Google LLC patent applications on January 9th, 2025
Patent Applications by Google LLC on January 9th, 2025
Google LLC: 43 patent applications
Google LLC has applied for patents in the areas of G10L15/22 (5), G06N20/00 (4), G06N3/08 (3), G10L15/16 (2), H04R1/04 (2) G10L15/22 (3), B25J9/1697 (1), H04L9/0852 (1), G06T11/001 (1), G09G3/2007 (1)
With keywords such as: data, device, user, based, assistant, receiving, response, automated, multiple, and network in patent application abstracts.
Patent Applications by Google LLC
20250010482. Multimodal Object Identification_simplified_abstract_(google llc)
Inventor(s): Michael Joseph Quinlan of Sunnyvale CA (US) for google llc, Gabriel A. Cohen of Alameda CA (US) for google llc
IPC Code(s): B25J9/16, B25J19/02, G05B19/048
CPC Code(s): B25J9/1697
Abstract: methods, systems, and apparatus for receiving a command for controlling a robot, the command referencing an object, receiving sensor data for a portion of an environment of the robot, identifying, from the sensor data, a gesture of a human that indicates a spatial region located outside of the portion of the environment described by the sensor data, searching map data for the object, determining, based at least on searching the map data for the object referenced in the command, that the object referenced in the command is present in the spatial region, and in response to determining that the object referenced in the command is present in the spatial region, controlling the robot to perform an action with respect to the object referenced in the command.
Inventor(s): Matthew Sharifi of Mountain View CA (US) for google llc
IPC Code(s): G01C21/36, G01C21/34
CPC Code(s): G01C21/3617
Abstract: a computing device may implement a method for providing route information regarding a completed or ongoing trip by a user without the user having previously initiated a navigation session. the method may include receiving a query regarding a previous or ongoing trip by a user prior to the user initiating a navigation session; determining an origin for the previous or ongoing trip; obtaining route information for the previous or ongoing trip; generating one or more route attributes associated with the query based at least on the origin for the previous or ongoing trip and the route information for the previous or ongoing trip; and providing a response to the query based at least on the one or more route attributes.
20250012589. Navigation Directions Preview_simplified_abstract_(google llc)
Inventor(s): Victor Carbune of Zurich (CH) for google llc, Matthew Sharifi of Zurich (CH) for google llc
IPC Code(s): G01C21/36
CPC Code(s): G01C21/3647
Abstract: to present a navigation directions preview, a server device receives a request for navigation directions from a starting location to a destination location and generates a set of navigation directions in response to the request. the set of navigation directions includes a set of route segments for traversing from the starting location to the destination location. the server device selects a subset of the route segments based on characteristics of each route segment in the set of route segments. for each selected route segment, the server device provides a preview of the route segment to be displayed on a client device. the preview of the route segment includes panoramic street level imagery depicting the route segment.
20250012595. Generation of Surface Maps to Improve Navigation_simplified_abstract_(google llc)
Inventor(s): Yan Mayster of Aurora CO (US) for google llc, Brian Daniel Shucker of Superior CO (US) for google llc
IPC Code(s): G01C21/00, B60W40/06, B60W40/076, B60W50/14, G01S7/48, G06V10/80, G06V20/56
CPC Code(s): G01C21/3807
Abstract: provided are methods, systems, devices, and tangible non-transitory computer readable media for mapping geographical surfaces. the disclosed technology can access image data and sensor data. the image data can include a plurality of images of one or more locations and semantic information associated with the one or more locations. the sensor data can include sensor information associated with detection of one or more surfaces at the one or more locations by one or more sensors. one or more irregular surfaces can be detected based at least in part on the image data and the sensor data. the one or more irregular surfaces can include the one or more surfaces associated with the image data and the sensor data that satisfies one or more irregular surface criteria at each of the one or more locations respectively. map data including information associated with the one or more irregular surfaces can be generated.
Inventor(s): Liming Wang of San Jose CA (US) for google llc, Xiang Zhou of Sunnyvale CA (US) for google llc, Cedric Fung Lam of San Carlos CA (US) for google llc
IPC Code(s): G01M11/00
CPC Code(s): G01M11/33
Abstract: methods and apparatus for monitoring chirp in a modulated light beam. the modulated light is passed through a variable dispersion element or “vde”, and the light from the variable dispersion element is detected to yield a signal. a parameter which represents the strength of modulation in the light after passage through the vde such as the peak intensity of the modulated light is measured as the vde is controlled to vary the applied dispersion. the chip is determined from the variation of the parameter with dispersion, such as from the dispersions at which the parameter is at minima. the method can be applied to beams modulated by common digital transmitters used in optical communication systems.
20250013310. MULTI-MODAL GESTURE SENSING ON WEARABLE DEVICES_simplified_abstract_(google llc)
Inventor(s): Patrick Muller Amihood of Palo Alto CA (US) for google llc, Octavio Ponce Madrigal of Mountain View CA (US) for google llc
IPC Code(s): G06F3/01, G06F3/0346
CPC Code(s): G06F3/017
Abstract: techniques include using, in addition to imu signals, audio captured by one or more microphones on a wearable device to determine whether a gesture has been made, and if so, which gesture has been made. the imus provide a first electronic signal to processing circuitry on the wearable device in response to detected motion. the one or more microphones provide a second electronic signal to the processing circuitry in response to detected audio resulting from a gesture. the processing circuitry determines whether a predefined gesture has been made based at least on the first electronic signal and the second electronic signal. if the processing circuitry determines that the predefined gesture was made, the processing circuitry performs an operation on the wearable device corresponding to the predefined gesture.
