View source for Google LLC patent applications on March 20th, 2025

=Patent Applications by Google LLC on March 20th, 2025=



[[:Category:Google LLC|Google LLC]]: 55 patent applications[[Category:Google LLC]]

Google LLC has applied for patents in the areas of [[:Category:G10L15/06|G10L15/06]] (4), [[:Category:G10L15/22|G10L15/22]] (4), [[:Category:H04L9/40|H04L9/40]] (3), [[:Category:G06F16/9535|G06F16/9535]] (3), [[:Category:G06N20/20|G06N20/20]] (2)
[[:Category:CPC_G06F16/9535|G06F16/9535]] (3), [[:Category:CPC_G06F9/45558|G06F9/45558]] (2), [[:Category:CPC_G10L15/063|G10L15/063]] (2), [[:Category:CPC_G06N20/20|G06N20/20]] (2), [[:Category:CPC_C09K5/10|C09K5/10]] (1)

With keywords such as: data, content, device, user, based, include, example, audio, output, and computing in patent application abstracts.




====Patent Applications by Google LLC====


[[20250092296. THERMAL INTERFACE MATERIAL AND METHOD FOR MAKING THE SAME_simplified_abstract_(google llc)]]

Inventor(s): Huijuan Chen of Fremont CA US for google llc, Michael John Bliss of Santa Clara CA US for google llc

IPC Code(s): C09K5/10, B82Y30/00, C09K5/14, H01L23/373

CPC Code(s): C09K5/10




Abstract: a thermal interface material including: a matrix material composing 10 wt. % or less of the thermal interface material; and a filler dispersed in the matrix material composing 80 wt. % to 90 wt. % of the thermal interface material, the filler including: particles of a metal having a nominal dimension in a range from 1 micron to 100 microns, the particles of the metal composing at least 40 wt. % of the thermal interface material; particles of a metal oxide having a nominal dimension in a range from 0.1 microns to 20 microns, the particles of the metal oxide composing at least 15 wt. % of the thermal interface material; and diamond particles having a nominal dimension of 1,000 nm or less, the diamond particles composing 0.1 wt. % to 1.5 wt. % of the thermal interface material.[[Category:C09K5/10]][[Category:B82Y30/00]][[Category:C09K5/14]][[Category:H01L23/373]][[Category:CPC_C09K5/10]][[Category:google llc]]



[[20250093159. Indoor Localization Based on Multiple Device Sensors_simplified_abstract_(google llc)]]

Inventor(s): Dongeek Shin of San Jose CA US for google llc

IPC Code(s): G01C21/16

CPC Code(s): G01C21/16




Abstract: example embodiments of the present disclosure provide for an example method including obtaining location data associated with a first and second computing device. example method can include determining an on-user device status for the each of the first and second computing devices. example method can include obtaining inertial measurement unit (imu) sensor data from each of the first and second computing devices. example method can include inputting the imu sensor data from each of the first and second computing devices into a machine learned model. example method can include obtaining, from the machine learned model, output data indicative of a predicted location. example method can include comparing the output data indicative of the predicted location to data indicative of a location of a target subzone. example method can include transmitting data which instructs a user interface of the first computing device to provide a content item for display.[[Category:G01C21/16]][[Category:CPC_G01C21/16]][[Category:google llc]]



[[20250093164. Foundational Models for Semantic Routing_simplified_abstract_(google llc)]]

Inventor(s): Victor Carbune of Zurich  CH for google llc, Polina Zablotskaia of Berlin  DE for google llc, Matthew Sharifi of Kilchberg  CH for google llc, Manuel Tragut of Zug  CH for google llc

IPC Code(s): G01C21/34, G06N3/0455, G06N3/084, G10L15/06, G10L15/18, G10L15/183, G10L15/30

CPC Code(s): G01C21/3446




Abstract: training data is obtained. the training data includes (a) route information indicative of a route from a starting location to a destination location, wherein the route comprises a plurality of route segments comprising a first subset of route segments and a second subset of route segments, and (b) route characteristic information descriptive of one or more route characteristics. at least the first subset of route segments and a portion of the route characteristic information associated with the first subset of route segments is processed with a machine-learned semantic routing model to obtain one or more predicted route segments for the second subset of route segments. one or more parameters of the machine-learned semantic routing model are adjusted based on an optimization function that evaluates a difference between the one or more predicted route segments and the second subset of route segments.[[Category:G01C21/34]][[Category:G06N3/0455]][[Category:G06N3/084]][[Category:G10L15/06]][[Category:G10L15/18]][[Category:G10L15/183]][[Category:G10L15/30]][[Category:CPC_G01C21/3446]][[Category:google llc]]



[[20250093173. GOAL-ORIENTED DIRECTIONS_simplified_abstract_(google llc)]]

Inventor(s): Matthew Sharifi of Mountain View CA US for google llc, Jyrki Alakuijala of Mountain View CA US for google llc

IPC Code(s): G01C21/36, G01C21/34

CPC Code(s): G01C21/3644




Abstract: to provide navigation directions to one or more points of interest (pois) for accomplishing a user's goals, a computing device receives an indication of n goals for a user to accomplish, and identifies m pois for accomplishing the n goals. n is greater than m. the computing device then generates a set of navigation directions for navigating to each of the m pois, and provides the set of navigation directions for display to the user.[[Category:G01C21/36]][[Category:G01C21/34]][[Category:CPC_G01C21/3644]][[Category:google llc]]



[[20250093502. ULTRASONIC MAPPING SYSTEM_simplified_abstract_(google llc)]]

Inventor(s): Dongeek Shin of Mountain View CA US for google llc

IPC Code(s): G01S15/89, G01C21/16, G01S7/54, G01S15/10, G01S15/42, G01S15/58, G01S15/86

CPC Code(s): G01S15/89




Abstract: to determine a location of a user, a computing device transmits an audio signal via a speaker and receives a reflected audio signal via a microphone. the computing device obtains sensor data from at least one of: one or more positioning sensors, one or more accelerometers, one or more gyroscopes, or one or more inertial measurement units, and determines a location of a user based on (i) a round trip time of the audio signal and the reflected audio signal, and (ii) the sensor data.[[Category:G01S15/89]][[Category:G01C21/16]][[Category:G01S7/54]][[Category:G01S15/10]][[Category:G01S15/42]][[Category:G01S15/58]][[Category:G01S15/86]][[Category:CPC_G01S15/89]][[Category:google llc]]



[[20250093568. SYSTEMS AND METHODS FOR LIGHT RECYCLING USING POLARIZATION AT AN INCOUPLER AND A REFLECTIVE STRUCTURE_simplified_abstract_(google llc)]]

Inventor(s): Daniel Adema of Kitchener  CA for google llc, Shreyas Potnis of Kitchener  CA for google llc, Timothy Paul Bodiya of Toronto  CA for google llc

IPC Code(s): F21V8/00

CPC Code(s): G02B6/0018




Abstract: the present disclosure describes techniques for reflecting light incoupled into a waveguide in a direction away from the outcoupler back toward the outcoupler. the waveguide includes an incoupler to incouple light of a first polarization state, and a reflective structure to receive incoupled light of the first polarization state and reflect it with a second polarization state toward the outcoupler. the reflective structure is on an opposite side of the incoupler as the outcoupler. in some embodiments, a polarization beam splitter or other polarization-selective layer is included at an interface of the incoupler and a waveguide substrate of the waveguide to transmit light of the first polarization state and reflect light of the second polarization state.[[Category:F21V8/00]][[Category:CPC_G02B6/0018]][[Category:google llc]]



[[20250093640. RELATIVE HEAD-TRACKING FOR USER-INTERFACE ELEMENT SELECTION ON A HEAD-MOUNTED DISPLAY DEVICE_simplified_abstract_(google llc)]]

Inventor(s): Stiven Guillaume Francois Morvan of New York NY US for google llc, Konstantine Nicholas John Tsotsos of Corte Madera CA US for google llc, Dongeek Shin of San Jose CA US for google llc, Tinglin Duan of Toronto  CA for google llc

IPC Code(s): G02B27/00, G02B27/01

CPC Code(s): G02B27/0093




Abstract: a head-mounted display device may initiate display of a user interface on a display of the head-mounted display device. a head-mounted display device may compute an angular distance between a previous head orientation and a current head orientation based on head movement data. a head-mounted display device may apply a gain value to the angular distance to move a position indicator to an updated position within a boundary of the user interface, the user interface configured to remain fixed to a location in the display regardless of head movements.[[Category:G02B27/00]][[Category:G02B27/01]][[Category:CPC_G02B27/0093]][[Category:google llc]]



