Google LLC patent applications on January 2nd, 2025
Patent Applications by Google LLC on January 2nd, 2025
Google LLC: 55 patent applications
Google LLC has applied for patents in the areas of G06N20/00 (5), G06N3/08 (4), G06F16/332 (3), A61B5/00 (3), G10L17/22 (3) G10L17/22 (3), G06F40/40 (2), G06N10/70 (2), G06N20/00 (2), G06T7/97 (2)
With keywords such as: data, user, device, content, based, input, processing, application, methods, and respective in patent application abstracts.
Patent Applications by Google LLC
Inventor(s): Dongeek Shin of Santa Clara CA (US) for google llc, Brandon Barbello of Mountain View CA (US) for google llc, Shwetak Patel of Seattle WA (US) for google llc, Anupam Pathak of San Carlos CA (US) for google llc, Michael Dixon of Sunnyvale CA (US) for google llc
IPC Code(s): A61B5/0507, A61B5/00, A61B5/024, A61B5/08, A61B5/11, G01S13/28
CPC Code(s): A61B5/0507
Abstract: various arrangements for performing radar-based measurement of vital signs. waveform data may be received then filtered of data indicative of static objects to obtain motion-indicative waveform data. the motion-indicative waveform data may be analyzed to determine one or more frequencies of movement present within the motion-indicative waveform data. a spectral analysis may be performed on the motion-indicative waveform data to determine a spectral-analysis state of a monitored region. the spectral-analysis state of the monitored region may be determined to match a predefined spectral-analysis state during which vital sign monitoring is permitted. one or more vital signs of a monitored user present within the monitored region may be determined and output based on analyzing the motion-indicative waveform data.
Inventor(s): Sarah Ann Stokes Kernasovskiy of San Francisco CA (US) for google llc, Hamed Vavadi of Castro Valley CA (US) for google llc, Peter Richards of San Francisco CA (US) for google llc, Conor Joseph Heneghan of Campbell CA (US) for google llc, Lindsey Sunden of San Francisco CA (US) for google llc, Hao-Wei Su of Cambridge MA (US) for google llc, Logan Alexander Niehaus of Colorado Springs CO (US) for google llc
IPC Code(s): A61B5/1455, A61B5/00
CPC Code(s): A61B5/14552
Abstract: the present disclosure provides computer-implemented methods, systems, and devices for estimating the oxygen saturation levels of the blood of a user. a wearable computing device emits using one or more green light sources, light towards a skin of a user at a green wavelength. the wearable computing device further emits, using one or more red light sources, light towards a skin of a user at a red wavelength. the wearable computing device further emits, using one or more infrared light sources, light towards a skin of a user at an infrared wavelength. the wearable computing device further detects an intensity of green light, red light, and infrared light emitted from the skin of a user. the wearable computing device further determines an estimated oxygen saturation level.
Inventor(s): Ming-Zher Poh of Belmont MA (US) for google llc, John Weston Hughes of Palo Alto CA (US) for google llc, Paolo Di Achille of Medford MA (US) for google llc, Shun Liao of Cambridge MA (US) for google llc
IPC Code(s): A61B5/00, A61B5/024, A61B5/318
CPC Code(s): A61B5/7275
Abstract: a computer-implemented method for detecting a cardiac dysfunction in a user includes obtaining, from a sensor, photoplethysmogram (ppg) signals indicative of a cardiac rhythm of the user. the computer-implemented method further includes processing, in a computing device, the ppg signals to generate a cardiac dysfunction prediction for the user based, at least in part, on the ppg signals. the computer-implemented method further includes providing, via an annunciator, the cardiac dysfunction prediction for the user as an output.
20250002205. Lip Feature in Tube Packaging Structures_simplified_abstract_(google llc)
Inventor(s): Nicole Danielle Hermann of Redwood City CA (US) for google llc
IPC Code(s): B65D5/38, B65D6/06
CPC Code(s): B65D5/38
Abstract: this document describes systems directed at a lip feature in tube packaging structures. in aspects, a system includes a sleeve portion having a hollow tube structure. the system also includes an open-faced enclosure (a box) configured to be slidably placed inside the sleeve portion such that at least a portion of the open-faced enclosure is disposed within the sleeve portion. the system further includes a lip feature configured to fold from a first position to a second position such that when the open-faced enclosure is slidably placed inside the sleeve portion, the lip feature folds from the first position to the second position and reverts back to the first position once the open-faced enclosure is at least partially disposed within the sleeve portion. through such techniques, the lip feature can prevent boxes from falling out of tube structures.
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): G01C21/36, G06F40/30, G06N5/022
CPC Code(s): G01C21/3608
Abstract: the present disclosure is generally related to systems and methods of interfacing among multiple applications in a networked computer environment. a data processing system can access a navigation application to retrieve point locations within a reference frame corresponding to a geographic region displayed in a viewport of the navigation application. each point location can have an identifier. the data processing system can parse an input audio signal to identify a request and a referential word. the data processing system can identify a point location within the reference frame based on the referential word parsed from the input audio signal and the identifier for the point location. the data processing system can generate an action data structure including the point location identified. the data processing system can transmit the action data structure to the navigation application to initiate a navigation guidance process using the point location.
Inventor(s): Herschel Watkins of Sausalito CA (US) for google llc
IPC Code(s): G01N33/543, G01N33/84
CPC Code(s): G01N33/54386
Abstract: the present disclosure provides an assay device for determining a concentration of sodium in a sample. the device includes a separation membrane and a detection membrane located downstream from the separation membrane. the detection membrane includes a complex comprising an ion and a cryptand having an affinity for the ion. the detection membrane also includes an ion-dependent dye. further, the ion-dependent dye is configured to elicit a quantifiable response after the ion binds to the ion-dependent dye after its release from the cryptand after sodium from the blood fluid sample is introduced to the detection membrane and binds to the cryptand. additionally, the quantifiable response corresponds to an amount of the ion bound to the ion-dependent dye, which corresponds to a concentration of sodium present in the sample. the present disclosure also provides methods for using an assay device to quantify the amount of sodium present in the sample.
20250004021. DEVICE HAVING INTEGRATED CURRENT SENSORS_simplified_abstract_(google llc)
Inventor(s): Amirpouya Kavousian of San Jose CA (US) for google llc, Nathan Michael Pletcher of Mountain View CA (US) for google llc
IPC Code(s): G01R19/25, G01R19/00, G01R19/10, G01R22/08
CPC Code(s): G01R19/2513
Abstract: disclosed herein are integrated current sensors and methods for sensing and measuring current consumption of electronic devices. the electronic device can comprise: a plurality of layers within a power delivery network of the device, each tile comprising circuitry for performing one or more functions; a plurality of probes, each probe having a pair of inputs connected to portions of one or more layers having a voltage drop, wherein each probe is configured to convert a respective differential voltage to a representative current passing through the one or more layers; a capacitor that is configured to integrate the respective currents passing through the one or more layers to an integrated voltage; and a converter that is configured to generate a measure of current consumed by the device based on the integrated voltage.