20250013331. AUTOMATIC LIQUID DETECTION_simplified_abstract_(google llc)
Inventor(s): John J. Anthony, III of East Lyme CT (US) for google llc, Aaron Michael Rudolph of Penryn CA (US) for google llc, Tyler Gore of Mountain View CA (US) for google llc, Sushant Sundaresh of San Carlos CA (US) for google llc
IPC Code(s): G06F3/041, G06N20/00
CPC Code(s): G06F3/04186
Abstract: a computing device may determine, based on one or more inputs detected by a presence-sensitive screen, whether at least a threshold amount of liquid is present on the presence-sensitive screen. the computing device may automatically transition the computing device from operating in a first operating mode to operating in a second operating mode responsive to determining that at least the threshold amount of liquid is present. the computing device may discard inputs detected by the presence-sensitive screen while the computing device is operating in the second operating mode.
20250013351. Efficiently Augmenting Images with Related Content_simplified_abstract_(google llc)
Inventor(s): Charles Yang of Fremont CA (US) for google llc, Louis Wang of San Francisco CA (US) for google llc, Charles J. Rosenberg of Cupertino CA (US) for google llc
IPC Code(s): G06F3/0482, G06F3/04845, G06F16/583, G06F16/951, G06F40/205
CPC Code(s): G06F3/0482
Abstract: the subject matter of this specification generally relates to providing content related to text depicted in images. in one aspect, a system includes a data processing apparatus configured to extract text from an image. the extracted text is partitioned into multiple blocks. the multiple blocks are presented as respective first user-selectable targets on a user interface at a first zoom level. a user selection of a first block of the multiple blocks is detected. in response to detecting the user selection of the first block, portions of the extracted text in the first block are presented as respective second user-selectable targets on the user interface at a second zoom level greater than the first zoom level. in response to detecting a user selection of a portion of the extracted text within the first block, an action is initiated based on content of the user-selected text.
Inventor(s): David Kogan of Natick MA (US) for google llc, Bryan Christopher Horling of Belmont MA (US) for google llc
IPC Code(s): G06F3/16, G06F3/0484, G06F16/248, G06F16/28, G06F16/332, G06F16/338, G06F16/951
CPC Code(s): G06F3/167
Abstract: methods, apparatus, and computer readable media related to interaction between a user and an automated assistant during a dialog between the user and the automated assistant. some implementations are directed to adapting a graphical and/or audible presentation of search results provided by the automated assistant for presentation to the user. the adaptation may be in response to attribute(s), of one or more of the search results, referenced in spoken and/or typed textual input provided by the user during the dialog. some of those implementations may enable a user to provide textual input to navigate the search results within the dialog and within resource and/or interface constraints associated with the dialog. some of those implementations may additionally and/or alternatively enable adapting, based on textual input provided by a user to the automated assistant, when and/or whether search results having certain attributes are provided to the user by the automated assistant.
Inventor(s): Vinayak Anand Gokhale of Austin TX (US) for google llc, Matthew Leever Hedlund of Sun Prairie WI (US) for google llc, Rahul Nagarajan of San Jose CA (US) for google llc, Naveen Muralimanohar of San Jose CA (US) for google llc, Shriram Nagarajan of Santa Clara CA (US) for google llc
IPC Code(s): G06F7/544, G06F7/50, G06F7/533
CPC Code(s): G06F7/5443
Abstract: aspects of the disclosed technology include techniques and mechanisms for using a custom scratchpad memory for partial dot product reductions. the custom scratchpad memory may be a special purpose memory that is dedicated to receiving and storing partial dot products determined by matrix multiplier units. each partial dot product may correspond to tiles of a resultant matrix, where the resultant matrix is the product of matrix multiplication that can use a first matrix representing a user query as a left-hand side operand and a second matrix representing a trained model containing data that may be used to respond to the user query as a right-hand side operand. the custom scratchpad memory may append the tiles determined by the matrix multiplication, where the appended tiles may create the resultant matrix. custom scratchpad memory may write the resultant matrix to general purpose memory, where it may be used to respond to the user query.
20250013438. SCRIPT EDITOR FOR ROUTINE CREATION_simplified_abstract_(google llc)
Inventor(s): Michael Andrew Goodman of Mountain View CA (US) for google llc, Deepak Goyal of Mountain View CA (US) for google llc
IPC Code(s): G06F8/35, G06F8/34, G10L13/08, G10L15/22
CPC Code(s): G06F8/35
Abstract: a method include receiving a natural language prompt from a user comprising a command to generate a code script for an automated assistant to perform a routine. the routine includes multiple discrete actions specified by the natural language prompt. the method further includes processing, by a pre-trained large language model (llm), the natural language prompt to generate the code script as an llm output, and processing the code script to determine the code script is incomplete, thereby rendering the code script unsuitable for the automated assistant to fulfill performance of the routine. based on determining the code script is incomplete, the method includes issuing a user prompt soliciting the user to provide additional information needed to complete the code script and receiving user input of the additional information needed to complete the code script. the method includes supplementing the code script with the additional information to render completed code script.