[[20250093659. ELONGATED COLLIMATOR FOR PUPIL PLACEMENT_simplified_abstract_(google llc)]]

Inventor(s): Ozan Cakmakci of San Mateo CA US for google llc, Oscar Alberto Martinez of San Diego CA US for google llc

IPC Code(s): G02B27/01, G02B27/00

CPC Code(s): G02B27/0172




Abstract: an elongated collimator collimates light generated by a microdisplay for coupling to an exit pupil expander of a waveguide. the elongated collimator includes a first portion having four or more freeform surfaces that fold the optical path of the light and then direct the light via total internal reflection through an elongated flat (or nearly flat) second portion of the collimator to form a pupil within a lens of an eyewear display device. the elongated collimator delivers collimated light to a pupil located toward the center of the lens where the light can be collected by an exit pupil expander having a relatively small footprint.[[Category:G02B27/01]][[Category:G02B27/00]][[Category:CPC_G02B27/0172]][[Category:google llc]]



[[20250093921. DYNAMIC RESET LATENCY_simplified_abstract_(google llc)]]

Inventor(s): Syed Shakir Iqbal of Bengaluru  IN for google llc, Vaibhav Gupta of Gurgaon  IN for google llc

IPC Code(s): G06F1/24, G06F1/12

CPC Code(s): G06F1/24




Abstract: a method of resetting a number of functional components in a computing device includes determining a number of cycles required to reset the functional components based on a predetermined voltage controlling a reset synchronizer to run for the determined number of cycles wherein the reset synchronizer controls a reset network connected to the functional components, and wherein the determined number of cycles at a first voltage is different than a determined number of cycles at a second voltage.[[Category:G06F1/24]][[Category:G06F1/12]][[Category:CPC_G06F1/24]][[Category:google llc]]



[[20250094022. DETERMINING ELIGIBILITY OF CONTENT LOCATORS FROM PREVIOUS COMPUTING DEVICE_simplified_abstract_(google llc)]]

Inventor(s): Daniel Peng of Seattle WA US for google llc, Jorge Zuniga of Falls Church VA US for google llc, Nesrine Changuel of Vanves  FR for google llc, Sophie Chang of Seattle WA US for google llc, Thomas Nont Boonsiri of Santa Clara CA US for google llc, Tarun Bansal of Bellevue WA US for google llc, Matthew Spencer Rendely of Seattle WA US for google llc, Nasim Sedaghat of Montreal  CA for google llc

IPC Code(s): G06F3/0483

CPC Code(s): G06F3/0483




Abstract: a non-transitory computer-readable storage medium can include instructions stored thereon that, when executed by at least one processor, are configured to cause a computing device to receive a first content locator and a second content locator, content associated with the first content locator being previously accessed by a previous computing device in association with a user account and content associated with the second content locator being previously accessed by the previous computing device in association with the user account; determine that the content associated with the first content locator is eligible for viewing on the current computing device; determine that the content associated with the second content locator is ineligible for viewing on the computing device; and present, using a web browser associated with the user account, content associated with the first content locator without presenting content associated with the second content locator.[[Category:G06F3/0483]][[Category:CPC_G06F3/0483]][[Category:google llc]]



[[20250094116. DETERMINING INPUT MODALITY OF HEAD-MOUNTED DEVICE BASED ON INPUT MODALITY OF HANDHELD DEVICE_simplified_abstract_(google llc)]]

Inventor(s): Ruofei Du of San Francisco CA US for google llc, David Kim of Zug  CH for google llc, Fengyuan Zhu of Toronto  CA for google llc, Daniel Kalmar of Zurich  CH for google llc

IPC Code(s): G06F3/14, G06F3/01, G06F3/0346, G06F3/04886

CPC Code(s): G06F3/1454




Abstract: a method can include determining, by a head-mounted device mounted on a head of a user, a number of degrees of freedom of an input modality of an auxiliary device; determining an input modality of the head-mounted device based on the number of degrees of freedom of the input modality of the auxiliary device; and presenting the input modality of the head-mounted device to the user.[[Category:G06F3/14]][[Category:G06F3/01]][[Category:G06F3/0346]][[Category:G06F3/04886]][[Category:CPC_G06F3/1454]][[Category:google llc]]



[[20250094137. Visual Programming Platform Featuring Machine Learning for Automated Code Development_simplified_abstract_(google llc)]]

Inventor(s): Ruofei Du of San Francisco CA US for google llc, Zhongyi Zhou of San Francisco CA US for google llc

IPC Code(s): G06F8/34, G06F8/33

CPC Code(s): G06F8/34




Abstract: a visual programming platform can leverage a machine learning-based coding system to generate an initial set of programming-language code for further graphical editing by a human user. as an example, the visual programming platform can obtain a natural language description of a task to be performed by a computational pipeline. the visual programming platform can process the natural language description of the task with a machine learning coding system that includes one or more machine-learned models to generate, as an output of the machine learning coding system, a set of pseudocode that describes performance of the task. the platform can process the set of pseudocode that describes performance of the task with a compiler to generate a set of programming-language code that defines the computational pipeline for performing the task. the visual programming platform can generate a graphical visualization of the computational pipeline defined by the set of programming-language code.[[Category:G06F8/34]][[Category:G06F8/33]][[Category:CPC_G06F8/34]][[Category:google llc]]



[[20250094156. MANAGING APPLICATION UPDATES_simplified_abstract_(google llc)]]

Inventor(s): Haifeng Ji of Mountain View CA US for google llc, Giang Huong Le of Norwalk CA US for google llc, Luis Silva Vargas of San Jose CA US for google llc, Alexey Semenov of San Jose CA US for google llc

IPC Code(s): G06F8/65

CPC Code(s): G06F8/65




Abstract: a process according to the techniques described herein includes determining a set of available application updates for one or more applications installed at a computing device, and determining, based at least in part on an amount of metered data available during a time period and an amount of metered data used during the time period, an application update data budget for downloading application updates over a metered data network. lire process may also include determining a respective amount of data required to download each available application update from the set of available application updates, and scheduling, based the respective amounts of data required to download each available application update, a first set of application updates to be downloaded using the metered data, network or an unmetered data, network and a second set of application updates to be downloaded using only the unmetered data network.[[Category:G06F8/65]][[Category:CPC_G06F8/65]][[Category:google llc]]



[[20250094204. RESOURCE MANAGER INTEGRATION IN CLOUD COMPUTING ENVIRONMENTS_simplified_abstract_(google llc)]]

Inventor(s): Ilya Beyer of Mill Valley CA US for google llc, Manoj Sharma of Sunnyvale CA US for google llc, Gururaj Pangal of Pleasanton CA US for google llc, Maurilio Cometto of Redwood City CA US for google llc

IPC Code(s): G06F9/455, G06F8/60, G06F9/50

CPC Code(s): G06F9/45558




Abstract: a system includes first host machines implementing a public-cloud computing environment, wherein at least one of the first host machines includes a resource manager that provides a public-cloud resource interface through which one or more public-cloud clients interact with one or more virtual machines, and second host machines implementing a private-cloud computing environment, wherein at least one of the second host machines includes one or more private-cloud virtual machines, wherein at least one of the first host machines further includes a private-cloud vm resource provider through which the resource manager interacts with the private-cloud virtual machines, wherein the vm resource provider translates requests to perform virtual machine operations from a public-cloud-resource interface to a private-cloud virtual machine interface, and the private-cloud virtual machines perform the requested virtual machine operations in response to receiving the translated requests from the vm resource provider.[[Category:G06F9/455]][[Category:G06F8/60]][[Category:G06F9/50]][[Category:CPC_G06F9/45558]][[Category:google llc]]



[[20250094205. BEHAVIOR-BASED VM RESOURCE CAPTURE FOR FORENSICS_simplified_abstract_(google llc)]]

Inventor(s): Michael Halcrow of Kirkland WA US for google llc, Thomas Garnier of Mountain View CA US for google llc

IPC Code(s): G06F9/455, G06F9/50, G06F11/14, G06F12/14, G06F21/55, G06F21/56, G06F21/57

CPC Code(s): G06F9/45558




Abstract: a method including monitoring, using a standard level of auditing, one or more processes of a vm and, based on monitoring the process(es), detecting aberrant behavior indicating that an attack against the vm is imminent. based on detecting aberrant behavior indicating that the attack is imminent, the method includes monitoring, using a heightened level of auditing, the process(es), the heightened level of auditing generating log data representative of memory accesses performed by the vm, and notifying a user of the vm that the imminent attack is detected. during the attack against the vm, maintaining the monitoring of the process(es) using the heightened level of auditing, the method includes determining that the attack has concluded and, based on determining that the attack has concluded, processing the log data to determine an action performed by the detected attack; and monitoring, using the standard level of auditing, the process(es).[[Category:G06F9/455]][[Category:G06F9/50]][[Category:G06F11/14]][[Category:G06F12/14]][[Category:G06F21/55]][[Category:G06F21/56]][[Category:G06F21/57]][[Category:CPC_G06F9/45558]][[Category:google llc]]



