respective predicted values on the user device.
20240193421.Automatic Memory Management for Compute Graphs_simplified_abstract_(google llc)
Inventor(s): Ashish Saxena of Ilford (GB) for google llc, Vinsensius B. Vega S. Naryanto of Zurich (CH) for google llc, Matej Rizman of London (GB) for google llc, Pavel Shmakov of London (GB) for google llc, Juan Antonio Navarro Perez of London (GB) for google llc, Cyril Chimisov of London (GB) for google llc
IPC Code(s): G06N3/084
CPC Code(s): G06N3/084
Abstract: a method includes obtaining a compute graph for computing a first tensor, identifying in the graph a reduction operation in at least one dimension of the first tensor, locating, at the operation, a cut point that cuts the graph into first and second portions, and determining a plurality of slices of the first tensor. the method also includes backpropagating the cut point through the graph to define a plurality of first graph pieces for the first portion, each particular first graph piece representing a computation of a particular slice of the plurality of slices based on a particular portion of a plurality of portions of a second tensor. the method further includes defining one or more second graph pieces to combine outputs of the first graph pieces, and executing the first graph pieces and the second graph pieces to execute the first portion of the compute graph.
20240193449.Training Quantum Evolutions Using Sublogical Controls_simplified_abstract_(google llc)
Inventor(s): Ryan BABBUSH of Venice CA (US) for google llc, Hartmut NEVEN of Malibu CA (US) for google llc
IPC Code(s): G06N10/00, B82Y10/00, G06F15/16, G06N20/00
CPC Code(s): G06N10/00
Abstract: methods, systems, and apparatus for training quantum evolutions using sub-logical controls. in one aspect, a method includes the actions of accessing quantum hardware, wherein the quantum hardware includes a quantum system comprising one or more multi-level quantum subsystems; one or more control devices that operate on the one or more multi-level quantum subsystems according to one or more respective control parameters that relate to a parameter of a physical environment in which the multi-level quantum subsystems are located; initializing the quantum system in an initial quantum state, wherein an initial set of control parameters form a parameterization that defines the initial quantum state; obtaining one or more quantum system observables and one or more target quantum states; and iteratively training until an occurrence of a completion event.
20240193461.CONTENT DISTRIBUTION_simplified_abstract_(google llc)
Inventor(s): Timothy Chun-Wai Au of Milpitas CA (US) for google llc
IPC Code(s): G06N20/00, G06N5/022, G06N7/01
CPC Code(s): G06N20/00
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adjusting distribution criteria of digital component in one or more geographical regions. methods include obtaining data quantifying digital component distribution in a first and a second region during a first predetermined period of time. a machine learning model is generated to predict a first outcome quantifying digital component distribution in the first region based on a correlation between digital component distribution in a first and a second region. data is obtained that quantifies digital component distribution in the first region during a second predetermined period of time and a predicted second outcome is generated that quantifies digital component distribution during the second predetermined period of time. the predicted second outcome is compared with the digital component distribution in the first region and distribution criteria is adjusted for the first region based on the comparison.
Inventor(s): Chetan Pitambar Bhole of Mountain View CA (US) for google llc, Tanmay Khirwadkar of Fremont CA (US) for google llc, Sourabh Prakash Bansod of Mountain View CA (US) for google llc, Sanjay Mangla of San Jose CA (US) for google llc, Deepak Ramamurthi Sivaramapuram Chandrasekaran of San Jose CA (US) for google llc
IPC Code(s): G06N20/00, G06F11/36, G06F18/214, G06N20/20
CPC Code(s): G06N20/00
Abstract: simulation data associated with a simulation test performed with respect to a first set of training data is obtained. responsive to a determination that the obtained simulation data satisfies one or more criteria, a second set of training data is obtained, where a size of the second set of training data meets or exceeds a size of the first set of training data. a machine learning model is trained using the second set of training data.
20240193731.FACE REGION BASED AUTOMATIC WHITE BALANCE IN IMAGES_simplified_abstract_(google llc)
Inventor(s): Liang Liang of San Diego CA (US) for google llc, Dohyun Kim of San Mateo CA (US) for google llc
IPC Code(s): G06T5/00, G06T7/90, G06V10/25, G06V10/75, G06V40/16
CPC Code(s): G06T5/001
Abstract: implementations described herein relate to methods, devices, and computer-readable media to automatically adjust white balance in an image. in some implementations, a computer-implemented method includes detecting a face in the image, wherein the face corresponds to a plurality of pixels. the method further includes determining a region of interest (roi) for the face, wherein the region of interest excludes at least one pixel from the plurality of pixels that correspond to the face. the method further includes performing a face color calculation for the face based on the region of interest for the face. the method further includes adjusting the white balance in the image based on the face color calculation to obtain an output image.