Inventor(s): Christopher Ian Schneider of Edinburgh (GB) for google llc, Bessie S. Jiang of London (GB) for google llc, J. Nicolas Watson of Reston VA (US) for google llc
IPC Code(s): G06F8/41
CPC Code(s): G06F8/41
Abstract: a method includes generating a modeling language diagram that is indicative of a compiled version of program code. the modeling language diagram includes at least one node corresponding to at least one function in the program code. the method also includes identifying at least one function signature associated with anode state transition between nodes in the modeling language diagram. the method also includes identifying, using a large language model, a particular policy to attribute to the at least one function signature associated with the node state transition. the method further includes performing, using the large language model, a policy compliance operation that ensures a particular portion of the program code complies with the particular policy. the particular portion of the program code is associated with the node state transition. performing the policy compliance operation includes generating a policy-compliant version of the particular portion of the program code.
Inventor(s): Joseph Cohen of Mountain View CA (US) for google llc, Justin Lewis of Marina Del Rey CA (US) for google llc
IPC Code(s): G06F9/54, G06F3/04847, G06F9/451
CPC Code(s): G06F9/542
Abstract: systems and methods of implementing a finite-state machine using electronic notifications delivered to a client device in a computer networking environment are provided. a content item can be received, along with first and second notifications associated with the content item. the first and second notifications can be stored in a queue. in some implementations, a state machine can be maintained in which at least some states may cause the first or second notifications to be displayed, and in which transitional conditions between states may depend at least in part on user interaction with the displayed notifications.
Inventor(s): Fady Sedrak of Santa Clara CA (US) for google llc
IPC Code(s): G06F16/17, G06F16/11, G06F16/14, G06F16/188
CPC Code(s): G06F16/1734
Abstract: a data storage management method includes detecting a data change to data in a data repository, identifying metadata of the data change, and storing the metadata in a virtual file, the virtual file being in a data storage format that is compatible with one or more data analysis tools. in response to a subsequent user request to access metadata of the data in the data repository, the method may transmit one or more virtual files containing metadata identified in the user request.
20250013630. DATA INTEGRITY OPTIMIZATION_simplified_abstract_(google llc)
Inventor(s): Satvik Chauhan of Campbell CA (US) for google llc, Riyana Basu of Mountain View CA (US) for google llc, Lianxiao Qiu of Sunnyvale CA (US) for google llc
IPC Code(s): G06F16/23, G06F16/26
CPC Code(s): G06F16/2365
Abstract: a method includes receiving interaction data indicating a performance of a specified action by a user of a user device, identifying a last-in-time action associated with the user and an initiation action associated with the user and the specified action, generating, based on the identified last-in-time and initiation actions, a first attribution associated with the identified last-in-time action and the specified action and a second, additional attribution associated with the identified initiation action and the specified action, propagating, to two or more different models, the first attribution and the second, additional attribution, and generating, based on the first attribution and the second, additional attribution, one or more visual representations of the first attribution and the second, additional attribution.
20250013774. ENCRYPTED INFORMATION RETRIEVAL_simplified_abstract_(google llc)
Inventor(s): Eli Simon Fox-Epstein of Los Angeles CA (US) for google llc, Kevin Wei Li Yeo of New York NY (US) for google llc, Sarvar Patel of Montville NJ (US) for google llc, Raimundo Mirisola of Los Angeles CA (US) for google llc, Craig William Wright of Louisville CO (US) for google llc
IPC Code(s): G06F21/62
CPC Code(s): G06F21/6218
Abstract: encrypted information retrieval can include generating a database that is partitioned into shards each having a shard identifier, and database entries in each shard that are partitioned into buckets having a bucket identifier. a batch of client-encrypted queries are received. the batch of client-encrypted queries are processed using a set of server-encrypted data stored in a database. the processing includes grouping the client-encrypted queries according to shard identifiers of the client-encrypted queries, executing multiple queries in the group of client-encrypted queries for the shard together in a batch execution process, and generating multiple server-encrypted results to the multiple queries in the group of client-encrypted queries. the multiple server-encrypted results for each shard are transmitted to the client device.
Inventor(s): Brian Chu of New York NY (US) for google llc, Manoj Kumar Tiwari of Santa Clara CA (US) for google llc
IPC Code(s): G06F40/284
CPC Code(s): G06F40/284
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an explanation of a content item recommendation. for example, a system can use a language model neural network to generate a natural language explanation of why a particular content item was recommended given the context of the recommendation.
20250013864. BATCH NORMALIZATION LAYERS_simplified_abstract_(google llc)
Inventor(s): Sergey Ioffe of Mountain View CA (US) for google llc, Corinna Cortes of New York NY (US) for google llc
IPC Code(s): G06N3/08, G06F18/2415, G06N3/04, G06N3/084, G06V10/70, G06V10/82
CPC Code(s): G06N3/08
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a batch normalization layer. one of the methods includes receiving a respective first layer output for each training example in the batch; computing a plurality of normalization statistics for the batch from the first layer outputs; normalizing each component of each first layer output using the normalization statistics to generate a respective normalized layer output for each training example in the batch; generating a respective batch normalization layer output for each of the training examples from the normalized layer outputs; and providing the batch normalization layer output as an input to the second neural network layer.
Inventor(s): Yingjie Miao of Fremont CA (US) for google llc, John Dalton Co-Reyes of San Francisco CA (US) for google llc, Esteban Alberto Real of Sunnyvale CA (US) for google llc, George Jay Tucker of Sunnyvale CA (US) for google llc, Aleksandra Faust of Palo Alto CA (US) for google llc
IPC Code(s): G06N5/01, G06N3/08
CPC Code(s): G06N5/01
Abstract: methods and systems for receiving training data for a machine learning (ml) task and searching, using the training data, for an optimized component of an ml algorithm for performing the ml task are described.