20250004289. MULTIPLE-SOURCE LASER DISPLAY SYSTEM_simplified_abstract_(google llc)
Inventor(s): Aurelien Jean Francois David of San Francisco CA (US) for google llc, Benjamin Wales of Waterloo (CA) for google llc, Bergen Albert Fletcher of St. Jacobs (CA) for google llc, Daniel Adema of Kitchener (CA) for google llc, Daniel J. Effinger of Squamish (CA) for google llc, Vance R. Morrison of Kitchener (CA) for google llc, Patrick F. Brinkley of San Mateo CA (US) for google llc, Ian Andrews of Kitchener (CA) for google llc, Stuart James Myron Nicholson of Waterloo (CA) for google llc, Shreyas Potnis of Kitchener (CA) for google llc
IPC Code(s): G02B27/10, G02B26/08, G02B27/01, G02B27/12
CPC Code(s): G02B27/1006
Abstract: a display system includes one or more low-power laser diodes, each producing an emission. the emissions are directed to an optical element that affects the direction or divergence of the emissions. the optical element redirects the emissions toward a steering element such as a mems-actuated mirror, or a combination of such mirrors. the steering element directs the emissions toward the incoupler of a waveguide acting as an optical combiner. the emissions propagate through the waveguide and are extracted by an outcoupler in the direction of an observer. by scanning the direction of the beam-steering element along one or several directions, an image may be formed.
Inventor(s): Daniel J. Effinger of Squamish (CA) for google llc, Daniel Adema of Kitchener (CA) for google llc
IPC Code(s): G03B21/20, G02B27/01
CPC Code(s): G03B21/208
Abstract: a micro-projection system for use in small electronic devices can benefit from an optical assembly equipped with light-absorbing apertures. the light-absorbing apertures can aid in reducing or eliminating stray light and associated ghost images from appearing on the display of the projection system. modular units that include laminated stacks of such apertures, along with spacers, can be inserted into air gaps within the optical assembly. such stacked units can be made cost effective to manufacture in high volume.
Inventor(s): Sujit Varghese of New York NY (US) for google llc, Barine Tee of East Stroudsburg PA (US) for google llc
IPC Code(s): G06F3/0482, G06F3/04817, G06F3/0488, G06F3/04883, G06F3/04886, G06F40/166
CPC Code(s): G06F3/0482
Abstract: technology for a touchscreen device that enhances the presentation of menus. in one example, the technology may involve presenting a set of menu icons at a location on a touchscreen device, detecting a rotating interaction associated with the touchscreen device, selecting, based on the rotating interaction, a menu icon from the set of menu icons comprising different menu options, presenting additional menu icons as a group of menu icons adjacent to the location of the menu icon, wherein the additional menu icons comprise a first menu icon to perform a first operation on a screen of the touchscreen device, and a second menu item to perform a second operation on the screen of the touchscreen device, detecting a selection of the first menu icon of the additional menu icons, performing the first operation on the screen of the touchscreen device, detecting a selection of the second menu icon of the additional menu icons, and performing the second operation on the screen of the touchscreen device.
20250004628. MEDIA INPUT CONTROL SETTINGS_simplified_abstract_(google llc)
Inventor(s): Megha Malpani of San Francisco CA (US) for google llc, Ryosuke Matsumoto of Dublin CA (US) for google llc, Guoxing Zhao of South Hurstville (AU) for google llc, Jonathon Leigh Napper of Pymble (AU) for google llc, Megan L. Fu of San Francisco CA (US) for google llc, Nikhil Siva Subash of San Jose CA (US) for google llc, Gary Hyun Jin Kim of San Mateo CA (US) for google llc, Alex Newcomer of San Francisco CA (US) for google llc, Joseph Kurachi Luk of Hokkaido (JP) for google llc
IPC Code(s): G06F3/04847
CPC Code(s): G06F3/04847
Abstract: a method may determine that an application with access to a media input resource has been launched by a user. a method may in response to determining that the application is launched, initiate a display of a settings user interface including a control for modifying a media input resource setting accessible via the operating system. a method may control transmission of a media output to the application based on the media input resource setting.
20250004717. Semi-Constant Operand Multipliers_simplified_abstract_(google llc)
Inventor(s): Herman Henry Schmit of Marina CA (US) for google llc
IPC Code(s): G06F7/523, G06F7/50
CPC Code(s): G06F7/523
Abstract: aspects of the disclosure are directed to multiplier circuits for semi-constant operand multiplication. the multiplier circuits can receive operands for multiplication. the multiplier circuits can convert one of the operands to a set of configuration bits, such as canonical signed digit representation (csd). the multiplier circuits can process the other operand using the set of configuration bits to generate a multiplication output.
Inventor(s): Keun Soo Yim of () for google llc
IPC Code(s): G06F8/61
CPC Code(s): G06F8/61
Abstract: techniques for filtering third-party content that is to be provided via a mobile computing device based on which applications are already installed on that mobile computing device are provided. an example method includes determining, by a server, a set of candidate mobile applications, including first and second applications, each associated with respective third-party content presentable on a mobile computing device; in response to determining that the first application is absent from a set of applications installed on the mobile computing device: sending, by the server to the mobile computing device, third-party content associated with the first application; and in response to determining that the second application is included in the set of applications installed on the mobile computing device: refraining from sending third-party content associated with the second application to the mobile computing device.
20250004752. REAL-TIME VERSION ROLLBACK_simplified_abstract_(google llc)
Inventor(s): David Shangni Li of Emeryville CA (US) for google llc, Dan Chen of Bellevue WA (US) for google llc, Ligeng Dong of Bellevue WA (US) for google llc, Zachary Warneke of Bellevue WA (US) for google llc, Crystal Ying Wang of San Francisco CA (US) for google llc, Shumeng Gu of Kirkland WA (US) for google llc
IPC Code(s): G06F8/658, G06F11/14, G06F16/14
CPC Code(s): G06F8/658
Abstract: disclosed implementations for rolling back a web-based application to a prior version. in response to receiving an intent to rollback a web-based application, a prior version of the web-based application that meets a rollback condition is identified. a next version of the web-based application is generated based on the prior version of the web-based application. the next version of the web-based application is published to complete the rollback of the web-based application.
Inventor(s): Lisa Michelle Jakobovits of San Carlos CA (US) for google llc, Jonathan James Mulligan of San Francisco CA (US) for google llc, Mert Dikmen of Belmont CA (US) for google llc, Xinlong Bao of Los Altos CA (US) for google llc, John Chen of Mountain View CA (US) for google llc, Jing Wang of Mountain View CA (US) for google llc
IPC Code(s): G06F9/451, G06N20/00
CPC Code(s): G06F9/451
Abstract: example embodiments of the present disclosure provide for an example method. the example method includes obtaining session data descriptive of a plurality of user sessions, the plurality of user sessions respectively including an interaction with an input element rendered at a user device and a request for a resource associated with the input element. the example method includes obtaining, using a first machine-learned model, a plurality of weights associated with the plurality of user sessions by, for a respective user session of the plurality of user sessions: inputting, to the first machine-learned model, data descriptive of one or more characteristics of the respective user session; and obtaining, from the first machine-learned model, a respective weight of the plurality of weights, the respective weight indicative of an incremental probability of the request conditioned on rendering of the input element. the example method includes updating, based on the plurality of weights, a second machine-learned model to optimize candidate proposals for participation in a real-time content selection process for populating a user interface with one or more selected input elements.