20240193815.VERIFICATION OF A MULTI-CAMERA CALIBRATION_simplified_abstract_(google llc)
Inventor(s): Ali Osman Ulusoy of Seattle WA (US) for google llc
IPC Code(s): G06T7/80, H04N23/90
CPC Code(s): G06T7/80
Abstract: a method may receive first image data from a first camera and second image data from a second camera. a method may determine a calibration target position based on an extrinsic calibration, the first image data, the second image data, and calibration target information. a method may measure a first reprojection error of the first camera based on the extrinsic calibration, the calibration target position, and the first image data. a method may measure a second reprojection error of the second camera based on the extrinsic calibration, the calibration target position, and the second image data. upon determining that any combination of the first reprojection error is greater than a threshold reprojection error or the second reprojection error is greater than the threshold reprojection error, the method may provide an indication that the first camera and the second camera are out of calibration.
20240193841.Systems and Methods for Motion-Controlled Animation_simplified_abstract_(google llc)
Inventor(s): Shan Huang of Pudong, Shanghai (CN) for google llc
IPC Code(s): G06T13/40, G06N20/00, G06T7/246, G06T7/73, G06T15/20, H04N7/15
CPC Code(s): G06T13/40
Abstract: systems and methods can enable the control the motion of an animated character based on imagery (e.g., captured by an image capture device such as a web camera or “webcam”) which shows a person in motion. specifically, the animated character can be automatically rendered to have the same motion as the entity shown in the imagery (e.g., in real time). according to one aspect of the present disclosure, the animated character can be rendered by iteratively transforming (e.g., including deforming the actual geometry of) a vector-based surface illustration. specifically, the systems and methods present disclosure can leverage the scalable and transformable nature of a vector-based surface illustration to provide more realistic motion-controlled animation, in which the underlying geometry of the animated character is able to be adjusted to imitate human motion more realistically (e.g., as opposed to basic rotations of fixed character geometry).
Inventor(s): Jiayang Zhang of Santa Clara CA (US) for google llc, Daniel Edmond Fish of Palo Alto CA (US) for google llc, Eric Baczuk of Palo Alto CA (US) for google llc, Lynn Tsai of Seattle WA (US) for google llc
IPC Code(s): G06T19/20, G06F3/01, G06T13/40
CPC Code(s): G06T19/20
Abstract: a method of facilitating a virtual conference includes determining that a first object is non-directional, the first object being presented within an original image on a first display within the virtual conference; based on determining that the first object is non-directional, reversing an appearance and a location of the first object to generate a reversed first object; determining that a second object is directional, the second object being presented within the original image on the first display within the virtual conference; based on determining that the second object is directional, transferring a location of the second object while maintaining an orientation of the second object to generate a transferred second object; and causing a second display to generate a transformed image, the transformed image including the reversed first object and the transferred second object.
Inventor(s): Skirmantas Kligys of Manhattan Beach CA (US) for google llc, Wen-Sheng Chu of Santa Clara CA (US) for google llc, Xiaoming Liu of Mountain View CA (US) for google llc
IPC Code(s): G06V10/25, G06T7/13, G06V20/70
CPC Code(s): G06V10/25
Abstract: provided are systems and methods for detecting an object in an image. the method can include receiving an input image and analyzing the input image using an image segmentation model to identify one or more indicative areas within the input image, the one or more indicative areas being indicative of one or more objects within the input image. the method can also include analyzing the one or more indicative areas of the input image using a convolutional model to generate at least one label for at least one portion of the one or more indicative areas of the input image, the label indicating whether a specific object is identified within the input image, and performing at least one action based on the at least one label for the at least one portion.