Inventor(s): Hyun Jin Park of Palo Alto CA (US) for google llc, Dongseong Hwang of Kirkland WA (US) for google llc, Chang Wan Ryu of Mountain View CA (US) for google llc
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: in one example aspect, the present disclosure provides an example computer-implemented method for generating feedback signals for training a machine-learned agent model. the example method can include obtaining an output of a machine-learned agent model, the output including a next state feature generated by the machine-learned agent model based on a sequence of preceding states. the example method can include processing, using a machine-learned reward model, the output and the sequence of preceding states to generate a quality indicator indicating a quality of the next state feature in view of the preceding states. the machine-learned reward model could be trained by retrieving reference data from a reference data source and computing one or more quality indicators in view of a respective training input and output(s), and the reference data. the example method can include outputting the quality indicator to a model trainer for updating the machine-learned agent model.
20250013937. Holiday Modeling in Forecasting_simplified_abstract_(google llc)
Inventor(s): Honglin Zheng of Seattle WA (US) for google llc, Haoming Chen of Kirkland WA (US) for google llc, Jun Ya Zhang of Kirkland WA (US) for google llc, Xi Cheng of Kirkland WA (US) for google llc, Weijie Shen of Mountain View CA (US) for google llc, Jiashang Liu of Kirkland WA (US) for google llc, Mingge Deng of Kirkland WA (US) for google llc, Amir Hossein Hormati of Seattle WA (US) for google llc
IPC Code(s): G06Q10/04, G06Q10/1057
CPC Code(s): G06Q10/04
Abstract: aspects of the disclosure are directed methods, systems, and computer readable media for in-database holiday effect modeling for time series forecasting. the modeling can be accurate, explainable, customizable, and scalable. machine learning models can receive a first dataset for time series data and a second dataset for configurable holiday data. the models can detect and model effects of each configurable holiday on one or more forecasts, effectively accumulating effects of overlapping holidays, to manage different levels of holiday modeling. holiday data can be customizable, including an ability to modify existing holidays and/or add new holidays, through one or more interfaces that can display default holiday information, combined holiday information based on both default and customizable holidays, effects of each holiday on forecasts, and accumulated effects of multiple holidays on forecasts.
20250014071. COMBATING FALSE INFORMATION WITH CROWDSOURCING_simplified_abstract_(google llc)
Inventor(s): Gang Wang of Frederick MD (US) for google llc, Yian Gao of Sunnyvale CA (US) for google llc
IPC Code(s): G06Q30/0241, H04L9/32
CPC Code(s): G06Q30/0248
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for combating false advertising using crowdsourcing. in one aspect, a method includes receiving a false digital component alert indicating that a digital component presented at a client device includes false information, validating the false digital component alert based on a public key to verify digital signature included in the false digital component alert matching the public key of stored attestation tokens specifying presentation and interaction data for the digital component. in response, adding the false digital component alert to an aggregated report. based on a false alert ratio, determining that a magnitude of validated false digital component alerts in the aggregated report meets a threshold, and triggering a false digital component mitigation response including providing a false information warning with the false digital component to one or more client devices or digital component provider.
20250014222. CALIBRATING CAMERA IN ELECTRONIC DEVICE_simplified_abstract_(google llc)
Inventor(s): Idris Syed Aleem of Kitchener (CA) for google llc, Zhiheng Jia of Sunnyvale CA (US) for google llc
IPC Code(s): G06T7/80, G06V40/16, H04N23/66, H04N23/85
CPC Code(s): G06T7/80
Abstract: a method performed by a server can include receiving, from a first computing device, multiple captured images that were captured by a camera, the multiple captured images including instances of a calibration image presented by a display included in a second computing device, the calibration image being a representation of a calibration image file; and based on the multiple captured images, calibrating the camera.
20250014236. View Synthesis Robust to Unconstrained Image Data_simplified_abstract_(google llc)
Inventor(s): Daniel Christopher Duckworth of Berlin (DE) for google llc, Alexey Dosovitskiy of Berlin (DE) for google llc, Ricardo Martin-Brualla of Seattle WA (US) for google llc, Jonathan Tilton Barron of Alameda CA (US) for google llc, Noha Radwan of Berlin (DE) for google llc, Seyed Mohammad Mehdi Sajjadi of Berlin (DE) for google llc
IPC Code(s): G06T11/00, G06T7/90
CPC Code(s): G06T11/001
Abstract: provided are systems and methods for synthesizing novel views of complex scenes (e.g., outdoor scenes). in some implementations, the systems and methods can include or use machine-learned models that are capable of learning from unstructured and/or unconstrained collections of imagery such as, for example, “in the wild” photographs. in particular, example implementations of the present disclosure can learn a volumetric scene density and radiance represented by a machine-learned model such as one or more multilayer perceptrons (mlps).
Inventor(s): Sangmoo Choi of Palo Alto CA (US) for google llc, Ka Ho Liu of San Diego CA (US) for google llc
IPC Code(s): G09G3/20, G04G21/08
CPC Code(s): G09G3/2007
Abstract: this document describes systems and techniques for mitigating a display artifact that may result from first frame rate effects at low luminance levels. for example, in an implementation, a computer-implemented method includes receiving display data to be presented on a display of an electronic device at a display driver. at the display driver, a luminance level of the display data is determined. responsive to determining at the display driver that the luminance level is below a threshold luminance level, a gray level is determined for one or more regions of the display data. responsive to determining at the display driver that the gray level for at least one region of the one or more regions is below a baseline gray level for the threshold luminance level, the gray level is increased to an adjusted gray level equal to at least the baseline gray level.