Inventor(s): Ozgur Ozel of Sunnyvale CA (US) for google llc, Siddhi Ram Tadpatrikar of Los Altos CA (US) for google llc, Cleophus Anderson Davis, IV of Mountain View CA (US) for google llc, Jonah Benjamin Wasserman of Mountain View CA (US) for google llc, Terrine Balayut Forman of San Francisco CA (US) for google llc, Azmat Ali Pasha of Saint Paul MN (US) for google llc, Samuel James Stow of Buderim (AU) for google llc, David Andrew Brown of Huntington Beach CA (US) for google llc, Eric Alan Burns of Sunnyvale CA (US) for google llc, Eric Daniel Leichtenschlag of Burlingame CA (US) for google llc, William Aaron Simmons of Mill Valley CA (US) for google llc, Catherine Goings Lin of Irvine CA (US) for google llc, Mengke Wang of Sunnyvale CA (US) for google llc, Qian Li of Campbell CA (US) for google llc, Edward Eric Weng of Sunnyvale CA (US) for google llc
IPC Code(s): G06F11/34, G06F3/01
CPC Code(s): G06F11/3438
Abstract: an example method includes receiving, by one or more processing circuits, a registration request comprising an identifier and an activation gesture associated with a mobile application on a mobile device. the example method includes sending, by the one or more processing circuits to the mobile application on the mobile device, a notification indicating the mobile device is registered. the example method includes receiving, by the one or more processing circuits, a content item test request for content items in a specific content network. the example method includes testing, by the one or more processing circuits, the content items on the specific content network. the example method includes transmitting, by the one or more processing circuits to the mobile application on the mobile device, content event logs comprising debugging information of the content items during the testing on the content network.
20250004956. ON-CHIP INTERCONNECT FOR MEMORY CHANNEL CONTROLLERS_simplified_abstract_(google llc)
Inventor(s): Rahul Nagarajan of Sunnyvale CA (US) for google llc, Hema Hariharan of Mountain View CA (US) for google llc
IPC Code(s): G06F13/16, G06F12/02
CPC Code(s): G06F13/1668
Abstract: methods, systems, and apparatus, including computer-readable media, are described for an integrated circuit that accelerates machine-learning computations. the circuit includes processor cores that each include multiple channel controllers; an interface controller for coupling each channel controller to any memory channel of a system memory; and a fetch unit in each channel controller. each fetch is configured to: receive channel data that encodes addressing information; obtain, based on the addressing information, data from any memory channel of the system memory using the interface controller; and write the obtained data to a vector memory of the processor core via the corresponding channel controller that includes the respective fetch unit.
20250005034. Cloud Platform Based Management of Data Centers_simplified_abstract_(google llc)
Inventor(s): Ramasimha Rangaraju of Bengaluru (IN) for google llc, Johnson Plathottam Jose of Bengaluru (IN) for google llc, Srivats Ramaswami of Saratoga CA (US) for google llc, Sandesh Dayanand Raikar of Menlo Park CA (US) for google llc
IPC Code(s): G06F16/25
CPC Code(s): G06F16/258
Abstract: aspects of the disclosure are directed to a cloud based data center management platform. the data center management platform collects telemetry data associated with various data centers from heterogeneous data sources and transforms the heterogeneous telemetry data into a homogeneous data set. the data center management platform generates metrics from the homogeneous data set for monitoring the various data centers. the data center management platform can trigger an alert from monitoring the metrics and can also predict potential future alerts from the metrics.
Inventor(s): Jian Wei Leong of San Francisco CA (US) for google llc, Nicu Cornea of San Jose CA (US) for google llc, Maya Tekke Anant of Sunnyvale CA (US) for google llc
IPC Code(s): G06F16/432, G06F9/38, G06F16/23, G06F16/242, G06F16/25
CPC Code(s): G06F16/433
Abstract: the present disclosure is generally related to a data processing system to coordinate parallel processing of audio queries across multiple devices. a data processing system can receive an audio input signal detected the display device and parse the audio input signal to identify an entity. the data processing system can transmit a query command to the display device to cause a multimedia content application to perform a search for the entity. the data processing system can access at least one of an address database and a multimedia content provider to identify a reference address for the entity. the data processing system can provide the reference address for the entity to cause the display device to present a content selection interface. the content selection interface can include an element for the reference address, prior to completion of the search for the entity performed by the multimedia content application.
Inventor(s): Justin Lewis of Marina Del Rey CA (US) for google llc, Scott Davies of Santa Monica CA (US) for google llc
IPC Code(s): G06F16/9032, G06F16/955, G10L15/26, G10L15/30, G10L15/32
CPC Code(s): G06F16/90332
Abstract: methods, apparatus, systems, and computer-readable media are provided for transferring dialog sessions between devices using deep links. the dialog sessions can correspond to interactions, mediated by an automated assistant, between a user and a third party application. during the dialog session, a user can request that the dialog session be transferred to a different device, for example, to interact with the third party application through a different modality. in response, the automated assistant and/or the third party application can generate a link that can be transferred to the transferee device to allow the transferee device to seamlessly take over the dialog session. in this way, computational resources and electrical power can be preserved by not requiring a recipient device to re-process natural language inputs previously provided during the dialog session.
Inventor(s): Wei HUANG of Kirkland WA (US) for google llc, Arne Mauser of Los Altos Hills CA (US) for google llc
IPC Code(s): G06F16/9535, G06F16/906, G06N20/00, H04L67/306, H04L67/50, H04L67/55
CPC Code(s): G06F16/9535
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting and distributing digital components based on predicted user attributes of users are described. in one aspect, a method includes obtaining data indicating content categories of content of the content pages accessed by the user during the user visits. a determination is made for an aggregate measure of each content category based on a quantity of user visits to content pages of the electronic resource of the publisher that included content classified as belonging to the content category. user attribute prediction data indicating previously predicted user attributes of the user is obtained. user attributes are predicted for the current visit of the user to the electronic resource of the publisher that is further used to select digital components for display with the electronic resource on a client device during the current visit.
Inventor(s): Animesh Nandi of Cupertino CA (US) for google llc, Alessandro Epasto of New York NY (US) for google llc
IPC Code(s): G06F21/56
CPC Code(s): G06F21/56
Abstract: for a plurality of iterations, entity detection information is obtained from one or more client computing devices. the entity detection information includes (a) information that indicates whether an entity detected at the client computing device is malicious, and (b) information that associates the entity with a particular subspace of a plurality of subspaces of an embedding space. the entity detection information received over the plurality of iterations is aggregated to obtain aggregated threat information, wherein the aggregated threat information is descriptive of a number of malicious entities and a total number of entities detected for each subspace of the plurality of subspaces. based on the entity detection information subspace classification information is generated that identifies a first subspace of the plurality of subspaces as being a malicious subspace associated with malicious entities.