20240193926.ATTENTION-BASED IMAGE GENERATION NEURAL NETWORKS_simplified_abstract_(google llc)
Inventor(s): Noam M. Shazeer of Palo Alto CA (US) for google llc, Lukasz Mieczyslaw Kaiser of San Francisco CA (US) for google llc, Jakob D. Uszkoreit of Berlin (DE) for google llc, Niki J. Parmar of San Francisco CA (US) for google llc, Ashish Teku Vaswani of San Francisco CA (US) for google llc
IPC Code(s): G06V10/82, G06F18/21, G06F18/213, G06F18/28, G06N3/04, G06N3/084, G06T3/4053, G06V10/56, G06V10/77
CPC Code(s): G06V10/82
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output image. in one aspect, one of the methods includes generating the output image intensity value by intensity value according to a generation order of pixel-color channel pairs from the output image, comprising, for each particular generation order position in the generation order: generating a current output image representation of a current output image, processing the current output image representation using a decoder neural network to generate a probability distribution over possible intensity values for the pixel-color channel pair at the particular generation order position, wherein the decoder neural network includes one or more local masked self-attention sub-layers; and selecting an intensity value for the pixel-color channel pair at the particular generation order position using the probability distribution.
Inventor(s): Firas Sammoura of Dublin CA (US) for google llc, James Brooks Miller of Sunnyvale CA (US) for google llc
IPC Code(s): G06V40/13, G06V40/12
CPC Code(s): G06V40/1318
Abstract: this document describes methods and systems of adaptive fingerprint-enrollment to finger characteristics using local under-display fingerprint sensors, udfps, in an electronic device. the electronic device includes an adaptive-enrollment module that determines characteristics of a fingerprint based on information corresponding to a touch input detected by a touch-display device, including size and shape of an area of the touch input. based on the fingerprint characteristics, a number and location of enrollment touches used for completing enrollment of the fingerprint are adjusted to minimize the number of enrollment touches required to complete the enrollment, minimize the amount of time needed to complete the enrollment, and maximize coverage of the fingerprint. the adaptive-enrollment module also provides visual guidance to guide the user to touch the adjusted locations of the enrollment touches and, if needed, feedback to instruct the user to adjust the location of their finger to align with the visual guidance.
20240194175.Mobile Device Assisted Active Noise Control_simplified_abstract_(google llc)
Inventor(s): Ke Dong of San Jose CA (US) for google llc, Wei Wu of Sunnyvale CA (US) for google llc, Guohua Sun of Santa Clara CA (US) for google llc, Ronald Ho of Fremont CA (US) for google llc
IPC Code(s): G10K11/178
CPC Code(s): G10K11/1783
Abstract: the present disclosure provides systems and methods for generating and transmitting, or applying, a noise profile based on a determined environment a host device is operating in. the host device may receive data from one or more sensors, location information, and/or device information. the sensors may include a pressure, temperature, light, location, or humidity sensor. the location information may include data from a global positioning system and/or connectivity signals, such as multicast dns and/or bluetooth broadcast. device information may include schedule data and/or device state information. the data from one or more sensors, the location information, and/or the device information may be aggregated to determine the environment in which the host device is operating in. based on the determined environment, a noise profile generator may generate a noise profile. the noise profile may define gains to be applied to audio signals being output to the user.
Inventor(s): Sasha Goldshtein of Tel Aviv (IL) for google llc, Yoav Tzur of Tel Aviv (IL) for google llc, Asaf Aharoni of Ramat Hasharon (IL) for google llc, Ofer Ron of Givatayim (IL) for google llc
IPC Code(s): G10L13/047, H04L51/02
CPC Code(s): G10L13/047
Abstract: implementations are directed to receiving unstructured free-form natural language input, generating a chatbot based on the unstructured free-form natural language input and in response to receiving the unstructured free-form natural language input, and causing the chatbot to perform engage in corresponding conversations with additional users. in various implementations, the unstructured free-form natural language input implicitly defines a corresponding dialog state map (e.g., defines corresponding dialog states and/or corresponding dialog state transitions) without defining any explicit dialog states and/or explicit dialog state transitions. in other implementations, the unstructured free-form natural language input is assigned to explicit dialog states and/or explicit dialog state transitions. nonetheless, the unstructured free-form natural language input may be utilized to fine-tune and/or primed a machine learning model that is already capable of being utilized in conducting generalized conversations. as a result, the chatbot can be generated and deployed in a quick and efficient manner.
20240194188.Voice-history Based Speech Biasing_simplified_abstract_(google llc)
Inventor(s): Agoston Weisz of Zurich (CH) for google llc, Mikhail Dektiarev of Zurich (CH) for google llc
IPC Code(s): G10L15/07, G10L15/30
CPC Code(s): G10L15/07
Abstract: a method of using voice query history to improve speech recognition includes receiving audio data corresponding to a current query spoken by a user and processing the audio data to generate a lattice of candidate hypotheses. the method also includes obtaining voice query history data associated with the user that includes n-grams extracted from transcriptions of previous queries spoken by the user, and generating, using a biasing context model configured to receive the voice query history data, a biasing context vector. the biasing context vector indicates a likelihood that each n-gram from the n-grams extracted from the transcriptions of the previous queries spoken by the user will appear in the current query. the method also includes augmenting the lattice of candidate hypotheses based on the biasing context vector and determining a transcription for the current query based on the augmented lattice of candidate hypotheses.