Inventor(s): Pu-sen Chao of Los Altos CA (US) for google llc, Alex Fandrianto of Los Gatos CA (US) for google llc
IPC Code(s): G10L15/16, G06N3/08, G10L15/08, G10L17/00, G10L21/0208
CPC Code(s): G10L15/16
Abstract: the presentation of an automated assistant response may be selectively pre-empted in response to a hot-word free utterance that is received during the presentation and that is determined to be likely directed to the automated assistant. the determination that the utterance is likely directed to the automated assistant may be performed, for example, using an utterance classification operation that is performed on audio data received during presentation of the response, and based upon such a determination, the response may be pre-empted with another response associated with the later-received utterance. in addition, the duration that is used to determine when a session should be terminated at the conclusion of a conversation between a user and an automated assistant may be dynamically controlled based upon when the presentation of a response has completed.
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc, Victor Carbune of Zurich (CH) for google llc
IPC Code(s): G10L15/22, G10L15/16
CPC Code(s): G10L15/22
Abstract: implementations set forth herein relate to an automated assistant that can jointly process spoken utterances that can include at least one corrective utterance and one utterance that may have been misinterpreted by the automated assistant. in this way, the automated assistant does not need to exclusively rely on the corrective utterance to determine a request of a user but, rather, can utilize data capturing any prior spoken utterance to more accurately determine the request. the automated assistant can process utterances jointly after determining that they are acoustically similar and/or received within a threshold duration of time. the joint processing can involve generating a single input, or multiple inputs, to characterize the series of utterances and processing the single input, or multiple inputs, with one or more neural network models and/or machine learning models. the automated assistant can then proactively correct any previous responses to misinterpreted utterances.
Inventor(s): Vikram Aggarwal of Palo Alto CA (US) for google llc, Moises Morgenstern Gali of San Francisco CA (US) for google llc
IPC Code(s): G10L15/22, G06F3/14, G10L15/26, G10L15/30, H04L67/01, H04L67/75, H04W4/02
CPC Code(s): G10L15/22
Abstract: methods, apparatus, systems, and computer-readable media are provided for isolating at least one device, from multiple devices in an environment, for being responsive to assistant invocations (e.g., spoken assistant invocations). a process for isolating a device can be initialized in response to a single instance of a spoken utterance, of a user, that is detected by multiple devices. one or more of the multiple devices can be caused to query the user regarding identifying a device to be isolated for receiving subsequent commands. the user can identify the device to be isolated by, for example, describing a unique identifier for the device. unique identifiers can be generated by each device of the multiple devices and/or by a remote server device. the unique identifiers can be presented graphically and/or audibly to the user, and user interface input. any device that is not identified can become temporarily unresponsive to certain commands, such as spoken invocation commands.
Inventor(s): Stacy Cronin of Berkeley CA (US) for google llc, Cliff Kuang of San Francisco CA (US) for google llc, Abraham Wallin of San Francisco CA (US) for google llc, Katrina Egert-Pecot of Sunnyvale CA (US) for google llc, Sean Joseph Klassen of Burlington VT (US) for google llc, Caleb Misclevitz of Portland OR (US) for google llc, Karan Patel of New York NY (US) for google llc, Ian Baker of San Francisco CA (US) for google llc, Simon Sok of Brooklyn NY (US) for google llc, Ryan Allen of Denver CO (US) for google llc
IPC Code(s): G10L15/22, G06F3/0482, G06F3/16, G10L15/18
CPC Code(s): G10L15/22
Abstract: some implementations relate to an automated assistant that can provide assistant suggestions based on content that the user has requested for the automated assistant to render at a computing device. in some instances, an assistant suggestion can correspond to a portion of the content that is not being rendered at the computing device but that is part of the content that the user is accessing. in other instances, an assistant suggestion can be based on data that can indicate how one or more users may have interacted with their automated assistant when viewing the content. therefore, an assistant suggestion can correspond to an assistant operation that may have been initialized by another user who had previously viewed the content. in some implementations, an arrangement of the assistant suggestions can be modified according to which part of the content a user is viewing and/or user distance.
20250014591. PRIVACY-PRESERVING SOCIAL INTERACTION MEASUREMENT_simplified_abstract_(google llc)
Inventor(s): Julian Maclaren of Nelson (NZ) for google llc, Karolis Misiunas of Zurich (CH) for google llc, Vahe Tshitoyan of Pleasanton CA (US) for google llc, Brian Foo of Union City CA (US) for google llc, Kelly Dobson of Santa Cruz CA (US) for google llc
IPC Code(s): G10L25/51, A61B5/024, G10L15/22, G10L21/028, G10L25/78, H04R1/04, H04R1/40, H04R3/00
CPC Code(s): G10L25/51
Abstract: various systems, devices, and methods for social interaction measurement that preserve privacy are presented. an audio signal can be captured using a microphone. the audio signal can be processed using an audio-based machine learning model that is trained to detect the presence of speech. the audio signal can be discarded such that content of the audio signal is not stored after the audio signal is processed using the machine learning model. an indication of whether speech is present within the audio signal can be output based at least in part on processing the audio signal using the audio-based machine learning model.