[[20250094353. Memory Migration and Page Fault Avoidance_simplified_abstract_(google llc)]]

Inventor(s): Prashanth Prakash of Santa Clara CA US for google llc, Jerome Glisse of Sunnyvale CA US for google llc

IPC Code(s): G06F12/1009, G06F12/0817

CPC Code(s): G06F12/1009




Abstract: accessing information associated with a virtual memory address by receiving a virtual memory address, translating the virtual memory address into a nominal physical memory address, receiving the nominal physical memory address at a memory migrator, and using the memory migrator to determine an old physical memory address corresponding to the nominal physical memory address and access the information at the old physical memory address or a new physical memory address. the accessing operation may be performed as part of migrating the information from an old physical memory location corresponding the old physical memory address to a new physical memory location corresponding to the new physical memory address.[[Category:G06F12/1009]][[Category:G06F12/0817]][[Category:CPC_G06F12/1009]][[Category:google llc]]



[[20250094456. LARGE LANGUAGE MODEL OUTPUT ENTAILMENT_simplified_abstract_(google llc)]]

Inventor(s): Kelvin Gu of Mountain View CA US for google llc, Zhuyun Dai of Mountain View CA US for google llc, Panupong Pasupat of Mountain View CA US for google llc, Chen Elkind of Mountain View CA US for google llc, Eran Ofek of Rehovot  CH for google llc, Hagai Taitelbaum of Mountain View CA US for google llc, Mukund Sundararajan of Mountain View CA US for google llc, Vered Cohen of Mountain View CA US for google llc, Itay Karo of Mountain View CA US for google llc, Norbert Kalb of Mountain View CA US for google llc, Yossi Matias of Tel Aviv  IL for google llc, Tej Toor of Brooklyn NY US for google llc, Teghan Tracy of Boulder CO US for google llc

IPC Code(s): G06F16/332, G06F16/33, G06F16/35

CPC Code(s): G06F16/3329




Abstract: implementations are described herein for identifying potentially false information in generative model output by performing entailment evaluation of generative model output. in various implementations, data indicative of a query may be processed to generate generative model output. textual fragments may be extracted from the generative model output, and a subset of the textual fragments may be classified as being suitable for textual entailment analysis. textual entailment analysis may be performed on each textual fragment of the subset, including formulating a search query based on the textual fragment, retrieving document(s) responsive to the search query, and processing the textual fragment and the document(s) using entailment machine learning model(s) to generate prediction(s) of whether the at least one document corroborates or contradicts the textual fragment. when natural language (nl) responsive to the query is rendered at a client device, annotation(s) may be rendered to express the prediction(s).[[Category:G06F16/332]][[Category:G06F16/33]][[Category:G06F16/35]][[Category:CPC_G06F16/3329]][[Category:google llc]]



[[20250094491. Structured Video Documents_simplified_abstract_(google llc)]]

Inventor(s): Johan Schalkwyk of Scarsdale NY US for google llc, Francoise Beaufays of Mountain View CA US for google llc

IPC Code(s): G06F16/783, G06F16/738, G06F40/169, G06F40/30

CPC Code(s): G06F16/7844




Abstract: a method includes receiving a content feed that includes audio data corresponding to speech utterances and processing the content feed to generate a semantically-rich, structured document. the structured document includes a transcription of the speech utterances and includes a plurality of words each aligned with a corresponding audio segment of the audio data that indicates a time when the word was recognized in the audio data. during playback of the content feed, the method also includes receiving a query from a user requesting information contained in the content feed and processing, by a large language model, the query and the structured document to generate a response to the query. the response conveys the requested information contained in the content feed. the method also includes providing, for output from a user device associated with the user, the response to the query.[[Category:G06F16/783]][[Category:G06F16/738]][[Category:G06F40/169]][[Category:G06F40/30]][[Category:CPC_G06F16/7844]][[Category:google llc]]



[[20250094503. AUTOMATICALLY RESTRUCTURING SEARCH CAMPAIGNS_simplified_abstract_(google llc)]]

Inventor(s): Vineet Verma of Mountain View CA US for google llc

IPC Code(s): G06F16/953, G06F16/2458, G06F16/901, G06F16/906

CPC Code(s): G06F16/953




Abstract: to automatically map keywords to landing pages, a system obtaining a dataset including an initial set of groups of content items, each of the groups mapped to a respective landing page in an initial set of landing pages, and each of the content items associated with one or more keywords in an initial keyword vocabulary; generates a reduced dataset based on the obtained dataset, which includes (i) generating a reduced set of landing pages based on the initial set of landing pages using parameters of links associated with the respective landing pages, (ii) clustering the keywords to determine a set of themes associated with the dataset, and (iii) generating a reduced set of groups, including identifying overlaps in themes included in the set of themes, between the groups. the system further uses the generated data structure to map a received search term to one or more of the content items.[[Category:G06F16/953]][[Category:G06F16/2458]][[Category:G06F16/901]][[Category:G06F16/906]][[Category:CPC_G06F16/953]][[Category:google llc]]



[[20250094508. DIGITAL COMPONENT PROVISION BASED ON CONTEXTUAL FEATURE DRIVEN AUDIENCE INTEREST PROFILES_simplified_abstract_(google llc)]]

Inventor(s): Wei Huang of Kirkland WA US for google llc, Zhenyu Liu of San Jose CA US for google llc, Liang Wang of Bellevue WA US for google llc, Kumar Rishabh of Redmond WA US for google llc

IPC Code(s): G06F16/9535, G06F16/9537

CPC Code(s): G06F16/9535




Abstract: methods, systems, and media comprising; obtaining, from a client device and during a browsing session conducted by a user, contextual features relating to context within the browsing session, wherein the contextual features do not include any personally-identifiable data; generating, using a trained contextual model and based on the contextual features, an audience interest profile, wherein the audience interest profile represents a prediction of affinity to one or more content categories, wherein the trained contextual model is trained using a set of historical contextual data aggregated from a plurality of prior browsing sessions and audience interest profiles that each represent an affinity to one or more content categories, and wherein the set of historical contextual data does not include any personally-identifiable data; identifying, based on the generated audience interest profile, a digital component for provision; and providing, for display on the client device and during the browsing session, the digital component.[[Category:G06F16/9535]][[Category:G06F16/9537]][[Category:CPC_G06F16/9535]][[Category:google llc]]



[[20250094511. Proactive Query and Content Suggestion with Generative Model Generated Question and Answer_simplified_abstract_(google llc)]]

Inventor(s): Ibrahim Badr of New York NY US for google llc, Yunsong Guo of Santa Clara CA US for google llc, Imran R. Mansuri of Sunnyvale CA US for google llc

IPC Code(s): G06F16/9535, G06F40/20

CPC Code(s): G06F16/9535




Abstract: systems and methods for proactive query and content suggestion can include obtaining web data, determining a change event occurred, and generating a query and content suggestion. generating the query and content suggestion can include processing data descriptive of the change event with a generative model to generate one or more model-generated query suggestions. one or more web resources can be obtained then processed to generate a change event summary. the one or more query suggestions and the change event summary can then be provided for display.[[Category:G06F16/9535]][[Category:G06F40/20]][[Category:CPC_G06F16/9535]][[Category:google llc]]



[[20250094514. AUTOMATED USER LANGUAGE DETECTION FOR CONTENT SELECTION_simplified_abstract_(google llc)]]

Inventor(s): Prajakta Kalekar of Mountain View CA US for google llc, Yiding Liu of Mountain View CA US for google llc

IPC Code(s): G06F16/9535

CPC Code(s): G06F16/9535




Abstract: systems and methods of determining languages of users in networked environments are provided herein. a data processing system having one or more processors coupled with memory can receive, from a client device, a request for content identifying an account profile. the data processing system can receive a request for content identifying an account profile and including one or more keywords; determine a first set of candidate languages from a plurality of languages; determine a second set of candidate languages based on one or more information resources associated with the one or more keywords; calculate confidence scores for at least some of the second set of candidate languages; and update the first set of candidate languages based on the confidence scores for the at least some of the second set of candidate languages.[[Category:G06F16/9535]][[Category:CPC_G06F16/9535]][[Category:google llc]]