Inventor(s): Yuan Yuan of Redwood City CA (US) for google llc, Bibo Xu of San Jose CA (US) for google llc, Tianyu Wang of Los Altos CA (US) for google llc, Anurag Jain of Palo Alto CA (US) for google llc
IPC Code(s): G10L15/08, G06F40/279, G06N20/00, G06V40/19
CPC Code(s): G10L15/08
Abstract: techniques are described herein for detecting and/or enrolling (or commissioning) new “hot commands” that are useable to cause an automated assistant to perform responsive action(s) without having to be first explicitly invoked. in various implementations, an automated assistant may be transitioned from a limited listening state into a full speech recognition state in response to a trigger event. while in the full speech recognition state, the automated assistant may receive and perform speech recognition processing on a spoken command from a user to generate a textual command. the textual command may be determined to satisfy a frequency threshold in a corpus of textual commands. consequently, data indicative of the textual command may be enrolled as a hot command. subsequent utterance of another textual command that is semantically consistent with the textual command may trigger performance of a responsive action by the automated assistant, without requiring explicit invocation.
Inventor(s): Pu-sen Chao of Los Altos CA (US) for google llc, Diego Melendo Casado of Mountain View CA (US) for google llc, Ignacio Lopez Moreno of New York NY (US) for google llc
IPC Code(s): G10L15/14, G06F3/16, G10L15/00, G10L15/02, G10L15/08, G10L15/18, G10L15/183, G10L15/22, G10L15/30
CPC Code(s): G10L15/14
Abstract: implementations relate to determining a language for speech recognition of a spoken utterance, received via an automated assistant interface, for interacting with an automated assistant. implementations can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. selection of a speech recognition model for a particular language can based on one or more interaction characteristics exhibited during a dialog session between a user and an automated assistant. such interaction characteristics can include anticipated user input types, anticipated user input durations, a duration for monitoring for a user response, and/or an actual duration of a provided user response.
Inventor(s): Ehsan Amid of Mountain View CA (US) for google llc, Rajiv Mathews of Sunnyvale CA (US) for google llc, Shankar Kumar of New York NY (US) for google llc, Jared Lichtarge of Brooklyn NY (US) for google llc, Mingqing Chen of Saratoga CA (US) for google llc, Tien-Ju Yang of Mountain View CA (US) for google llc, Yuxin Ding of San Francisco CA (US) for google llc
IPC Code(s): G10L15/16, G10L15/06
CPC Code(s): G10L15/16
Abstract: information can be distilled from a global automatic speech recognition (asr) model to a client asr model. many implementations include using an rnn-t model as the asr model, where the global asr model includes a global encoder, a joint network, a prediction network, and where the client asr model includes a client encoder, the joint network, and the prediction network. various implementations include using principal component analysis (pca) while training the global asr model to learn a mean vector and a set of principal components corresponding to the global asr model. additional or alternative implementations include training the client asr model to generate one or more predicted coefficients of the global asr model.
20240194532.MULTI-LAYER CHIP ARCHITECTURE AND FABRICATION_simplified_abstract_(google llc)
Inventor(s): Zhimin Jamie Yao of Santa Barbara CA (US) for google llc, Michael C. Hamilton of Auburn AL (US) for google llc, Marissa Giustina of Santa Barbara CA (US) for google llc, Brian James Burkett of Santa Barbara CA (US) for google llc, Theodore Charles White of Santa Barbara CA (US) for google llc, Ofer Naaman of Santa Barbara CA (US) for google llc
IPC Code(s): H01L21/822, H01L21/02, H01L21/311, H01L21/768, H01L23/00, H01L25/07
CPC Code(s): H01L21/8221
Abstract: a method includes providing a first chip having a circuit element layer stack, the circuit element layer stack including a plurality of circuit elements distributed across a plurality of layers. the circuit element layer stack has a sacrificial material filling a space between the plurality of circuit elements in the plurality of layers and a coherent device layer disposed on the circuit element layer stack. the method includes removing the sacrificial material.