20250015839. User-Equipment-Coordination Set for a Wireless Network_simplified_abstract_(google llc)
Inventor(s): Jibing Wang of San Jose CA (US) for google llc, Erik Richard Stauffer of Sunnyvale CA (US) for google llc
IPC Code(s): H04B7/024, H04B7/06
CPC Code(s): H04B7/024
Abstract: this document describes techniques and apparatuses for a user equipment (ue)-coordination set for a wireless network. in aspects, a base station specifies a set of ues to form a ue-coordination set for joint transmission and reception of data intended for a target ue within the ue-coordination set. the base station selects one of the ues within the ue-coordination set to act as a coordinating ue for the ue-coordination set and transmits a request message that directs the coordinating ue to coordinate the joint transmission and reception of the data intended for the target ue. then, the base station transmits a downlink signal to each ue within the ue-coordination set. each ue within the ue-coordination set demodulates and samples the downlink signal and then forwards the samples to the coordinating ue, which combines the samples and processes the combined samples to provide decoded data.
20250015879. Systems and Methods for Satellite Messaging_simplified_abstract_(google llc)
Inventor(s): Dang Tu Nguyen of San Diego CA (US) for google llc, Sooraj Sasindran of San Diego CA (US) for google llc, Aishwarya Mallampati of Gilroy CA (US) for google llc, Sarah Elizabeth Kim of San Jose CA (US) for google llc
IPC Code(s): H04B7/185, H04W4/14
CPC Code(s): H04B7/18513
Abstract: a computer-implemented method is provided. the method includes enabling, by a mobile device, reception of satellite-communicated datagrams. the method also includes receiving, by the mobile device, a satellite datagram from a satellite after enabling reception of satellite-communicated datagrams. transmission of the satellite datagram is initiated from a nearby mobile device within a region of interest of the mobile device. the method also includes displaying, by the mobile device, a notification based on the satellite datagram.
20250015981. POST-QUANTUM CRYPTOGRAPHY FOR SECURE BOOT_simplified_abstract_(google llc)
Inventor(s): Kenneth Leon Root of Menlo Park CA (US) for google llc, Daniel Saul Fess of San Francisco CA (US) for google llc
IPC Code(s): H04L9/08, H04L9/06, H04L9/32
CPC Code(s): H04L9/0852
Abstract: in general, a computing device comprising a secure memory, a storage device, and a processor may be configured to implement the techniques. the secure memory may store a post-quantum cryptographic reference signature (pqcrs). the storage device may store bootloader stages, a list of classical cryptographic reference signatures (ccrs), and a pqc public key (pqcpk). the processor may, prior to executing a first bootloader stage, obtain the list of ccrs, the pqcrs, and the pqcpk. the processor may also apply a pqc algorithm with respect to the pqcrk and the list of ccrs to obtain a pqc verification signature (pqcvs), and responsive to the pqcvs matching the pqcrs, compare a first ccrs in the digitally signed list of ccrs to a first cc verification signature (ccvs) obtained based on the first bootloader stage. the processor may also, responsive to the first ccvs matching the first ccrs, execute the first bootloader stage.
Inventor(s): Guosen Yue of Edison NJ (US) for google llc, Jibing Wang of San Jose CA (US) for google llc
IPC Code(s): H04L25/02
CPC Code(s): H04L25/0204
Abstract: a receiver receives signals from a transmitter in subframes on subcarriers having orthogonal frequencies. a subset of the subframes include reference signals. the receiver generates a first channel estimate for a target subframe based on reference signals in the target subframe. the receiver also generates one or more second channel estimates for one or more other subframes based on one or reference signals in the other subframes. the receiver combines the first channel estimate and the one or more second channel estimates based on a frequency offset between the receiver and the transmitter to form a channel estimate of the target subframe. in some cases, the receiver performs joint estimates of a timing offset, a frequency offset, and a channel for the target subframe based on the reference signals, selected candidate timing offsets, selected candidate frequency offsets, and selected candidate channel estimates.
Inventor(s): Jeffrey P. Matthews of Longmont CO (US) for google llc, Lee R. Taylor of Boulder CO (US) for google llc
IPC Code(s): H04L41/0806, H04B10/116, H04W4/70, H04W4/80, H04W76/10, H04W84/12, H04W84/18
CPC Code(s): H04L41/0806
Abstract: an electronic device includes a first processor; a first commissioning element to communicate with external devices using wireless communication and a first memory storing programs for commissioning a target device onto a communication network. the communication network has configuration data including a network identifier and a network key. the programs provide a user interface for commissioning the target device. the target device includes a second processor, a second wireless radio, and a second commissioning element to receive the network configuration data. the target device decodes the network configuration data to commission the target device onto the communication network. the electronic device sends the network configuration data to the target device and receives confirmation that the target device has successfully connected to the communication network. the electronic device displays the success in a user interface.
Inventor(s): Rui Wang of Mountain View CA (US) for google llc, Keqiang He of Fremont CA (US) for google llc, Hassan Wassel of San Jose CA (US) for google llc, Junlan Zhou of Sunnyvale CA (US) for google llc, Shidong Zhang of San Jose CA (US) for google llc, Leonid Poutievski of Santa Clara CA (US) for google llc, Shaileshh Bojja Venkatakrishnan of Columbus OH (US) for google llc
IPC Code(s): H04L45/7453, H04L45/00, H04L45/125, H04L45/24
CPC Code(s): H04L45/7453
Abstract: methods are provided for mitigating hash correlation. in this regard, a hash correlation may be found between a first switch and a second switch in a network. in this network, a first egress port is to be selected among a first group of egress ports at the first switch for forwarding packets, and a second egress port is to be selected among a second group of egress ports at the second switch for forwarding packets, where the first group has a first group size and the second group has a second group size. upon finding the hash correlation, a new second group size coprime to the first group size may be selected, and the second group of egress ports may be mapped to a mapped group having the new second group size. the second switch may be configured to route packets according to the mapped group.