[[20250094518. PROVISION OF DIFFERENT CONTENT PAGES BASED ON VARYING USER INTERACTIONS WITH A SINGLE CONTENT ITEM_simplified_abstract_(google llc)]]

Inventor(s): Margaret Calliope Georgiadis of Palo Alto CA US for google llc

IPC Code(s): G06F16/954, G06F3/0483, G06F3/04842, G06F16/958

CPC Code(s): G06F16/954




Abstract: methods, systems, and computer programs encoded on a computer storage medium, that provide different content pages based on varying user interactions with a content item on a content page. a first content page that includes a first multi-interaction content navigation item may be provided for display within a first application. a first set of user interactions with this content navigation item may cause display of a second content page that is linked to by this content navigation item. a second set of user interactions with this content navigation item may cause display of a different content page that is generated using contextual data. when data indicating performance of the second set of user interactions with this content navigation item may be received, the contextual data may be obtained, based on which, the third content page may be provided for display within the first application.[[Category:G06F16/954]][[Category:G06F3/0483]][[Category:G06F3/04842]][[Category:G06F16/958]][[Category:CPC_G06F16/954]][[Category:google llc]]



[[20250094521. GENERATIVE NAVIGATIONAL CORPUS_simplified_abstract_(google llc)]]

Inventor(s): Victor Carbune of Zurich  CH for google llc, Arash Sadr of Belmont CA US for google llc, Matthew Sharifi of Kilchberg  CH for google llc

IPC Code(s): G06F16/958, G06F16/955

CPC Code(s): G06F16/958




Abstract: disclosed implementations relate to structures that support an on-demand navigational corpus. an example method involves receiving a navigation request from a client device pertaining to an intent, determining seed content associated with the navigation request, utilizing a large foundational model to create a web page incorporating the seed content, based on a navigation model, and the intent, and delivering the generated web page for presentation on the client device. the method enables efficient and personalized web page generation based on user intent, enhancing user experience and facilitating dynamic navigation using raw seed content.[[Category:G06F16/958]][[Category:G06F16/955]][[Category:CPC_G06F16/958]][[Category:google llc]]



[[20250094556. USING AUTHENTICATION CHALLENGES TO AUTOMATICALLY OBTAIN TRAINING DATA TO TRAIN A MACHINE LEARNING MODEL_simplified_abstract_(google llc)]]

Inventor(s): Obaid Sarvana of Plainfield IL US for google llc

IPC Code(s): G06F21/36

CPC Code(s): G06F21/36




Abstract: a method for using authentication challenges to automatically obtain training data to train a machine learning model (mlm). the method includes identifying a generative mlm to be trained using training data reflecting analytical responses of humans, and automatically collecting the training data from a plurality of users by providing an authentication challenge for each user attempting to access a resource. the authentication challenge requests a set of responses from a respective user of the plurality of users. the set of responses include a first response to a first sample which indicates whether the respective user is a human, and a second response to a second sample which indicates an analytical response of the respective user. responsive to determining that the respective user is a human, the second response is used as part of the training data for the generative mlm.[[Category:G06F21/36]][[Category:CPC_G06F21/36]][[Category:google llc]]



[[20250094561. VERIFIABLE SECURE DATASET OPERATIONS WITH PRIVATE JOIN KEYS_simplified_abstract_(google llc)]]

Inventor(s): Carlos Cela of Mountain View CA US for google llc, John Tobler of Mountain View CA US for google llc, Eugene Shaphir of Mountain View CA US for google llc, Chanda Patel of Mountain View CA US for google llc, Quaseer Mujawar of Mountain View CA US for google llc, Farshid Shariatzadeh of Mountain View CA US for google llc, Dina Kurman of Mountain View CA US for google llc, Minh Hoang of Mountain View CA US for google llc

IPC Code(s): G06F21/53

CPC Code(s): G06F21/53




Abstract: to performing a join operation, a module executing in a trusted execution environment (tee) receives a first dataset including personal identifiable information (pii) data and non-pii data from a first-party (1p) data source. the module pre-processes the pii data to generate first formatted pii data, the first formatted pii data conforming to a predefined format: matches, in the tee, the first formatted pii data to second formatted pii data included in a second dataset: performs a join operation between the first dataset and the second dataset based on the matching, to generate a joined dataset: and provides, to a data service operating independently of the 1p data source, the joined dataset.[[Category:G06F21/53]][[Category:CPC_G06F21/53]][[Category:google llc]]



[[20250094613. SECURE WORKFLOWS WITH RULE-BASED DATA ACCESS SECURITY_simplified_abstract_(google llc)]]

Inventor(s): Gang Wang of Frederick MD US for google llc, Nikolaus Rath of Harpenden  GB for google llc

IPC Code(s): G06F21/62

CPC Code(s): G06F21/6218




Abstract: methods, systems, and apparatus, including medium-encoded computer program products, for providing secure workflows with rule-based data access security are described. in one aspect, a method includes receiving a digital component (dc) request. a workflow, which can include customizable stages, for selecting a dc is identified. stages can include executable instructions and can be executed as defined by the workflow. the method can include, for each stage: initiating an isolated environment, receiving a data access request and, for each request, obtaining access rules associated with the request, processing access rules to determine whether to return the data requested by the request, and whenever it is determined to return the data, providing the data to the isolated environment. the method can include, receiving output data from customizable stages and selecting, using a stage and based on the output data received, a dc, which can be sent to the client device.[[Category:G06F21/62]][[Category:CPC_G06F21/6218]][[Category:google llc]]



[[20250094623. METHOD AND SYSTEM FOR ROBUST PSEUDONYMIZATION THAT RETAINS DATA DIVERSITY_simplified_abstract_(google llc)]]

Inventor(s): Alexander Mihlin of San Jose CA US for google llc

IPC Code(s): G06F21/62, G06N20/00

CPC Code(s): G06F21/6245




Abstract: method(s) of determining frequent templates (e.g., single tokens/words used by enough distinct users) and frequent template sets (permutations of the frequent templates) for storage in a pii-free template database are provided, where the frequent template sets can be derived from frequent templates and combined thereof. the frequent template sets can also be indexed with ids for the frequent template sets, where the ids are stored in the pii-free template database in association with the frequent template sets. method of redacting a query is also provided, where the frequent templates and/or the frequent template sets in the pii-free template database can be applied to redact one or more words in a query that potentially reveal personal identifiable information (pii). the query with one or more redacted words can be processed, using a generative model, to generate a pii-free query, for use to train the generative model or other machine learning models.[[Category:G06F21/62]][[Category:G06N20/00]][[Category:CPC_G06F21/6245]][[Category:google llc]]



[[20250094798. Partitioned Inference And Training Of Large Models_simplified_abstract_(google llc)]]

Inventor(s): Li Zhang of Kirkland WA US for google llc, Matthew Sharifi of Kilchberg  CH for google llc, David Petrou of Brooklyn NY US for google llc, Blaise Aguera y Arcas of Seattle WA US for google llc

IPC Code(s): G06N3/08

CPC Code(s): G06N3/08




Abstract: systems and methods for partitioning a large model that has been configured to use a model-synthesis approach in which multiple basis models are combined to generate a final output. the present technology provides systems and methods for identifying a device-specific or subject-specific subset of those basis models to be used on a given device, such that it need not store the weight matrices for the entire set of basis models, and may perform inference using only the weight matrices of the identified subset of basis models. in some examples, the subset of basis models used by a given device may be updated based on actual usage and feedback. likewise, in some examples, the model may be trained in a federated setting in which multiple devices each utilize different subsets of the basis models, and share training signals with a full copy of the model.[[Category:G06N3/08]][[Category:CPC_G06N3/08]][[Category:google llc]]



[[20250094838. Image Analysis by Prompting of Machine-Learned Models Using Chain of Thought_simplified_abstract_(google llc)]]

Inventor(s): Jason Weng Wei of Mountain View CA US for google llc, Dengyong Zhou of Redmond WA US for google llc, Xuezhi Wang of New York NY US for google llc, Dale Eric Schuurmans of Edmonton  CA for google llc, Quoc V. Le of Sunnyvale CA US for google llc, Maarten Paul Bosma of Cupertino CA US for google llc, Ed Huai-Hsin Chi of Palo Alto CA US for google llc, Olivier Jean Andrè Bousquet of Zürich  CH for google llc, Le Hou of South Setauket NY US for google llc, Charles Aloysius Sutton of Santa Clara CA US for google llc, Nathanael Martin Schärli of Mountain View CA US for google llc, Nathan Kemp Sekiguchi Scales of Mountain View CA US for google llc, Augustus Quadrozzi Odena of San Francisco CA US for google llc, Sharan Ajit Narang of Mountain View CA US for google llc, Guy Gur-Ari Krakover of Palo Alto CA US for google llc, Aakanksha Chowdhery of Santa Clara CA US for google llc, David Martin Dohan of San Francisco CA US for google llc, Aitor Lewkowycz of Mountain View CA US for google llc, Jacob Austin of New York NY US for google llc, Henryk Michalewski of Mountain View CA US for google llc, David Luan of Mountain View CA US for google llc, David J. Bieber of New York NY US for google llc, Anders Johan Andreassen of Princeton NJ US for google llc, Maxwell Isaac Nye of Mountain View CA US for google llc