20240194661.MULTI-LAYER CHIP ARCHITECTURE AND FABRICATION_simplified_abstract_(google llc)
Inventor(s): Zhimin Jamie Yao of Santa Barbara CA (US) for google llc, Michael C. Hamilton of Auburn AL (US) for google llc, Marissa Giustina of Santa Barbara CA (US) for google llc, Brian James Burkett of Santa Barbara CA (US) for google llc, Theodore Charles White of Santa Barbara CA (US) for google llc, Ofer Naaman of Santa Barbara CA (US) for google llc
IPC Code(s): H01L25/00, H01L23/00
CPC Code(s): H01L25/50
Abstract: a method includes providing a first chip having a circuit element layer stack, the circuit element layer stack including a plurality of circuit elements distributed across a plurality of layers. the circuit element layer stack has a sacrificial material filling a space between the plurality of circuit elements in the plurality of layers and a coherent device layer disposed on the circuit element layer stack. the method includes removing the sacrificial material.
20240195212.Timing Determination for UPS Power Transfer_simplified_abstract_(google llc)
Inventor(s): Sangsun Kim of San Jose CA (US) for google llc, Krishnanjan Gubba Ravikumar of Pullman WA (US) for google llc
IPC Code(s): H02J9/06, G01R19/02, H02J3/00
CPC Code(s): H02J9/062
Abstract: disclosed are devices, systems, and methods for operating a backup power source or an uninterruptible power supply (ups) that can be used in data centers and that provide a backup power source to power the data center when utility power is compromised. a power delivery system that provides power to a primary system may include a ups with a state timing control system that operates a bypass static switch. the state timing control system can determine when to transition the primary system from the utility power supply to the backup ups, based on the current ac voltage conditions. the state timing control system may perform modeling to emulate the intermediate dc voltage of an actual rectifier, and particularly emulate the holdup capacitor voltage. the emulated capacitor voltage can be obtained in real time by both an input power model based on rms utility voltage and the actual rectifier output load.
Inventor(s): Gang Wang of Frederick MD (US) for google llc, Marcel M. Moti Yung of New York NY (US) for google llc
IPC Code(s): H04L9/00
CPC Code(s): H04L9/008
Abstract: this document describes systems and techniques for using secure mpc to select digital components in ways that preserve user privacy and protects the security of data of each party that is involved in the selection process. in one aspect, a method includes obtaining, by a first computer of a secure multi-party computation (mpc) system, at least a first share of a set of contextual properties of an environment in which a selected digital component will be displayed at a client device. for each digital component in a set of digital components, at least a first share of an eligibility expression that defines a relationship between a set of eligibility criteria for the digital component is obtained. a determination is made, based on the at least first share of the set of contextual properties and the at least first share of the eligibility expression, a first share of an eligibility parameter.
Inventor(s): Mehmet Alphan Ulusoy of Framingham MA (US) for google llc, Miguel Angel Osorio Lozano of El Dorado Hills CA (US) for google llc
IPC Code(s): H04L9/32
CPC Code(s): H04L9/3249
Abstract: aspects of hardened encoded message check systems and methods for rsa signature verification are described. in one implementation, an encoded message is received that includes an array of words. each of the words in the encoded message are processed using an expected value and a share associated with each word. a verification value is calculated based on the array of words in the encoded message, the expected value, and the share associated with each word. a determination is performed regarding whether the verification value is correct and, if the verification value is correct, a hardware device is unlocked.
Inventor(s): Yazhou Zu of Sunnyvale CA (US) for google llc, Alireza Ghaffarkhah of San Jose CA (US) for google llc, Dayou Du of San Jose CA (US) for google llc
IPC Code(s): H04L41/0654, H04L41/16, H04L43/02, H04L43/0823
CPC Code(s): H04L41/0672
Abstract: generally disclosed herein is an approach for smart topology-aware link disabling and user job rescheduling strategies for online network repair of broken links in high performance networks used in supercomputers that are common in machine learning (ml) and high-performance computing (hpc) applications. while a disabled link is repaired online, user jobs may continue to run. the broken links may be detected as part of pre-flight checks before the user jobs run and/or during the job run time via a distributed failure detection and mitigation software stack which includes a centralized network controller and multiple agents running on each node. the network controller may ensure that the user jobs are rerouted to healthy links within the same network until the broken links are fixed and tested by the repair workflows, in which case the broken links are enabled again by the network controller for future user jobs.