Inventor(s): Jiayu Peng of Sunnyvale CA (US) for google llc, Michael James Wurm of Morristown NJ (US) for google llc, Chenwei Wang of Mountain View CA (US) for google llc, Pasin Manurangsi of Bangkok (TH) for google llc, Adam Benjamin Gelernter Sealfon of New York NY (US) for google llc, Jakub Tetek of Mountain View CA (US) for google llc, Matthew Tran Clegg of Los Angeles CA (US) for google llc
IPC Code(s): G06F21/62
CPC Code(s): G06F21/62
Abstract: systems and methods for generating and maintaining differential privacy while providing accurate values can include obtaining a plurality of noise-added values, processing the plurality of noise-added values to determine a predicted value. the plurality of noise-added value may be utilized to determine one or more accuracy values that can be compared to a threshold to determine if more data is to be obtained and processed before providing a predicted value.
Inventor(s): Tuan Nguyen of San Jose CA (US) for google llc, Sergei Volnov of London (GB) for google llc, William A. Truong of San Jose CA (US) for google llc, Yunfan Ye of Sunnyvale CA (US) for google llc, Sana Mithani of Plantation FL (US) for google llc, Neel Joshi of Newcastle WA (US) for google llc, Alexey Galata of San Jose CA (US) for google llc, Tzu-Chan Chuang of San Francisco CA (US) for google llc, Liang-yu Chen of Sunnyvale CA (US) for google llc, Qiong Huang of San Jose CA (US) for google llc, Krunal Shah of Mountain View CA (US) for google llc, Sai Aditya Chitturu of Sunnyvale CA (US) for google llc
IPC Code(s): G06F40/40, G06F40/30
CPC Code(s): G06F40/40
Abstract: implementations relate to leveraging large language model(s) (llms) and vision language model(s) (vlms) to facilitate human-to-computer dialogs. in various implementations, one or more digital images may be processed using one or more vlms to generate vlm output indicative of a state of an environment. an llm prompt may be assembled based on the vlm output and a natural language input. the llm prompt may be processed using one or more llms to generate content that is responsive to the natural language input. the content that is responsive to the natural language input may subsequently be rendered at one or more output devices.
20250005303. GENERATIVE SUMMARIES FOR SEARCH RESULTS_simplified_abstract_(google llc)
Inventor(s): Matthew K. Gray of Reading MA (US) for google llc, John Blitzer of Mountain View CA (US) for google llc, Corinn Herrick of Mountain View CA (US) for google llc, Srinivasan Venkatachary of Sunnyvale CA (US) for google llc, Jayant Madhavan of San Francisco CA (US) for google llc, Sam Oates of Cambridge MA (US) for google llc, Phiroze Parakh of San Jose CA (US) for google llc, Aditya Shah of Mountain View CA (US) for google llc, Mahsan Rofouei of Menlo Park CA (US) for google llc, Ibrahim Badr of Zurich (CH) for google llc
IPC Code(s): G06F40/40, G06F16/332
CPC Code(s): G06F40/40
Abstract: at least selectively utilizing a large language model (llm) in generating a natural language (nl) based summary to be rendered in response to a query. in some implementations, in generating the nl based summary additional content is processed using the llm. the additional content is in addition to query content of the query itself and, in generating the nl based summary, can be processed using the llm and along with the query content—or even independent of the query content. processing the additional content can, for example, mitigate occurrences of the nl based summary including inaccuracies and/or can mitigate occurrences of the nl based summary being over-specified and/or under-specified.
20250005322. MULTI-TASK RECURRENT NEURAL NETWORKS_simplified_abstract_(google llc)
Inventor(s): Milad Olia Hashemi of San Francisco CA (US) for google llc, Jamie Alexander Smith of Boston MA (US) for google llc, Kevin Jordan Swersky of Toronto (CA) for google llc
IPC Code(s): G06N3/044, G06F3/06, G06N3/08
CPC Code(s): G06N3/044
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, relating to multi-task recurrent neural networks. one of the methods includes maintaining data specifying, for a recurrent neural network, a separate internal state for each of a plurality of memory regions; receiving a current input; identifying a particular memory region of the memory access address defined by the current input; selecting, from the internal states specified in the maintained data, the internal state for the particular memory region; processing, in accordance with the selected internal state for the particular memory region, the current input in the sequence of inputs using the recurrent neural network to: generate an output, the output defining a probability distribution of a predicted memory access address, and update the selected internal state of the particular memory region; and associating the updated selected internal state with the particular memory region in the maintained data.
20250005354. Learning Strides in Convolutional Neural Networks_simplified_abstract_(google llc)
Inventor(s): Neil Zeghidour of Paris (FR) for google llc, Rachid Riad of Paris (FR) for google llc, Olivier Teboul of Paris (FR) for google llc, David Grangier of Mountain View CA (US) for google llc
IPC Code(s): G06N3/08
CPC Code(s): G06N3/08
Abstract: a method of training a machine learning model, includes receiving training data for the machine learning model, wherein the training data comprises a plurality of batches. the method also includes applying a downsampling layer of the machine learning model to the plurality of batches of the training data to determine a stride comprising a learnable parameter for the downsampling layer. applying the downsampling layer of the machine learning model to a batch of the training data includes projecting an input in a spatial domain to a fourier domain, constructing a mask in the fourier domain based on a current value of the stride and dimensions of the input, applying the mask as a low-pass filter to the projected input to produce a tensor in the fourier domain, cropping the tensor based on the mask, and transforming the cropped tensor to the spatial domain.
Inventor(s): Craig Gidney of Goleta CA (US) for google llc
IPC Code(s): G06N10/70, G06N10/20, G06N10/40
CPC Code(s): G06N10/70
Abstract: methods, systems, and apparatus for encoding a magic state in a surface code patch of physical qubits with a target distance. in one aspect, a method includes performing a first surface code cycle on a surface code patch of physical qubits with an initial distance to encode the magic state into the surface code patch. performing the first surface code cycle introduces a hook error associated with a four-body stabilizer on a qubit included in the surface code patch, where the hook error rotates a logical observable of the surface code patch. further, performing the first surface code cycle includes initializing the qubit in the magic state. one or more rounds of error detection are performed on the surface code patch that encodes the magic state. the surface code patch is expanded to the target distance based on results of the one or more rounds of error detection.