Inventor(s): Srinivas Vaduvatha of San Jose CA (US) for google llc, Hassan Mohamed Gamal Hassan Wassel of San Jose CA (US) for google llc, Ye Tang of Palo Alto CA (US) for google llc, Sarin Thomas of Sunnyvale CA (US) for google llc, Rakesh Gautam of Fremont CA (US) for google llc, Prashant Chandra of San Jose CA (US) for google llc, Anupam Jain of Bangalore (IN) for google llc
IPC Code(s): H04L47/122, H04L47/125
CPC Code(s): H04L47/122
Abstract: a custom processor core is provided, wherein the custom processor core may be used for congestion control in reliable transport protocols. the hardware architecture of the custom processor core allows for custom instructions, special register sets, and datapath enhancements for accelerating congestion control algorithms to achieve higher performance.
Inventor(s): Xuemei Ouyang of Redwood City CA (US) for google llc, Michael Scot Pate of Pleasanton CA (US) for google llc, Ethan Grabau of London (GB) for google llc, Dennis Yee of San Francisco CA (US) for google llc, Daniel Fernandes Barros of Porto (PT) for google llc, Chi Kin Benjamin Leung of Sunnyvale CA (US) for google llc
IPC Code(s): H04L65/613, H04L65/70
CPC Code(s): H04L65/613
Abstract: this document describes an accessory that may wirelessly connect to one or more host devices such that the accessory is able to receive content from two or more of the host devices at the same or substantially the same time. when each of the host devices is wirelessly coupled to the accessory, the accessory and each host device may determine a bit rate for the accessory to receive content from each host device. the accessory may receive content from a first host device at a first bit rate. based on the content received, the accessory may determine a new bit rate for other host devices.
Inventor(s): Tim Wantland of Bellevue WA (US) for google llc, Brandon Barbello of Mountain View CA (US) for google llc, Robert Berry of New York NY (US) for google llc
IPC Code(s): H04L67/63, G06N20/00
CPC Code(s): H04L67/63
Abstract: a computing system can be configured to input model input that includes context data into a machine-learned model and receive model output that describes one or more semantic entities referenced by the context data. the computing system can be configured to provide data descriptive of the semantic entity or entities to the computer application(s) and receive application output(s) respectively from the computing application(s) in response to providing the data descriptive of semantic entity or entities to the computer application(s). the application output(s) received from each computer application can describe available action(s) of the corresponding computer application with respect to the semantic entity or entities. the computing system can be configured to provide at least one indicator to a user that describes the available action(s) of the corresponding computer applications with respect to the semantic entity or entities.
Inventor(s): Yi-Chih Hsin of Zhubei (TW) for google llc, In Suk Chong of Mountain View CA (US) for google llc
IPC Code(s): H04N19/43, H04N19/127, H04N19/167, H04N19/176, H04N19/513, H04N19/56, H04N19/573
CPC Code(s): H04N19/43
Abstract: various hardware arrangements for use with a hardware decoder are described to perform motion vector (mv) refinement. a buffer stores pixel values for a first prediction block identified by a first initial mv and pixels defined by a first search area and stores a second prediction block identified by a second initial mv and pixels defined by a second search area. the first and second initial mvs were used for inter prediction of a block of image data. second hardware components determine, for multiple pixel locations defined by respective offsets, a respective difference value between the blocks shifted by the offsets. a third hardware component determines a minimum of the difference values to identify an offset mv for mv refinement, and a fourth hardware component outputs one or more refined values based on the offset mv to reconstruct a sub-block of the block.
20250016387. EPHEMERAL LEARNING OF MACHINE LEARNING MODEL(S)_simplified_abstract_(google llc)
Inventor(s): Françoise Beaufays of Mountain View CA (US) for google llc, Khe Chai Sim of Dublin CA (US) for google llc, Trevor Strohman of Sunnyvale CA (US) for google llc, Oren Litvin of New York City NY (US) for google llc
IPC Code(s): H04N21/233, G06F18/214, G06N20/00, H04N21/232
CPC Code(s): H04N21/233
Abstract: implementations disclosed herein are directed to ephemeral learning of machine learning (“ml”) model(s) based on gradient(s) generated at a remote system (e.g., remote server(s)). processor(s) of the remote system can receive stream(s) of audio data capturing spoken utterance(s) from a client device of a user. a fulfillment pipeline can process the stream(s) of audio data to cause certain fulfillment(s) of the spoken utterance(s) to be performed. meanwhile, a training pipeline can process the stream(s) of audio data to generate gradient(s) using unsupervised learning techniques. subsequent to the processing by the fulfillment pipeline and/or the training pipeline, the stream(s) of audio data are discarded by the remote system. accordingly, the ml model(s) can be trained at the remote system without storing or logging of the stream(s) of audio data by non-transient memory thereof, thereby providing more efficient training mechanisms for training the ml model(s) and also increasing security of user data.