20240195713.Synthetic Resource Records_simplified_abstract_(google llc)
Inventor(s): Brent Anthony Piller Bryan of Mountain View CA (US) for google llc, Jonathan Mack of Seattle WA (US) for google llc, Roberto Ramalho Fischer of Mountain View CA (US) for google llc
IPC Code(s): H04L43/04, G06F16/23
CPC Code(s): H04L43/04
Abstract: provided are methods and systems for using synthetic resource records to configure and manage web applications and various online services. a user is provided with the ability to setup a single synthetic resource record for their domain such that all of the associated dependent resource records are automatically configured and added to the domain as well. the methods and systems provided utilize synthetic resource records as a way of logically grouping resource records into “human readable” sets of resource records. through synthetic resource records, users are able to address common configuration issues without having to know the technical specifications of associated zone files or resource records. additionally, users can complete a variety of configuration tasks related to setting-up web applications without having to look-up resource record values from external sites (e.g., from the domain host).
Inventor(s): Yazhou Zu of Sunnyvale CA (US) for google llc, Brian Patrick Towles of Chapel Hill NC (US) for google llc, Alireza Ghaffarkhah of San Jose CA (US) for google llc
IPC Code(s): H04L45/28, H04L45/00
CPC Code(s): H04L45/28
Abstract: generally disclosed herein is an approach for optimizing routing strategy to tolerate faults in a toroidal network topology including, but not limited to, n-dimensional mesh, torus, and twisted torus. the approach may include balancing a load for a specified input traffic pattern operating offline or online. the approach may also include an optimization enhancement technique specifically applicable to symmetric, dynamically composable toroidal networks based on a set of centrally connected circuit switches.
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc, Victor Carbune of Zurich (CH) for google llc
IPC Code(s): H04L51/02, G06V40/16, G10L15/08, G10L17/06
CPC Code(s): H04L51/02
Abstract: implementations are directed to enabling a representative associated with an entity to quickly and efficiently modify a voice bot associated with the entity. the voice bot can be previously trained to communicate with user(s) on behalf of the entity through various communication channels (e.g., a telephone communication channel, a software application communication channel, a messaging communication channel, etc.). processor(s) of a computing device can receive, from the representative, representative input to modify behavior(s) and/or parameter(s) that the voice bot utilizes in communicating with the plurality of users via the communication channels, determine whether the representative is authorized to cause the behavior(s) and/or parameter(s) to be modified, and cause the behavior(s) and/or parameter(s) to be modified in response to determining that the representative is authorized. notably, the representative input can be received through the same communication channels that the user(s) utilize to communicate with the voice bot.
20240195765.PERSONALITY REPLY FOR DIGITAL CONTENT_simplified_abstract_(google llc)
Inventor(s): Ibrahim Badr of Zurich (CH) for google llc, Aayush Kumar of Zurich (CH) for google llc, Goekhan Hasan Bakir of Zurich (CH) for google llc, Nils Grimsmo of Adiswill (CH) for google llc, Bianca Madalina Buisman of Kilchberg (CH) for google llc
IPC Code(s): H04L51/046, H04L51/10
CPC Code(s): H04L51/046
Abstract: a computer-implemented method is described. the method includes a computing system receiving an item of digital content from a user device. the computing system generates one or more labels that indicate attributes of the item of digital content. the computing system also generates one or more conversational replies to the item of digital content based on the one or more labels that indicate attributes of the item of digital content. the method also includes the computing system selecting a conversational reply from among the one or more conversational replies and providing the conversational reply for output to the user device.
Inventor(s): Yaowu Xu of Saratoga CA (US) for google llc, Bohan Li of Santa Clara CA (US) for google llc, Jingning Han of Santa Clara CA (US) for google llc
IPC Code(s): H04N19/139, H04N19/105, H04N19/172, H04N19/537, H04N19/573, H04N19/577
CPC Code(s): H04N19/139
Abstract: a motion vector for a current block of a current frame is decoded from a compressed bitstream. a location of a reference block within an un-generated reference frame is identified. the reference block is generated using a forward reference frame and a backward reference frame without generating the un-generated reference frame. the reference block is generated by identifying an extended reference block by extending the reference block at each boundary of the reference block by a number of pixels related to a filter length of a filter used in sub-pixel interpolation; and generating pixel values of only the extended reference block by performing a projection using the forward reference frame and the backward reference frame without generating the whole of the un-generated reference frame. the current block is then decoded based on the reference block and the motion vector.