Inventor(s): Michael Gabriel Newman of Palo Alto CA (US) for google llc, Kevin Satzinger of Goleta CA (US) for google llc, Daniel Thomas Sank of Goleta CA (US) for google llc, Nathan Cody Jones of Santa Barbara CA (US) for google llc
IPC Code(s): G06N10/70, G06N10/60
CPC Code(s): G06N10/70
Abstract: methods, systems, and apparatus for enhanced decoding using in-phase and quadrature information. in one aspect, a method includes obtaining in-phase and quadrature values for multiple measurement operations in a quantum error correction code for a quantum computation; classifying measurement outcomes of the multiple measurement operations using respective in-phase and quadrature values; generating a detector graph of nodes and edges, wherein the detector graph labels detection events that occur in the classified measurement outcomes; assigning weights to the edges of the detector graph using posterior probability distributions of the classified measurement outcomes to generate a weighted detector graph; and executing a decoding process on the weighted detector graph to compute a decoding output of the decoding process, wherein the decoding output predicts an occurrence of errors in the quantum computation.
20250005439. Online Learning with Component Factorized Models_simplified_abstract_(google llc)
Inventor(s): Julian Paul Grady of Pittsburgh PA (US) for google llc, Satyaki Mahalanabis of Sunnyvale CA (US) for google llc
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: systems and methods for improving accuracy of machine-learning models are described herein. the system can obtain, by one or more computing devices, component data from a donor model. the donor model can be an online model. the component data can have a first embedding. the system can store the component data in a persistent database. the component data can be input data for a plurality of recipient models. the system can receive from the first recipient model of the plurality of recipient models, a first request for the first embedding. the system can transmit, from the persistent database to the first recipient model, the first embedding. the system can process, using the first recipient model, the first embedding to generate a first recipient output.
Inventor(s): Ehsan Amid of Mountain View CA (US) for google llc, Christopher James Fifty of Churchville MD (US) for google llc, Manfred Klaus Warmuth of Santa Cruz CA (US) for google llc, Rohan Anil of Lafayette CA (US) for google llc
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: provided is an approach for knowledge distillation based on exporting principal components approximations (e.g., bregman representations) of one or more layer-wise representations of the teacher model. in particular, the present disclosure provides an extension to the original bregman pca formulation by incorporating a mean vector and orthonormalizing the principal directions with respect to the geometry of the local convex function around the mean. this extended formulation allows viewing the learned representation as a dense layer, thus casting the problem as learning the linear coefficients of the compressed examples, as the input to this layer, by the student network. example empirical data indicates that example implementations of the approach improve performance when compared to typical teacher-student training using soft labels.
20250005656. Uncertainty Informed Automatic Bidding_simplified_abstract_(google llc)
Inventor(s): Alexander Kerelsky of New York NY (US) for google llc, Sergiu Ion Goschin of Mountain View CA (US) for google llc, Dong Lin of Mountain View CA (US) for google llc, Jie Han of San Jose CA (US) for google llc
IPC Code(s): G06Q30/08
CPC Code(s): G06Q30/08
Abstract: this technology generally relates to a method for leveraging a measure of bidding model uncertainty to directly improve automatic bidding. the methods may include measuring the inherent uncertainty of automatic bidding models using techniques, such as quantile regression. further, the measure of bidding model uncertainty may be incorporated into bid formulas to inform the generated bids for an auction. the method may be further formulated to modify the bids to be more conservative when the bidding model uncertainty is higher. once the uncertainty level of the bidding model is reduced to a more stable level, the bidding method will resume generating bids with more efficiency.
Inventor(s): Neil Matthew Tinmouth Houlsby of Zurich (CH) for google llc, Sylvain Gelly of Aix-en-Provence (FR) for google llc, Jakob D. Uszkoreit of Berlin (DE) for google llc, Xiaohua Zhai of Zurich (CH) for google llc, Georg Heigold of Aachen (DE) for google llc, Lucas Klaus Beyer of Zurich (CH) for google llc, Alexander Kolesnikov of Zurich (CH) for google llc, Matthias Johannes Lorenz Minderer of Zurich (CH) for google llc, Dirk Weissenborn of Berlin (DE) for google llc, Mostafa Dehghani of Amsterdam (NL) for google llc, Alexey Dosovitskiy of Berlin (DE) for google llc, Thomas Unterthiner of Berlin (DE) for google llc
IPC Code(s): G06T7/00, G06F18/24, G06N3/045, G06N3/08
CPC Code(s): G06T7/97
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. one of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
Inventor(s): Neil Matthew Tinmouth Houlsby of Zurich (CH) for google llc, Sylvain Gelly of Aix-en-Provence (FR) for google llc, Jakob D. Uszkoreit of Berlin (DE) for google llc, Xiaohua Zhai of Zurich (CH) for google llc, Georg Heigold of Aachen (DE) for google llc, Lucas Klaus Beyer of Zurich (CH) for google llc, Alexander Kolesnikov of Zurich (CH) for google llc, Matthias Johannes Lorenz Minderer of Zurich (CH) for google llc, Dirk Weissenborn of Berlin (DE) for google llc, Mostafa Dehghani of Amsterdam (NL) for google llc, Alexey Dosovitskiy of Berlin (DE) for google llc, Thomas Unterthiner of Berlin (DE) for google llc
IPC Code(s): G06T7/00, G06F18/24, G06N3/045, G06N3/08
CPC Code(s): G06T7/97
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. one of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.
20250005823. Automated Generation of Immersive Interfaces_simplified_abstract_(google llc)
Inventor(s): Ahmad Nizam Anuar of Iskandar Puteri, Johor (MY) for google llc, Sandy Karunia of Singapore (SG) for google llc, Dian Zhang of Singapore (SG) for google llc, Sumeet Kale of Singapore (SG) for google llc
IPC Code(s): G06T11/60, G06F40/289
CPC Code(s): G06T11/60
Abstract: the present disclosure provides systems, methods, and computer program products for performing automated generation of immersive interfaces. for example, a computing device may perform automated generation of immersive interfaces by analyzing a web-based resource comprising textual content, extracting a plurality of textual content segments from the web-based resource, obtaining visual content and audio content related to each respective textual content segment from the plurality of textual content segments, generating target content for an audio-visual display of the web-based resource based on combining at least a portion of each respective textual content segment with the visual content and the audio content related to the respective textual content segment, and providing data descriptive of the generated target content to a computing device for presentation of the audio-visual display of the web-based resource.
Inventor(s): Anthony J. Piergiovanni of Denver CO (US) for google llc, Wei-Cheng Kuo of Santa Clara CA (US) for google llc, Anelia Angelova of Palo Alto CA (US) for google llc
IPC Code(s): G06V20/40, G06V10/776, G06V10/82
CPC Code(s): G06V20/41
Abstract: provided are machine-learned models for performing video processing with improved efficiency. in particular, the machine-learned model can perform the sparse application of one or more video kernels to a set of video data to generate video tokens that can, for example, be provided as input to a visual transformer. thus, example implementations of the present disclosure are directed to an approach which can turn a visual transformer (e.g., a vit encoder) into an efficient video model. furthermore, example implementations described herein can seamlessly work with both image and video inputs. specifically, by sparsely sampling the inputs, the model is able to do training and inference from both inputs. the proposed model is easily scalable and can optionally be adapted to large-scale pre-trained visual transformers without requiring full finetuning.