IPC Code(s): G06N5/022

CPC Code(s): G06N5/022




Abstract: an example technique for image analysis is provided. an example image analysis method includes obtaining an instructive sequence descriptive of an instructive query, an instructive response, and an instructive trace of intermediate states from the instructive query to the instructive response. the example image analysis method includes inputting, to a machine-learned model, the instructive sequence and an operative image processing query that comprises image data, wherein the machine-learned model is configured to process the operative query with attention over the instructive sequence. the example method can include generating, using the machine-learned model and responsive to the operative query, an operative image processing response that comprises an analysis of the image data.[[Category:G06N5/022]][[Category:CPC_G06N5/022]][[Category:google llc]]



[[20250094879. Generation and Utilization of Channel Allocation Models for Resource Allocation Recommendations_simplified_abstract_(google llc)]]

Inventor(s): Xinghua Zhao of Jersey City NJ US for google llc

IPC Code(s): G06N20/20, G06N20/10

CPC Code(s): G06N20/20




Abstract: example embodiments of the present disclosure provide for an example method including obtaining data associated with media channels. the example method includes inputting the data into a machine learning model. the example method includes estimating, by the machine learning model, a structure of a causal graph. the example method includes applying a second machine learning model to the causal graph to estimate one or more parameters associated with the causal graph. the example method includes determining an allocation of resources to the media channels based on the causal graph.[[Category:G06N20/20]][[Category:G06N20/10]][[Category:CPC_G06N20/20]][[Category:google llc]]



[[20250094880. Fully Private Ensembles Using Knowledge Transfer_simplified_abstract_(google llc)]]

Inventor(s): Preston Wooju Lee of Bellevue WA US for google llc

IPC Code(s): G06N20/20

CPC Code(s): G06N20/20




Abstract: example embodiments of the present disclosure provide for an example method including obtaining a private dataset. the example method includes dividing the private dataset into a first data subset and a second data subset. the example method includes training a first teacher model using the first data subset and a second teacher model using the second data subset. the example method includes generating the aggregate teacher model based at least in part on the trained first teacher model and the trained second teacher model. the example method can include obtaining a modified dataset that was generated based on a private dataset and labeling the modified dataset by the aggregate teacher model. the example method can include training a publicly available student model using the labeled modified dataset.[[Category:G06N20/20]][[Category:CPC_G06N20/20]][[Category:google llc]]



[[20250095087. SYSTEMS, APPARATUS AND METHODS FOR MANAGING DEMAND-RESPONSE PROGRAMS AND EVENTS_simplified_abstract_(google llc)]]

Inventor(s): Yoky Matsuoka of Palo Alto CA US for google llc, Anthony Michael Fadell of Portola Valley CA US for google llc, Matthew Lee Rogers of Los Gatos CA US for google llc, David Sloo of Menlo Park CA US for google llc, Scott A. McGaraghan of Menlo Park CA US for google llc, Samuel W. Kortz of Palo Alto CA US for google llc

IPC Code(s): G06Q50/06, F24F11/00, F24F11/30, F24F11/46, F24F11/47, F24F11/523, F24F11/58, F24F11/62, F24F11/64, F24F110/10, F24F120/10, F24F120/14, F24F130/00, F24F130/10, F24F140/50, F24F140/60, G05B13/02, G05D23/19, H04L12/28

CPC Code(s): G06Q50/06




Abstract: apparatus, systems, methods, and related computer program products for managing demand-response programs and events. the systems disclosed include an energy management system in operation with an intelligent, network-connected thermostat located at a structure. the thermostat controls an hvac system to cool the structure using a demand response event implementation profile over the demand response event period. the thermostat can also receive a requested change to the setpoint temperatures defined by the demand response event implementation profile and access a determination of an impact on energy shifting that would result if the requested change is incorporated into the demand response event implementation profile. this determination can be communicated to the energy consumer.[[Category:G06Q50/06]][[Category:F24F11/00]][[Category:F24F11/30]][[Category:F24F11/46]][[Category:F24F11/47]][[Category:F24F11/523]][[Category:F24F11/58]][[Category:F24F11/62]][[Category:F24F11/64]][[Category:F24F110/10]][[Category:F24F120/10]][[Category:F24F120/14]][[Category:F24F130/00]][[Category:F24F130/10]][[Category:F24F140/50]][[Category:F24F140/60]][[Category:G05B13/02]][[Category:G05D23/19]][[Category:H04L12/28]][[Category:CPC_G06Q50/06]][[Category:google llc]]



[[20250095224. GENERATIVE VIRTUAL BACKGROUNDS FOR VIDEO CONFERENCING_simplified_abstract_(google llc)]]

Inventor(s): Megha Malpani of San Francisco CA US for google llc, Ameet Jani of Campbell CA US for google llc, Kejia Shao of Santa Clara CA US for google llc, Ryosuke Matsumoto of Dublin CA US for google llc, Nikhil Siva Subash of San Jose CA US for google llc

IPC Code(s): G06T11/00, G06F40/40

CPC Code(s): G06T11/00




Abstract: a video conferencing system may receive, via a user interface of a video conferencing application, a user prompt for a virtual background in a video conference. a video conferencing system may generate a first prompt from the user prompt, the first prompt including an instruction to create a second prompt based on the user prompt. a video conferencing system may receive the second prompt from a text-to-text language model. a video conferencing system may provide the second prompt as an input to an image generation model. a video conferencing system may receive a generated image from the image generation model. a video conferencing system may apply the generated image as the virtual background.[[Category:G06T11/00]][[Category:G06F40/40]][[Category:CPC_G06T11/00]][[Category:google llc]]



[[20250095258. SYSTEMS AND METHODS FOR GENERATING ANIMATIONS FOR 3D OBJECTS USING MACHINE LEARNING_simplified_abstract_(google llc)]]

Inventor(s): Crystal Fong of Belmont CA US for google llc, Nicholas Wasilewski of San Bruno CA US for google llc, Douglas Sim Dietrich, JR. of Los Gatos CA US for google llc

IPC Code(s): G06T13/20, G06V10/70, G06V20/64

CPC Code(s): G06T13/20




Abstract: a method includes identifying a first three-dimensional (3d) object comprising a first animation rig covering a first set of features associated with the first 3d object. an indication of the first 3d object is provided as input to a machine-learning model. the machine-learning model is trained to generate, using a second 3d object comprising a second animation rig, an animation sequence for the first 3d object. the second animation rig covers a second set of features associated with the second 3d object and the second set of features comprises the first set of features and one or more additional features. one or more outputs of the machine-learning model is obtained. the one or more obtained outputs comprise a plurality of animation frames reflecting an animation sequence for the first 3d object.[[Category:G06T13/20]][[Category:G06V10/70]][[Category:G06V20/64]][[Category:CPC_G06T13/20]][[Category:google llc]]



[[20250095406. Continuous Personalization of Face Authentication_simplified_abstract_(google llc)]]

Inventor(s): Cem Kemal Hamami of Seattle WA US for google llc, Philip Andrew Mansfield of Penticton  CA for google llc, Samuel Paradis of Sunol CA US for google llc, Michael Williams of Sunnyvale CA US for google llc, Wen-Sheng Chu of San Jose CA US for google llc

IPC Code(s): G06V40/50, G06V10/762, G06V40/16

CPC Code(s): G06V40/50




Abstract: this document describes systems and techniques that enable continuous personalization of face authentication. in aspects, an authentication system associated with a network includes an authentication manager. the authentication manager receives an embedding representing image data associated with a user's face. the authentication manager generates a confidence score based on the embedding. further, the authentication manager updates previously enrolled embeddings with the embedding based on the confidence score, the embedding meeting a clustering confidence threshold. through such a technique, the authentication manager can alter the previously enrolled embeddings by which a future embedding is used to authenticate the user's face. by so doing, the techniques may provide more-accurate and successful user authentication over time.[[Category:G06V40/50]][[Category:G06V10/762]][[Category:G06V40/16]][[Category:CPC_G06V40/50]][[Category:google llc]]