20240195985.VIDEO INTER/INTRA COMPRESSION USING MIXTURE OF EXPERTS_simplified_abstract_(google llc)
Inventor(s): David Charles Minnen of Mountain View CA (US) for google llc, Sung Jin Hwang of Mountain View CA (US) for google llc, Elliott Michael Karpilovsky of Santa Clara CA (US) for google llc, Debargha Mukherjee of Cupertino CA (US) for google llc
IPC Code(s): H04N19/176, H04N19/119, H04N19/159
CPC Code(s): H04N19/176
Abstract: methods, systems, and apparatus, including computer programs, for compression and decompression of video data using an ensemble of machine learning models. methods can include defining for each frame in a video, a plurality of blocks in the frame. methods can further include processing the frames of video in sequential sets, wherein each sequential set is at least a current frame () of video and a prior frame () of video in the ordered sequence. each respective prediction of a block in the frame of the video includes providing, as input to a prediction model a first and the second border () of a current block () of the current frame, a first and a second border () for a respective current block () of the prior frame and the respective current block () of the prior frame.
Inventor(s): Rachel Hausmann of Mountain View CA (US) for google llc, Collin Irwin of Mountain View CA (US) for google llc
IPC Code(s): H04N21/439, G10L15/18, G11B27/029, H04N21/233, H04N21/81
CPC Code(s): H04N21/4394
Abstract: the present disclosure is generally related to inserting supplemental audio content into primary audio content via digital assistant applications. a data processing system can maintain an audio recording of a content publisher and a content spot marker to specify a content spot that defines a time at which to insert supplemental audio content. the data processing system can receive an input audio signal from a client device. the data processing system can parse the input audio signal to determine that the input audio signal corresponds to a request and can identify the audio recording of the content publisher. the data processing system can identify, responsive to the determination, a content selection parameter. the data processing system can select an audio content item using the content selection parameter. the data processing system can generate and transmit an action data structure including the audio recording inserted with audio content item.
20240196053.Media Arbitration_simplified_abstract_(google llc)
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc, Victor Carbune of Zürich (CH) for google llc
IPC Code(s): H04N21/442, H04N21/258, H04W4/029
CPC Code(s): H04N21/44209
Abstract: a method using media arbitration includes, while a first assistant-enabled device is performing a first long-standing operation, determining the first assistant-enabled device satisfies a co-presence condition with a second assistant-enabled device, and determining that the second assistant-enabled device is performing a second long-standing operation that conflicts with the first long-standing operation performed by the first assistant-enabled device. based on determining that the first long-standing operation and the second long-standing operation conflict, the method also includes executing an operation arbitration routine to identify one or more compromise operations for at least one of the first assistant-enabled device or the second assistant-enabled device to perform, and instructing the first assistant-enabled device or the second assistant-enabled device to perform a selected compromise operation among the identified compromise operations.
Inventor(s): Lukasz Bieniasz-Krzywiec of Sunnyvale CA (US) for google llc, Dariusz Leniowski of Mountain View CA (US) for google llc, Venu Vemula of San Ramon CA (US) for google llc
IPC Code(s): H04W4/02, G06F16/9535, G06F16/9537, H04W4/021
CPC Code(s): H04W4/025
Abstract: a method includes receiving, from a device, a request for content for presentation on the device, and receiving selection criteria for a plurality of candidate content items. the selection criteria define one or more operating system types on which the plurality of candidate content items are to be displayed. the method further includes selecting the plurality of candidate content items based on an operating system type of the device and the selection criteria, determining a value from a sensor of the device, and selecting, based on the value from the sensor, a content item from the plurality of candidate content items. the method further includes providing the content item for presentation on the device.
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc
IPC Code(s): H04W24/10, H04W76/27
CPC Code(s): H04W24/10
Abstract: a radio access network (ran): a core network (cn) or operations, administration, and management (0am) node; and a user equipment (ue) can implement a method for managing quality of experience (qoe) reporting from the ue. the method includes: receiving, by processing hardware and from a ue, a request to reestablish a radio connection; retrieving, by the processing hardware, a configuration for the qoe reporting; and performing at least one of: (i) facilitating, by the processing hardware and after the retrieving, reporting of qoe measurements for the ue to the qoe node, or (ii) releasing the configuration.