Inventor(s): Victor Carbune of Zurich (CH) for google llc, Matthew Sharifi of Kilchberg (CH) for google llc
IPC Code(s): G10L15/08, G06N20/00, G10L15/22, G10L21/0216
CPC Code(s): G10L15/08
Abstract: implementations described herein include detecting a stream of audio data that captures a spoken utterance of the user and that captures ambient noise occurring within a threshold time period of the spoken utterance being spoken by the user. implementations further include processing a portion of the audio data that includes the ambient noise to determine ambient noise classification(s), processing a portion of the audio data that includes the spoken utterance to generate a transcription, processing both the transcription and the ambient noise classification(s) with a machine learning model to generate a user intent and parameter(s) for the user intent, and performing one or more automated assistant actions based on the user intent and using the parameter(s).
Inventor(s): Sriram Natarajan of San Jose CA (US) for google llc, Yuxin Yu of San Jose CA (US) for google llc, Josh Brown of Seattle WA (US) for google llc, David Notario of Seattle WA (US) for google llc
IPC Code(s): G10L15/22, B60R16/037, G06F3/0481, G06F3/0488, G06F3/16, G06F9/451, G10L15/06, G10L15/08
CPC Code(s): G10L15/22
Abstract: implementations set forth herein relate to an automated assistant that can provide suggestions for a user to interact with the automated assistant to control applications while in a vehicle. the suggestions can be provided to encourage hands-free interactions with the applications, by suggesting an assistant input that invokes the automated assistant to operate as an interface between the user and the applications. assistant suggestions can be based on a context of a user and/or a context of the vehicle, such as content of a display interface of a device that the user is accessing while in the vehicle. for instance, the automated assistant can determine that an action that the user has employed an application to perform can be initialized more safely and/or in less time by utilizing a particular assistant input. this particular assistant input can then be rendered at an interface of a vehicle computing device.
Inventor(s): Amit Singhal of Sunnyvale CA (US) for google llc, Michael Ng of Sunnyvale CA (US) for google llc
IPC Code(s): G10L17/22, G06F16/33, G06F16/332, G10L17/14
CPC Code(s): G10L17/22
Abstract: implementations described herein relate to various techniques for biasing interpretations of spoken utterances that are received in a vehicular environment. for example, implementations can receive a spoken utterance that includes a query from a user of a vehicle and obtain a corresponding vehicle sensor data instance generated by vehicle sensor(s) of the vehicle. some implementations can determine to execute a search over only a first corpus of data, but not a second corpus of data, to obtain a given response to the query based on various criteria, including at least the query, the corresponding vehicle sensor data instance, a corresponding timestamp associated with the corresponding vehicle sensor data instance, and/or a corresponding duration of time the user has been associated with the vehicle. additional, or alternative, implementations can execute a search over both the first and second corpora of data, and obtain the given response based on the criteria.
20250006203. MANAGING DIALOG DATA PROVIDERS_simplified_abstract_(google llc)
Inventor(s): David Kliger Elson of Brooklyn NY (US) for google llc, David P. Whipp of San Jose CA (US) for google llc, Shir Judith Yehoshua of San Francisco CA (US) for google llc
IPC Code(s): G10L17/22, G06F16/332
CPC Code(s): G10L17/22
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing dialogs. in one aspect, a method includes receiving a request associated with a task from a user device; submitting the request to each of a plurality of distinct data providers; receiving a plurality of suggested dialog responses from two or more of the data providers; scoring the one or more suggested dialog responses based on one or more scoring factors; determining a particular dialog response to provide to the user based on the scoring; and providing the determined dialog response to the user device.
Inventor(s): Amit Singhal of Sunnyvale CA (US) for google llc, Dev M. Patel of San Francisco CA (US) for google llc, Yao Lin of Sunnyvale CA (US) for google llc, Arvind Sivaram Sharma of Mountian View CA (US) for google llc, Srikrishnan Subramanian of Fremont CA (US) for google llc
IPC Code(s): G10L17/22, B60R16/037, G06V40/16, G10L17/06
CPC Code(s): G10L17/22
Abstract: implementations described herein relate to determining how to fulfill a spoken utterance based on a user that provided the spoken utterance. for example, implementations can receive a spoken utterance from a user, determine a set of fulfillment actions for the spoken utterance, and determine whether the user that provided the spoken utterance corresponds to a first user or a second user. further, and in response to determining that the user corresponds to the first user, implementations can select a subset of first fulfillment action(s) from the set, and cause the subset of first fulfillment action(s) to be implemented to satisfy the spoken utterance. moreover, and in response to determining that the user corresponds to the second user, implementations can select a subset of distinct, second fulfillment action(s) from the set, and cause the subset of second fulfillment action(s) to be implemented to satisfy the spoken utterance.
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc
IPC Code(s): G10L19/00, G06F40/289, G10L13/08
CPC Code(s): G10L19/0018
Abstract: systems and methods for steganographic embedding of metadata in media, and improved generation of synthetic media files. in some examples, a steganography encoder may be trained to encode a media file with data such that it will be more likely to be accurately decoded, and/or less likely to be perceptible to a user or other applications. in some examples, the media file may be a synthetically generated media file, and the data may be some or all of the data used to generate the synthetically generated media file. in some examples, a generative model may be trained to create synthetically generated media files that are more likely to be accurately interpreted by an interpretive model. in some examples, data encoded into a synthetically generated media file may be used to output an indication that the file was synthetically generated.
Inventor(s): Christopher Li of New York NY (US) for google llc, Kyle Scott Kastner of Waltham MA (US) for google llc, Yuan Wang of Hoboken NJ (US) for google llc, Zhehuai Chen of Edgewater NJ (US) for google llc, Andrew Maxwell Rosenberg of Brooklyn NY (US) for google llc, Heng Su of Beijing (CN) for google llc, Qian Chen of Beijing (CN) for google llc, Leonid Aleksandrovich Velikovich of New York NY (US) for google llc, Patrick Maxim Rondon of New York NY (US) for google llc, Diamantino Antonio Caseiro of Philadelphia PA (US) for google llc, Zelin Wu of Jersey City NJ (US) for google llc
IPC Code(s): G10L25/30, G10L15/26
CPC Code(s): G10L25/30
Abstract: a method includes receiving training data that includes a set of transcribed speech utterances where each respective transcribed speech utterance is paired with a corresponding transcription. for each respective transcribed speech utterance, the method includes generating an encoded audio representation and an encoded textual representation, generating a higher order audio feature representation for a corresponding encoded audio representation, generating a higher order textual feature representation for a corresponding encoded textual representation, and determining a loss for the respective transcribed speech utterance based on the higher order audio feature representation and the higher order textual feature representation. the method also includes training a speech encoder and a text encoder of a correction model based on the loss determined for each transcribed speech utterance of the set of transcribed speech utterances.