20250016495. Impedance-Tuned Microphone Tunnel_simplified_abstract_(google llc)
Inventor(s): YuTing Tsai of New Taipei City (TW) for google llc
IPC Code(s): H04R1/28, H04R1/04, H04R1/08
CPC Code(s): H04R1/2807
Abstract: an impedance-tuned microphone tunnel for an electronic device is disclosed. the impedance-tuned microphone tunnel includes a ring-like structure having a central opening positioned within a microphone tunnel of an electronic device. the central opening of the ring-like structure has a diameter that is smaller than diameters of other central openings within the microphone tunnel. the ring-like structure may be used to tune an impedance of the microphone tunnel by varying the diameter of the central opening. in this way, the impedance of the microphone tunnel may be tuned to a frequency response target to reduce a resonant peak of the microphone tunnel. the ring-like structure may be coated with a non-stick material, such as with polyethylene terephthalate (pet), biaxially orientated polyethylene terephthalate (bopet), polyimide (pi), and the like.
Inventor(s): Chih-Hsiang Wu of Taoyuan city (TW) for google llc
IPC Code(s): H04W76/40, H04W76/12
CPC Code(s): H04W76/40
Abstract: a method, implemented in a user equipment (ue), for receiving multicast and/or broadcast services (mbs) data includes performing a protocol data unit (pdu) session establishment procedure with a core network (cn) to establish a pdu session to join an mbs session, including receiving, from a radio access network (ran), at least one first configuration for configuring radio resources for the pdu session; performing an mbs session join procedure with the cn to join the mbs session, including receiving, from the cn, an mbs session identifier and receiving, from the ran, at least one second configuration for configuring radio resources for the mbs session; receiving, from the cn via the ran, first mbs data of the mbs session in accordance with the at least one first configuration; and receiving, from the cn via the ran, second mbs data of the mbs session in accordance with the at least one second configuration.
- Google LLC
- B25J9/16
- B25J19/02
- G05B19/048
- CPC B25J9/1697
- Google llc
- G01C21/36
- G01C21/34
- CPC G01C21/3617
- CPC G01C21/3647
- G01C21/00
- B60W40/06
- B60W40/076
- B60W50/14
- G01S7/48
- G06V10/80
- G06V20/56
- CPC G01C21/3807
- G01M11/00
- CPC G01M11/33
- G06F3/01
- G06F3/0346
- CPC G06F3/017
- G06F3/041
- G06N20/00
- CPC G06F3/04186
- G06F3/0482
- G06F3/04845
- G06F16/583
- G06F16/951
- G06F40/205
- CPC G06F3/0482
- G06F3/16
- G06F3/0484
- G06F16/248
- G06F16/28
- G06F16/332
- G06F16/338
- CPC G06F3/167
- G06F7/544
- G06F7/50
- G06F7/533
- CPC G06F7/5443
- G06F8/35
- G06F8/34
- G10L13/08
- G10L15/22
- CPC G06F8/35
- G06F8/41
- CPC G06F8/41
- G06F9/54
- G06F3/04847
- G06F9/451
- CPC G06F9/542
- G06F16/17
- G06F16/11
- G06F16/14
- G06F16/188
- CPC G06F16/1734
- G06F16/23
- G06F16/26
- CPC G06F16/2365
- G06F21/62
- CPC G06F21/6218
- G06F40/284
- CPC G06F40/284
- G06N3/08
- G06F18/2415
- G06N3/04
- G06N3/084
- G06V10/70
- G06V10/82
- CPC G06N3/08
- G06N5/01
- CPC G06N5/01
- CPC G06N20/00
- G06Q10/04
- G06Q10/1057
- CPC G06Q10/04
- G06Q30/0241
- H04L9/32
- CPC G06Q30/0248
- G06T7/80
- G06V40/16
- H04N23/66
- H04N23/85
- CPC G06T7/80
- G06T11/00
- G06T7/90
- CPC G06T11/001
- G09G3/20
- G04G21/08
- CPC G09G3/2007
- G10L15/16
- G10L15/08
- G10L17/00
- G10L21/0208
- CPC G10L15/16
- CPC G10L15/22
- G06F3/14
- G10L15/26
- G10L15/30
- H04L67/01
- H04L67/75
- H04W4/02
- G10L15/18
- G10L25/51
- A61B5/024
- G10L21/028
- G10L25/78
- H04R1/04
- H04R1/40
- H04R3/00
- CPC G10L25/51
- H04B7/024
- H04B7/06
- CPC H04B7/024
- H04B7/185
- H04W4/14
- CPC H04B7/18513
- H04L9/08
- H04L9/06
- CPC H04L9/0852
- H04L25/02
- CPC H04L25/0204
- H04L41/0806
- H04B10/116
- H04W4/70
- H04W4/80
- H04W76/10
- H04W84/12
- H04W84/18
- CPC H04L41/0806
- H04L45/7453
- H04L45/00
- H04L45/125
- H04L45/24
- CPC H04L45/7453
- H04L47/122
- H04L47/125
- CPC H04L47/122
- H04L65/613
- H04L65/70
- CPC H04L65/613
- H04L67/63
- CPC H04L67/63
- H04N19/43
- H04N19/127
- H04N19/167
- H04N19/176
- H04N19/513
- H04N19/56
- H04N19/573
- CPC H04N19/43
- H04N21/233
- G06F18/214
- H04N21/232
- CPC H04N21/233
- H04R1/28
- H04R1/08
- CPC H04R1/2807
- H04W76/40
- H04W76/12
- CPC H04W76/40