- Google LLC
- B25J9/16
- CPC B25J9/163
- Google llc
- CPC B25J9/1671
- G03F7/20
- G03F1/70
- CPC G03F7/70216
- G06F1/16
- G02F1/1333
- G02F1/1337
- G06F3/16
- G06F21/83
- G10L15/28
- H04L12/28
- H04R1/02
- H04R1/34
- CPC G06F1/166
- G06F3/01
- CPC G06F3/016
- G06F3/043
- G10L15/22
- G10L21/0208
- CPC G06F3/043
- G06F3/0482
- G05B15/02
- G06F3/04817
- G06F16/738
- G06F40/35
- G11B27/30
- H04L65/403
- H04L65/61
- H04N7/18
- H04N21/2387
- H04N21/4223
- H04N21/431
- H04N21/472
- H04N21/488
- H04N21/63
- H04N21/845
- H04N21/8549
- H04N21/858
- CPC G06F3/0482
- G06F3/0485
- G06F3/0481
- H04N23/695
- CPC G06F3/0485
- G06F3/06
- CPC G06F3/0608
- G06F9/50
- G06N20/00
- CPC G06F3/0679
- G06F8/65
- G06F8/71
- CPC G06F9/5055
- G06F11/07
- CPC G06F11/0793
- G06F11/27
- CPC G06F11/27
- G06F12/0895
- G06F12/0864
- G06F12/121
- CPC G06F12/0895
- G06F16/21
- G06F16/23
- G06F16/2457
- CPC G06F16/219
- G06F16/438
- G06F16/638
- CPC G06F16/4387
- G06F16/957
- G06F16/955
- G06Q50/00
- H04L67/50
- CPC G06F16/9577
- G06F21/62
- G06F16/2458
- CPC G06F21/6227
- G16H10/60
- CPC G06F21/6245
- G06F21/72
- H04L9/08
- CPC G06F21/72
- G06F40/169
- H04L51/046
- H04L51/42
- H04L67/10
- CPC G06F40/169
- G06Q30/02
- CPC G06F40/35
- G06N3/08
- G06F40/18
- CPC G06N3/08
- G06N3/084
- CPC G06N3/084
- G06N10/00
- B82Y10/00
- G06F15/16
- CPC G06N10/00
- G06N5/022
- G06N7/01
- CPC G06N20/00
- G06F11/36
- G06F18/214
- G06N20/20
- G06T5/00
- G06T7/90
- G06V10/25
- G06V10/75
- G06V40/16
- CPC G06T5/001
- G06T7/80
- H04N23/90
- CPC G06T7/80
- G06T13/40
- G06T7/246
- G06T7/73
- G06T15/20
- H04N7/15
- CPC G06T13/40
- G06T19/20
- CPC G06T19/20
- G06T7/13
- G06V20/70
- CPC G06V10/25
- G06V10/82
- G06F18/21
- G06F18/213
- G06F18/28
- G06N3/04
- G06T3/4053
- G06V10/56
- G06V10/77
- CPC G06V10/82
- G06V40/13
- G06V40/12
- CPC G06V40/1318
- G10K11/178
- CPC G10K11/1783
- G10L13/047
- H04L51/02
- CPC G10L13/047
- G10L15/07
- G10L15/30
- CPC G10L15/07
- G10L15/08
- G06F40/279
- G06V40/19
- CPC G10L15/08
- G10L15/14
- G10L15/00
- G10L15/02
- G10L15/18
- G10L15/183
- CPC G10L15/14
- G10L15/16
- G10L15/06
- CPC G10L15/16
- H01L21/822
- H01L21/02
- H01L21/311
- H01L21/768
- H01L23/00
- H01L25/07
- CPC H01L21/8221
- H01L25/00
- CPC H01L25/50
- H02J9/06
- G01R19/02
- H02J3/00
- CPC H02J9/062
- H04L9/00
- CPC H04L9/008
- H04L9/32
- CPC H04L9/3249
- H04L41/0654
- H04L41/16
- H04L43/02
- H04L43/0823
- CPC H04L41/0672
- H04L43/04
- CPC H04L43/04
- H04L45/28
- H04L45/00
- CPC H04L45/28
- G10L17/06
- CPC H04L51/02
- H04L51/10
- CPC H04L51/046
- H04N19/139
- H04N19/105
- H04N19/172
- H04N19/537
- H04N19/573
- H04N19/577
- CPC H04N19/139
- H04N19/176
- H04N19/119
- H04N19/159
- CPC H04N19/176
- H04N21/439
- G11B27/029
- H04N21/233
- H04N21/81
- CPC H04N21/4394
- H04N21/442
- H04N21/258
- H04W4/029
- CPC H04N21/44209
- H04W4/02
- G06F16/9535
- G06F16/9537
- H04W4/021
- CPC H04W4/025
- H04W24/10
- H04W76/27
- CPC H04W24/10