Inventor(s): Namhoon Kim of San Jose CA (US) for google llc, Woon-Seong Kwon of Santa Clara CA (US) for google llc, Houle Gan of Santa Clara CA (US) for google llc, Yujeong Shim of Cupertino CA (US) for google llc, Mikhail Popovich of Danville CA (US) for google llc, Teckgyu Kang of Saratoga CA (US) for google llc
IPC Code(s): H01L25/065
CPC Code(s): H01L25/0657
Abstract: the technology relates to an integrated circuit (ic) package. the ic package may include a packaging substrate, an ic die, and an integrated voltage regulator die. the ic die may include a metal layer and a silicon layer. the metal layer may be connected to the packaging substrate. the integrated voltage regulator die may be positioned adjacent to the silicon layer and connected to the packaging substrate via one or more through mold vias or through dielectric vias. the ic die may be an application specific integrated circuit (asic) die.
Inventor(s): Miguel Cristian Young de la Sota of Cambridge MA (US) for google llc, Miguel Angel Osorio Lozano of El Dorado Hills CA (US) for google llc
IPC Code(s): H04L9/40
CPC Code(s): H04L63/1466
Abstract: this document describes techniques and apparatuses directed at implementing control flow integrity measurements to validate control flow in computing systems. within a scope, a local variable is initialized and configured to store a measurement value of a local control flow. during operations within the scope, at least one expression is computed, outputting a return value. a fingerprinting algorithm obtains the return value, combines the return value and the measurement value, and hashes the combination to produce a digest value. the local variable is then redefined as the digest value. next, the return value is compared to the expected, distinguished success return value in a branch instruction. before returning a final return value, the measurement value is compared against an expected value stored in a static variable. if the comparison fails, then the program can detect an attack on the control flow.
Inventor(s): Stefan Lindmark of Östhammar (SE) for google llc
IPC Code(s): H04L65/80, G06F3/0482, H04L65/1089, H04L65/1093, H04L65/403
CPC Code(s): H04L65/80
Abstract: systems and methods for determining video streams for presentation in a user interface (ui) of a video conference are provided. in response to a request of a first user of a video conference platform to participate in video conference, a user priority list associated with the first user is accessed. the user priority list identifies a plurality of users of the video conference platform. participants of the video conference are identified. the participants include the first user associated with a first client device of client devices of the participants of the video conference. a ui presenting video streams from client devices of at least a subset of the participants is provided for display on the first client device. presentation of each of the video streams in the ui depends on whether a respective participant of the at least the subset of the participants is included in the user priority list.
Inventor(s): Dongeek Shin of San Jose CA (US) for google llc
IPC Code(s): H04N5/265, G06T7/90, G06V10/25, G06V10/44, G06V10/56, H04N21/2743
CPC Code(s): H04N5/265
Abstract: methods and systems for color recommendations for overlaid text in a video are provided herein. a video for upload is received. the video includes a plurality of frames having overlaid content. data related to the video is provided as input to a machine learning model. one or more outputs obtained from the machine learning model is used to determine a color value that improves one or more presentation characteristics of the overlaid content within the video. a color associated with the determined color value is provided to a user for the overlaid content.
20250008158. EFFICIENT TRANSFORM SIGNALING FOR SMALL BLOCKS_simplified_abstract_(google llc)
Inventor(s): Jin Zhao of Mountian View CA (US) for google llc, In Suk Chong of Mountain View CA (US) for google llc
IPC Code(s): H04N19/625, H04N19/12, H04N19/176
CPC Code(s): H04N19/625
Abstract: a size of a transform block is identified. a transform type for the transform block is identified. the transform type includes a horizontal transform type and a vertical transform type. identifying the transform type includes determining whether the size of the transform block is below a predefined block size; and, in response to determining that the size is below the predefined block size, selecting a default transform type for each of the horizontal transform type and the vertical transform type. the transform type is then applied to the transform block. the default transform type can be the discrete cosine transform (dct).
Inventor(s): Tristan Schmelcher of Sammamish WA (US) for google llc, Markus Kuhn of Zurich (CH) for google llc, Laura McKnight of Somerville MA (US) for google llc, Alexander Kharitonov of Zurich (CH) for google llc, David Kim of Cambridge MA (US) for google llc
IPC Code(s): H04N21/439, H04N21/2187, H04N21/845
CPC Code(s): H04N21/4394
Abstract: a method includes receiving, by a processor, from a first server, a first plurality of frames associated with a media item. each frame of the first plurality of frames is associated with a respective timestamp of a first plurality of timestamps generated by the first server. a second plurality of frames associated with the media item are received from a second server. the second plurality of frames are each associated with a respective timestamp of a second plurality of timestamps generated by the second server. an offset value between a first timestamp of the first plurality of timestamps and a second timestamp of the second plurality of timestamps is determined. a modified plurality of frames is generated by modifying, based on the offset value, each timestamp of a subset of the second plurality of timestamps. the modified plurality of frames is sent to the client device.
Inventor(s): Oliver Woodman of London (GB) for google llc, Andrew Benedict Lewis of London (GB) for google llc
IPC Code(s): H04N21/8352, G06Q30/0241, G06Q30/0242, H04L9/40, H04N21/234, H04N21/2347, H04N21/254, H04N21/258, H04N21/44, H04N21/4408, H04N21/442, H04N21/647, H04N21/658
CPC Code(s): H04N21/8352
Abstract: systems and methods for verifying the rendering of video content on information resources are provided herein. a server can receive, from a target client device, a tracking message purporting to relate to delivery of a target content item; determine whether the tracking message contains an identifier of a sending device that sent the tracking message; determine whether the sending device and the target client device are the same device; if the sending client device and the target client device are the same device: recover, from the tracking message, information about at least a portion of a frame of a content item processed by a trusted platform module of the client device; and compare the at least a portion of the frame of the content item processed by a trusted platform module of the client device with a target content item.
Inventor(s): Fang Liu of Palo Alto CA (US) for google llc, Trausti Thormundsson of Irvine CA (US) for google llc, Yuan Jen Chang of Mountain View CA (US) for google llc, Nicholas Jordan Sanders of Saratoga CA (US) for google llc, Kari Antero Pulli of Belmont CA (US) for google llc, Kuan-Lin Chen of Palo Alto CA (US) for google llc
IPC Code(s): H04R1/10, G10K11/178
CPC Code(s): H04R1/1041
Abstract: the present disclosure provides a system and method using a charge collection antenna in a wearable device to collect charge variation based on a user's jawbone and muscle motion. the collected charge variation may be used to determine an on-body status of the wearable device. for example, in wireless earbuds, information acquired from a charge collection antenna may be used to determine whether the earbud is worn in-ear by the user. the collected charge variation may also be used to detect jaw motion by the user.
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc, Jing-Rong Hsieh of Taipei City (TW) for google llc
IPC Code(s): H04W68/00, H04W76/27, H04W76/40
CPC Code(s): H04W68/005
Abstract: managing paging for multicast and/or broadcast services (mbss) of interested ues that do not have an active radio connection with the ran can include providing, in mbs service paging instructions, indications of respective radio capabilities of interested ues in conjunction with the identifications of the interested ues, e.g., so that dus can have necessary ue radio capability information in-line with the paging instructions. another technique can include a base station providing an indication of ue radio capability information of interested ues to another base station. still another technique includes storing, at a du or at a cu, an indication of ue radio capabilities and/or a default or predetermined set of ue radio capabilities for use in paging interested ues.