[[20250095630. SYNTHESIS OF SPEECH FROM TEXT IN A VOICE OF A TARGET SPEAKER USING NEURAL NETWORKS_simplified_abstract_(google llc)]]

Inventor(s): Ye Jia of Mountain View CA US for google llc, Zhifeng Chen of Sunnyvale CA US for google llc, Yonghui Wu of Fremont CA US for google llc, Jonathan Shen of Mountain View CA US for google llc, Ruoming Pang of New York NY US for google llc, Ron J. Weiss of New York NY US for google llc, Ignacio Lopez Moreno of Brooklyn NY US for google llc, Fei Ren of Mountain View CA US for google llc, Yu Zhang of Mountain View CA US for google llc, Quan Wang of Hoboken NJ US for google llc, Patrick An Phu Nguyen of Palo Alto CA US for google llc

IPC Code(s): G10L13/04, G06N3/08, G10L13/02, G10L17/04, G10L19/00

CPC Code(s): G10L13/04




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech synthesis. the methods, systems, and apparatus include actions of obtaining an audio representation of speech of a target speaker, obtaining input text for which speech is to be synthesized in a voice of the target speaker, generating a speaker vector by providing the audio representation to a speaker encoder engine that is trained to distinguish speakers from one another, generating an audio representation of the input text spoken in the voice of the target speaker by providing the input text and the speaker vector to a spectrogram generation engine that is trained using voices of reference speakers to generate audio representations, and providing the audio representation of the input text spoken in the voice of the target speaker for output.[[Category:G10L13/04]][[Category:G06N3/08]][[Category:G10L13/02]][[Category:G10L17/04]][[Category:G10L19/00]][[Category:CPC_G10L13/04]][[Category:google llc]]



[[20250095632. VOICE WRAPPER(S) FOR EXISTING FIRST-PARTY TEXT-BASED CHATBOT(S)_simplified_abstract_(google llc)]]

Inventor(s): Sasha Goldshtein of Tel Aviv  IL for google llc, Yoav Tzur of Tel Aviv  IL for google llc, Gal Moshitch of Jerusalem  IL for google llc, ChiTa Tsai of New York NY US for google llc, Sharon Sultan of Tel Aviv  IL for google llc

IPC Code(s): G10L13/08, G10L15/22, H04L51/02

CPC Code(s): G10L13/08




Abstract: implementations are directed to providing a voice wrapper to an existing first-party text-based chatbot to enable the existing first-party text-based chatbot to engage in corresponding voice-based conversations. the voice wrapper can include a plurality of components. for instance, the voice wrapper can include a plurality of input components for utilization in responding to a spoken utterance, and in lieu of the existing first-party text-based chatbot, and/or to modify input to be provided to the existing first-party text-based chatbot in responding to the spoken utterance. also, for instance, the voice wrapper can include a plurality of output components for utilization in responding to the spoken utterance, to reduce perceived latency of the existing first-party text-based chatbot, and/or to modify output generated by the existing first-party text-based chatbot in responding to the spoken utterance.[[Category:G10L13/08]][[Category:G10L15/22]][[Category:H04L51/02]][[Category:CPC_G10L13/08]][[Category:google llc]]



[[20250095634. Language Agnostic Multilingual End-To-End Streaming On-Device ASR System_simplified_abstract_(google llc)]]

Inventor(s): Bo Li of Fremont CA US for google llc, Tara N. Sainath of Jersey City NJ US for google llc, Ruoming Pang of New York NY US for google llc, Shuo-yiin Chang of Sunnyvale CA US for google llc, Qiumin Xu of Mountain View CA US for google llc, Trevor Strohman of Mountain View CA US for google llc, Vince Chen of Mountain View CA US for google llc, Qiao Liang of Mountain View CA US for google llc, Heguang Liu of Mountain View CA US for google llc, Yanzhang He of Mountain View CA US for google llc, Parisa Haghani of Atlanta GA US for google llc, Sameer Bidichandani of Mountain View CA US for google llc

IPC Code(s): G10L15/00, G10L15/06, G10L15/22, G10L15/30

CPC Code(s): G10L15/005




Abstract: a method includes receiving a sequence of acoustic frames characterizing one or more utterances as input to a multilingual automated speech recognition (asr) model. the method also includes generating a higher order feature representation for a corresponding acoustic frame. the method also includes generating a hidden representation based on a sequence of non-blank symbols output by a final softmax layer. the method also includes generating a probability distribution over possible speech recognition hypotheses based on the hidden representation generated by the prediction network at each of the plurality of output steps and the higher order feature representation generated by the encoder at each of the plurality of output steps. the method also includes predicting an end of utterance (eou) token at an end of each utterance. the method also includes classifying each acoustic frame as either speech, initial silence, intermediate silence, or final silence.[[Category:G10L15/00]][[Category:G10L15/06]][[Category:G10L15/22]][[Category:G10L15/30]][[Category:CPC_G10L15/005]][[Category:google llc]]



[[20250095637. MULTILINGUAL AND CODE-SWITCHING ASR USING LARGE LANGUAGE MODEL GENERATED TEXT_simplified_abstract_(google llc)]]

Inventor(s): Ke Hu of Stony Brook NY US for google llc, Tara N. Sainath of Jersey City NJ US for google llc, Bo Li of Fremont CA US for google llc, Yu Zhang of Mountain View CA US for google llc, Yong Cheng of Mountain View CA US for google llc, Tao Wang of Sunnyvale CA US for google llc, Yujing Zhang of Sunnyvale CA US for google llc, Frederick Liu of Bellevue WA US for google llc

IPC Code(s): G10L15/06, G10L15/00

CPC Code(s): G10L15/063




Abstract: a method includes receiving a textual prompt in a first language and obtaining a fine-tuned prompt embedding configured to guide a large language model (llm) to generate text in a target language from textual prompts in the first language. the method also includes processing, using the llm, the textual prompt conditioned on the fine-tuned prompt embedding to generate output text in the target language and concatenating the textual prompt and the generated output text to provide an unspoken textual utterance. the method also includes training a multilingual automatic speech recognition (asr) model to learn how to recognize speech in the target language by injecting the unspoken textual utterance into a text encoder associated with the multilingual asr model.[[Category:G10L15/06]][[Category:G10L15/00]][[Category:CPC_G10L15/063]][[Category:google llc]]



[[20250095639. USING NON-PARALLEL VOICE CONVERSION FOR SPEECH CONVERSION MODELS_simplified_abstract_(google llc)]]

Inventor(s): Andrew M. Rosenberg of Brooklyn NY US for google llc, Gary Wang of Mountain View CA US for google llc, Bhuvana Ramabhadran of Mt. Kisco NY US for google llc, Fadi Biadsy of Mountain View CA US for google llc

IPC Code(s): G10L15/06, G10L13/02, G10L15/16, G10L15/197, G10L15/22, G10L19/00, G10L19/038, G10L21/003

CPC Code(s): G10L15/063




Abstract: a method includes receiving a set of training utterances each including a non-synthetic speech representation of a corresponding utterance, and for each training utterance, generating a corresponding synthetic speech representation by using a voice conversion model. the non-synthetic speech representation and the synthetic speech representation form a corresponding training utterance pair. at each of a plurality of output steps for each training utterance pair, the method also includes generating, for output by a speech recognition model, a first probability distribution over possible non-synthetic speech recognition hypotheses for the non-synthetic speech representation and a second probability distribution over possible synthetic speech recognition hypotheses for the synthetic speech representation. the method also includes determining a consistent loss term for the corresponding training utterance pair based on the first and second probability distributions and updating parameters of the speech recognition model based on the consistent loss term.[[Category:G10L15/06]][[Category:G10L13/02]][[Category:G10L15/16]][[Category:G10L15/197]][[Category:G10L15/22]][[Category:G10L19/00]][[Category:G10L19/038]][[Category:G10L21/003]][[Category:CPC_G10L15/063]][[Category:google llc]]



[[20250095657. GP-301925-00-US-CON-01 USER AUTHENTICATION, FOR ASSISTANT ACTION, USING DATA FROM OTHER DEVICE(S) IN A SHARED ENVIRONMENT_simplified_abstract_(google llc)]]

Inventor(s): Matthew Sharifi of Kilchberg  CH for google llc, Victor Carbune of Zurich  CH for google llc

IPC Code(s): G10L17/24, G06F21/31, G06F21/34, G06F21/35, G06F21/40, G10L17/02, G10L17/06, G10L17/16, H04L9/32, H04L9/40, H04W12/062