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc
IPC Code(s): H04W72/30, H04W72/11, H04W72/543, H04W88/08
CPC Code(s): H04W72/30
Abstract: methods for managing radio resources for multicast and/or broadcast services (mbs), which may be implemented in a distributed unit (du) or a central unit (cu) of a distributed base station, are provided. one such method, in a du, includes receiving, from a cu, a cu-to-du message associated with an mrb, and including, based on qos parameter(s) included in the cu-to-du message, one or more multicast configuration parameters in a du-to-cu message. the method also includes transmitting the du-to-cu message to the cu. another method, in a cu, includes receiving, from a core network, a cn-to-bs message associated with an mbs session, and including, based on one or more qos parameters included in the cn-to-bs message, an indication to request one or more multicast configuration parameters in a cu-to-du message. the method also includes transmitting the cu-to-du message to a du of the distributed base station.
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc
IPC Code(s): H04W76/22, H04W76/40
CPC Code(s): H04W76/22
Abstract: a method for delivering data to user equipments (ues) is implemented in a node of a radio access network (ran), and includes receiving, from a network node, a packet including data that is to be delivered from a core network (cn) to one or more user equipments (ues); transmitting the packet to at least some of the one or more ues via a broadcast transmission when the packet is received via a common downlink tunnel or via a first dl tunnel of a plurality of dl tunnels; and transmitting the packet to a particular ue of the one or more ues via a unicast transmission when the packet is not received via the common downlink tunnel or is received via a second dl tunnel of the plurality of dl tunnels.
20250008845. LOW FOOTPRINT RESONATOR IN FLIP CHIP GEOMETRY_simplified_abstract_(google llc)
Inventor(s): Julian Shaw Kelly of Santa Barbara CA (US) for google llc, Evan Jeffrey of Santa Barbara CA (US) for google llc
IPC Code(s): H10N60/80, G06N10/00, H01P3/00, H01P5/02, H01P11/00, H10N60/01, H10N60/12, H10N60/85
CPC Code(s): H10N60/805
Abstract: a device includes a first substrate having a principal surface; a second substrate having a principal surface, in which the first substrate is bump-bonded to the second substrate such that the principal surface of the first substrate faces the principal surface of the second substrate; a circuit element having a microwave frequency resonance mode, in which a first portion of the circuit element is arranged on the principal surface of the first substrate and a second portion of the circuit element is arranged on the principal surface of the second substrate; and a first bump bond connected to the first portion of the circuit element and to the second portion of the circuit element, in which the first superconductor bump bond provides an electrical connection between the first portion and the second portion.
- Google LLC
- A61B5/0507
- A61B5/00
- A61B5/024
- A61B5/08
- A61B5/11
- G01S13/28
- CPC A61B5/0507
- Google llc
- A61B5/1455
- CPC A61B5/14552
- A61B5/318
- CPC A61B5/7275
- B65D5/38
- B65D6/06
- CPC B65D5/38
- G01C21/36
- G06F40/30
- G06N5/022
- CPC G01C21/3608
- G01N33/543
- G01N33/84
- CPC G01N33/54386
- G01R19/25
- G01R19/00
- G01R19/10
- G01R22/08
- CPC G01R19/2513
- G02B27/10
- G02B26/08
- G02B27/01
- G02B27/12
- CPC G02B27/1006
- G03B21/20
- CPC G03B21/208
- G06F3/0482
- G06F3/04817
- G06F3/0488
- G06F3/04883
- G06F3/04886
- G06F40/166
- CPC G06F3/0482
- G06F3/04847
- CPC G06F3/04847
- G06F7/523
- G06F7/50
- CPC G06F7/523
- G06F8/61
- CPC G06F8/61
- G06F8/658
- G06F11/14
- G06F16/14
- CPC G06F8/658
- G06F9/451
- G06N20/00
- CPC G06F9/451
- G06F11/34
- G06F3/01
- CPC G06F11/3438
- G06F13/16
- G06F12/02
- CPC G06F13/1668
- G06F16/25
- CPC G06F16/258
- G06F16/432
- G06F9/38
- G06F16/23
- G06F16/242
- CPC G06F16/433
- G06F16/9032
- G06F16/955
- G10L15/26
- G10L15/30
- G10L15/32
- CPC G06F16/90332
- G06F16/9535
- G06F16/906
- H04L67/306
- H04L67/50
- H04L67/55
- CPC G06F16/9535
- G06F21/56
- CPC G06F21/56
- G06F21/62
- CPC G06F21/62
- G06F40/40
- CPC G06F40/40
- G06F16/332
- G06N3/044
- G06F3/06
- G06N3/08
- CPC G06N3/044
- CPC G06N3/08
- G06N10/70
- G06N10/20
- G06N10/40
- CPC G06N10/70
- G06N10/60
- CPC G06N20/00
- G06Q30/08
- CPC G06Q30/08
- G06T7/00
- G06F18/24
- G06N3/045
- CPC G06T7/97
- G06T11/60
- G06F40/289
- CPC G06T11/60
- G06V20/40
- G06V10/776
- G06V10/82
- CPC G06V20/41
- G10L15/08
- G10L15/22
- G10L21/0216
- CPC G10L15/08
- B60R16/037
- G06F3/0481
- G06F3/16
- G10L15/06
- CPC G10L15/22
- G10L17/22
- G06F16/33
- G10L17/14
- CPC G10L17/22
- G06V40/16
- G10L17/06
- G10L19/00
- G10L13/08
- CPC G10L19/0018
- G10L25/30
- CPC G10L25/30
- H01L25/065
- CPC H01L25/0657
- H04L9/40
- CPC H04L63/1466
- H04L65/80
- H04L65/1089
- H04L65/1093
- H04L65/403
- CPC H04L65/80
- H04N5/265
- G06T7/90
- G06V10/25
- G06V10/44
- G06V10/56
- H04N21/2743
- CPC H04N5/265
- H04N19/625
- H04N19/12
- H04N19/176
- CPC H04N19/625
- H04N21/439
- H04N21/2187
- H04N21/845
- CPC H04N21/4394
- H04N21/8352
- G06Q30/0241
- G06Q30/0242
- H04N21/234
- H04N21/2347
- H04N21/254
- H04N21/258
- H04N21/44
- H04N21/4408
- H04N21/442
- H04N21/647
- H04N21/658
- CPC H04N21/8352
- H04R1/10
- G10K11/178
- CPC H04R1/1041
- H04W68/00
- H04W76/27
- H04W76/40
- CPC H04W68/005
- H04W72/30
- H04W72/11
- H04W72/543
- H04W88/08
- CPC H04W72/30
- H04W76/22
- CPC H04W76/22
- H10N60/80
- G06N10/00
- H01P3/00
- H01P5/02
- H01P11/00
- H10N60/01
- H10N60/12
- H10N60/85
- CPC H10N60/805