CPC Code(s): G10L17/24




Abstract: implementations set forth herein relate to an automated assistant that can solicit other devices for data that can assist with user authentication. user authentication can be streamlined for certain requests by removing a requirement that all authentication be performed at a single device and/or by a single application. for instance, the automated assistant can rely on data from other devices, which can indicate a degree to which a user is predicted to be present at a location of an assistant-enabled device. the automated assistant can process this data to make a determination regarding whether the user should be authenticated in response to an assistant input and/or pre-emptively before the user provides an assistant input. in some implementations, the automated assistant can perform one or more factors of authentication and utilize the data to verify the user in lieu of performing one or more other factors of authentication.[[Category:G10L17/24]][[Category:G06F21/31]][[Category:G06F21/34]][[Category:G06F21/35]][[Category:G06F21/40]][[Category:G10L17/02]][[Category:G10L17/06]][[Category:G10L17/16]][[Category:H04L9/32]][[Category:H04L9/40]][[Category:H04W12/062]][[Category:CPC_G10L17/24]][[Category:google llc]]



[[20250095690. Automatic Generation of Support Video from Source Video_simplified_abstract_(google llc)]]

Inventor(s): Pei-Yu Chi of Menlo Park CA US for google llc, Sen-Po Hu of Menlo Park CA US for google llc, Irfan Aziz Essa of Atlanta GA US for google llc, Tao Dong of Cupertino CA US for google llc

IPC Code(s): G11B27/031, G06F40/166, G06F40/40, G06T13/20, G06T13/40, G06V20/50, G06V40/16, G11B27/34

CPC Code(s): G11B27/031




Abstract: provided are systems and methods for the automatic generation of support videos from a source video. for example, the support video can more deeply explain or elaborate upon content included in source video. in particular, a computing system can obtain a source video and extract one or more sets of textual content associated with the source video. for example, the sets of textual content can include a transcript of speech that occurs within the source video. the computing system can process the one or more sets of textual content with a generative sequence processing model to generate, as an output of the generative sequence processing model, additional textual content for a support video.[[Category:G11B27/031]][[Category:G06F40/166]][[Category:G06F40/40]][[Category:G06T13/20]][[Category:G06T13/40]][[Category:G06V20/50]][[Category:G06V40/16]][[Category:G11B27/34]][[Category:CPC_G11B27/031]][[Category:google llc]]



[[20250097168. VOICE WRAPPER(S) FOR EXISTING THIRD-PARTY TEXT-BASED CHATBOT(S)_simplified_abstract_(google llc)]]

Inventor(s): Sasha Goldshtein of Tel Aviv  IL for google llc, Yoav Tzur of Tel Aviv  IL for google llc, Shlomo Fruchter of Ness Ziona  IL for google llc, Gal Moshitch of Jerusalem  IL for google llc, ChiTa Tsai of New York NY US for google llc, Sharon Sultan of Tel Aviv  IL for google llc

IPC Code(s): H04L51/02, G10L13/08, G10L15/22

CPC Code(s): H04L51/02




Abstract: implementations are directed to providing a voice wrapper to an existing third-party text-based chatbot to enable the existing third-party text-based chatbot to engage in corresponding voice-based conversations. the voice wrapper can include a plurality of components. for instance, the voice wrapper can include a plurality of input components for utilization in responding to a spoken utterance, and in lieu of the existing third-party text-based chatbot, and/or to modify input to be provided to the existing third-party text-based chatbot in responding to the spoken utterance. also, for instance, the voice wrapper can include a plurality of output components for utilization in responding to the spoken utterance, to reduce perceived latency of the existing third-party text-based chatbot, and/or to modify output generated by the existing third-party text-based chatbot in responding to the spoken utterance.[[Category:H04L51/02]][[Category:G10L13/08]][[Category:G10L15/22]][[Category:CPC_H04L51/02]][[Category:google llc]]



[[20250097218. Integrated Second Factor Authentication_simplified_abstract_(google llc)]]

Inventor(s): Erica Wickstrom Brand of Palo Alto CA US for google llc, Marius Paul Michiel Schilder of Sunnyvale CA US for google llc, Scott D. Johnson of Cupertino CA US for google llc, Vincent Palatin of Zurich  CH for google llc

IPC Code(s): H04L9/40, G06F21/34, H04W4/80, H04W12/041, H04W12/069, H04W12/68

CPC Code(s): H04L63/0853




Abstract: techniques and apparatuses are described that enable integrated second factor authentication. these techniques and apparatuses enable the improved security of something you have without the accompanying inconvenience or chance of loss. to do so, a secure physical entity is integrated within a computing device. while this provides the something you have without a need to carry a separate object with you, the something you have also must not be able to be accessed remotely. to prevent remote access physical wires are connected from the secure physical entity to physical structures on the computing device. in this way, a hacker or cyber thief cannot convince an authentication system that the cyber attacker does indeed have the something you have because to do so the attacker must be in physical possession of the computing device.[[Category:H04L9/40]][[Category:G06F21/34]][[Category:H04W4/80]][[Category:H04W12/041]][[Category:H04W12/069]][[Category:H04W12/68]][[Category:CPC_H04L63/0853]][[Category:google llc]]



[[20250097253. THREAT INDICATOR ALERT GENERATION BASED ON PRIORITIZATION MODELS_simplified_abstract_(google llc)]]

Inventor(s): Erik Shih-Hau Huang of Pasadena CA US for google llc, Benjamin Henry Walter of Austin TX US for google llc, Eric James Stennett of Austin TX US for google llc, Ricardo Correa of Austin TX US for google llc, Barbara Davila of Austin TX US for google llc, Benjamin Zachary Withnell of New York NY US for google llc, John Whitcomb of Spokane WA US for google llc, Jeremiah David Warren of Senoia GA US for google llc, Moses Daniel Schwartz of Clayton CA US for google llc

IPC Code(s): H04L9/40, H04L41/16

CPC Code(s): H04L63/1433




Abstract: a method includes receiving, at a security platform, a plurality of threat indicators associated with current intrusive activities with respect to computing resources of a first entity and receiving, at the security platform, a plurality of threat datasets associated with prior intrusive activities with respect to computing resources associated with one or more entities including the first entity. the method further includes receiving, at the security platform, a plurality of environmental datasets associated with the computing resources of the first entity and determining an alert level associated with a first threat indicator of the plurality of threat indicators based on the plurality of threat datasets and the plurality of environmental datasets. the method further includes generating, responsive to the alert level satisfying an alert threshold criterion, an alert associated with the first threat indicator for one or more users of the first entity.[[Category:H04L9/40]][[Category:H04L41/16]][[Category:CPC_H04L63/1433]][[Category:google llc]]



[[20250097317. Streaming Network Monitoring Caching Infrastructure_simplified_abstract_(google llc)]]

Inventor(s): Carl Lebsack of Felton CA US for google llc, Robert Shakir of San Francisco CA US for google llc, Paul Borman of Inver Grove Heights MN US for google llc, Marcus Hines of Mountain View CA US for google llc, Anees Shaikh of San Jose CA US for google llc, Joshua George of Santa Clara CA US for google llc

IPC Code(s): H04L67/568, G06F12/0813, H04L41/14, H04L43/02, H04L49/90

CPC Code(s): H04L67/568




Abstract: systems and methods of network telemetry caching and distribution are provided. the system can receive network telemetry data and store it as a plurality of data nodes. the system can maintain a node pointer map and a node pointer queue. if the system receives an update to a data node having a corresponding node pointer not already present in the node pointer map, the system can add the node pointer to the node pointer queue and to the node pointer map with a count of zero. if the node pointer is already present in the node pointer map, the system can increment the node count for the node pointer in the node pointer map and not add the node pointer to the node pointer queue. the system can transmit data values and node counts to the client device for each node pointer in the node pointer queue.[[Category:H04L67/568]][[Category:G06F12/0813]][[Category:H04L41/14]][[Category:H04L43/02]][[Category:H04L49/90]][[Category:CPC_H04L67/568]][[Category:google llc]]



[[20250097331. Housing Assemblies_simplified_abstract_(google llc)]]

Inventor(s): Trevor Matthew Cardiff of Walnut Creek CA US for google llc, Charles Barnard Woodhull of Glen Ellyn IL US for google llc, Warren Zachary Jones of Glen Ellyn IL US for google llc, Kliulai Chow-Yee of San Francisco CA US for google llc, Joseph L. Allore of Mundelein IL US for google llc, James Leonard Tanner of Glen Ellyn IL US for google llc

IPC Code(s): H04M1/02

CPC Code(s): H04M1/0249




Abstract: techniques and apparatuses are described that implement housing assemblies for computing devices. in aspects, a housing assembly includes an elongated side-frame element comprising a first metal and a cast internal frame comprising a second, different, metal. the melting point of the first metal is higher than the melting point of the second metal. the elongated side-frame element may include at least one elongated slot disposed on an inner surface of the elongated side-frame element, with the elongated slot oriented parallel to the elongated side-frame element. the slot may include at least one undercut. the cast internal frame may include an elongated interlock flange that extends from an internal frame body. the elongated interlock flange received into the elongated slot of the elongated side-frame element. this document also describes methods for manufacturing a computing device housing assembly and a product-by-process.[[Category:H04M1/02]][[Category:CPC_H04M1/0249]][[Category:google llc]]



[[20250097375. GENERATING A VIRTUAL PRESENTATION STAGE FOR PRESENTATION IN A USER INTERFACE OF A VIDEO CONFERENCE_simplified_abstract_(google llc)]]

Inventor(s): Patrick Axel Völcker of Hamburg  DE for google llc, Irina Dietrich of Hamburg  DE for google llc, Ryan Hamilton Nelson of Walnut Creek CA US for google llc, Harbir Singh Bharaj of Henstedt-Ulzburg  DE for google llc, Jörg Hösel of Hamburg  DE for google llc

IPC Code(s): H04N5/272

CPC Code(s): H04N5/272




Abstract: systems and methods for generating a virtual presentation stage for presentation in a user interface of a video conference are provided. a first participant video stream representing a first participant of a plurality of participants of a video conference is received from a camera of a first client device of the first participant. a combined video stream is created comprising a background image, one or more images representing one or more content items presentable by the first participant during the video conference, the first participant video stream, and one or more teleprompter notes associated with at least one of the one or more content items. a user interface (ui) is provided for display on the first client device of the first participant, wherein the ui comprises a visual item corresponding to the combined video stream while the first participant is presenting at least one of the one or more content items to one or more other participants of the video conference.[[Category:H04N5/272]][[Category:CPC_H04N5/272]][[Category:google llc]]



[[20250097553. Camera Module with Electrostatic Discharge Protection_simplified_abstract_(google llc)]]

Inventor(s): Jingyu Huang of Santa Clara CA US for google llc, Liang Ching Tseng of Taipei City  TW for google llc, Tsung-Dar Cheng of Taipei City  TW for google llc, Alexander P. Wroblewski of San Francisco CA US for google llc, Weifeng Pan of Palo Alto CA US for google llc, Warwick Ka Kui Wong of Palo Alto CA US for google llc

IPC Code(s): H04N23/52, H04N23/55, H04N23/57

CPC Code(s): H04N23/52




Abstract: the present document describes a camera module with electrostatic discharge (esd) protection. in particular, the camera module includes a lightning rod structure, which guides an esd current to a safe location (e.g., system ground) when a lens retainer of the camera module is hit by an esd spark. due to the impact on camera focus tuning and the risk of audio rub and buzz, the lightning rod structure does not physically touch the lens retainer. as such, a gap separates the lightning rod structure from the lens retainer. when the lens retainer is stressed by an esd spark, the gap is broken down and a conductive path is established to guide the esd current to the safe location through the lightning rod structure. in this way, the esd current flows along a controlled path instead of jumping to arbitrary locations, which protects nearby susceptible circuitry.[[Category:H04N23/52]][[Category:H04N23/55]][[Category:H04N23/57]][[Category:CPC_H04N23/52]][[Category:google llc]]



[[20250097623. DUAL BAND WIRELESS COMMUNICATIONS FOR MULTIPLE CONCURRENT AUDIO STREAMS_simplified_abstract_(google llc)]]

Inventor(s): Daniel Barros of Sra da Hora  PT for google llc

IPC Code(s): H04R1/10

CPC Code(s): H04R1/1041




Abstract: various arrangements for performing wireless device-to-device communication are presented. an audio output device, such as an earbud or pair of earbuds, can establish a connection with an audio source via a first bluetooth interface that communicates using a bluetooth communication protocol on a 2.4 ghz bluetooth frequency band. the audio output device can negotiate that bluetooth frequency-shifted communication, such as on a 5 or 6 ghz frequency band, is available for use with the audio source. the audio output device may then perform bluetooth frequency-shifted communication with the audio source such that the audio output device receives an audio stream from the audio source using bluetooth frequency-shifted communication and the bluetooth communication protocol.[[Category:H04R1/10]][[Category:CPC_H04R1/1041]][[Category:google llc]]



[[20250097661. Three-Dimensional, Direction-Dependent Audio for Multi-Entity Telecommunication_simplified_abstract_(google llc)]]

Inventor(s): Shahabuddin Kakargola of Costa Mesa CA US for google llc

IPC Code(s): H04S7/00, G06F3/16, H04L65/1083, H04L65/403, H04L65/75

CPC Code(s): H04S7/306




Abstract: the document describes systems and techniques directed at three-dimensional, direction-dependent audio for multi-entity telecommunication. in aspects, a remote device receives multi-stream content, including at least one audio stream, from one or more audio-producing entities and obtains orientation information associated with the one or more audio-producing entities. the remote device can then, using the at least one audio stream and the orientation information, provide direction-dependent, three-dimensional audio sufficient to enable a multi-stereo audio output device to reproduce the spatial audio as if the at least one audio stream is originating from a direction, an elevation, and/or a proximity that corresponds to a physical location of the one or more audio-producing entities.[[Category:H04S7/00]][[Category:G06F3/16]][[Category:H04L65/1083]][[Category:H04L65/403]][[Category:H04L65/75]][[Category:CPC_H04S7/306]][[Category:google llc]]



[[20250097829. MANAGING SYSTEM INFORMATION COMMUNICATION IN SMALL DATA TRANSMISSION_simplified_abstract_(google llc)]]

Inventor(s): Chih-Hsiang Wu of Taoyuan City  TW for google llc

IPC Code(s): H04W48/14, H04W74/08

CPC Code(s): H04W48/14




Abstract: a user equipment (ue) performs a method of obtaining system information. the method includes disabling () a system information request function of the ue while the ue is in an inactive state and, while the system information request function is disabled and the ue is in the inactive state, communicating () with a radio access network (ran) using small data transmission (sdt). the method also includes enabling () the system information request function of the ue when the ue is no longer communicating with the ran using sdt.[[Category:H04W48/14]][[Category:H04W74/08]][[Category:CPC_H04W48/14]][[Category:google llc]]



[[20250097866. MEASUREMENT GAP MANAGEMENT IN A NON-TERRESTRIAL NETWORK_simplified_abstract_(google llc)]]

Inventor(s): Ming-Hung TAO of Taoyuan City  TW for google llc, Chih-Hsiang WU of Taoyuan City  TW for google llc

IPC Code(s): H04W56/00, H04W74/0833, H04W84/06

CPC Code(s): H04W56/0015




Abstract: a user equipment (ue) receives, from a non-terrestrial network (ntn), a measurement configuration that indicates a timing pattern for inter-frequency measurement, the timing pattern including a measurement gap of a certain duration. the ue receives, from the ntn, a synchronization signal during the measurement gap in accordance with the timing pattern, performs a measurement of the synchronization signal; and transmits, to the ntn, an indication related to the measurement gap. for example, the indication may be a request to terminate early the measurement gap.[[Category:H04W56/00]][[Category:H04W74/0833]][[Category:H04W84/06]][[Category:CPC_H04W56/0015]][[Category:google llc]]



[[20250098028. Configuring Resources for Multicast and/or Broadcast Services in a Distributed Base Station Architecture_simplified_abstract_(google llc)]]

Inventor(s): Chih-Hsiang Wu of Mountain View CA US for google llc

IPC Code(s): H04W76/40, H04W76/12, H04W76/28

CPC Code(s): H04W76/40




Abstract: a distributed unit (du) of a distributed base station including a central unit (cu) and the du can implement a method for configuring a user equipment (ue) to receive multicast and/or broadcast services (mbs). the method may include: receiving (), from the cu, a cu-to-du message identifying an mbs session and requesting that the du configure resources for the mbs session; and transmitting (), to the ue in response to receiving the cu-to-du message, configuration parameters for receiving the mbs session.[[Category:H04W76/40]][[Category:H04W76/12]][[Category:H04W76/28]][[Category:CPC_H04W76/40]][[Category:google llc]]



[[Google LLC patent applications on March 20th, 2025]]



[[Category:Google LLC]] [[Category:G10L15/06]] [[Category:G10L15/22]] [[Category:H04L9/40]] [[Category:G06F16/9535]] [[Category:G06N20/20]]