View source for Google LLC patent applications on May 16th, 2024

=Patent Applications by Google LLC on May 16th, 2024=



[[:Category:Google LLC|Google LLC]]: 45 patent applications[[Category:Google LLC]]

Google LLC has applied for patents in the areas of [[:Category:G10L15/22|G10L15/22]] (8), [[:Category:G06N3/08|G06N3/08]] (6), [[:Category:G06N3/045|G06N3/045]] (6), [[:Category:G06N20/00|G06N20/00]] (6), [[:Category:G06V10/774|G06V10/774]] (6)

With keywords such as: device, user, data, input, object, audio, based, quantum, respective, and image in patent application abstracts.




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


[[20240160251.Display Assistant Device_simplified_abstract_(google llc)]]

Inventor(s): Justin Leong of Milpitas CA (US) for google llc, Xiaoping Qin of San Jose CA (US) for google llc, Christen Cameron Bilger of Sunnyvale CA (US) for google llc, Philip Hobson Boothby of Scotts Valley CA (US) for google llc, Frances Kwee of Redwood City CA (US) for google llc, Matthew Michael Seflic of San Jose CA (US) for google llc, James Castro of San Jose CA (US) for google llc

IPC Code(s): G06F1/16, G02F1/1333, G02F1/1337, G06F3/16, G06F21/83, G10L15/28, H04R1/02, H04R1/34




Abstract: this application is directed to a display assistant device that acts as a voice-activated user interface device. the display assistant device includes a base, a screen and a rear speaker. the base is configured for sitting on a surface. the screen has a rear surface and is supported by the base at the rear surface. a bottom edge of the screen is configured to be held above the surface by a predefined height, and the base is substantially hidden behind the screen from a front view of the display assistant device. the rear speaker is concealed inside the base and oriented to project sound towards the rear side of the base.[[Category:G06F1/16]][[Category:G02F1/1333]][[Category:G02F1/1337]][[Category:G06F3/16]][[Category:G06F21/83]][[Category:G10L15/28]][[Category:H04R1/02]][[Category:H04R1/34]][[Category:google llc]]



[[20240160298.POINT AND GESTURE CONTROL OF REMOTE DEVICES_simplified_abstract_(google llc)]]

Inventor(s): Rajeev Nongpiur of Mountain View CA (US) for google llc, Roy Want of Los Altos CA (US) for google llc, Qian Zhang of Santa Clara CA (US) for google llc, JinJie Chen of Sunnyvale CA (US) for google llc, Der-Woei Wu of Mountain View CA (US) for google llc, Cody Wortham of San Francisco CA (US) for google llc, Aleksandr Salo of Santa Clara CA (US) for google llc, Marie Vachovsky of Mountain View CA (US) for google llc

IPC Code(s): G06F3/0354, G06F3/01




Abstract: techniques for controlling a remotely controllable device are described. in an example, a mobile device detects a remotely controllable device, measures a distance and direction from the mobile device to the remotely controllable device, and determines from the distance and direction that the mobile device is pointing at the remotely controllable device. in response to determining that the mobile device is in a handheld position, is pointing at the remotely controllable device, or both, the mobile device monitors for a movement of the mobile device according to a prescribed gesture. in response to detecting that the mobile device was moved according to the prescribed gesture, the mobile device presents a collection of selectable actions control operations of the remotely controllable device.[[Category:G06F3/0354]][[Category:G06F3/01]][[Category:google llc]]



[[20240160346.BACK GESTURE PREVIEW ON COMPUTING DEVICES_simplified_abstract_(google llc)]]

Inventor(s): Rohan Ketan Shah of Mountain View CA (US) for google llc, Yuan Hang Li of Milpitas CA (US) for google llc, Arif Huda of Dallas TX (US) for google llc, JT DiMartile of Seattle WA (US) for google llc, Nicholas John Bearman of London  (GB) for google llc, Selim Flavio Cinek of Zürich  (CH) for google llc, Shan Huang of Daly City CA (US) for google llc, Vadim René Marius Caen of Zürich  (CH) for google llc, Jonas Alon Naimark of San Francisco CA (US) for google llc, Ian Lake of Sunnyvale CA (US) for google llc, Jorim Dorian Jaggi of Zürich  (CH) for google llc

IPC Code(s): G06F3/04883, G06F3/0483




Abstract: an example method includes, outputting, for display by a display device, a graphical user interface of an application executing at a computing device; responsive to receiving an indication of a start of a user input swipe gesture: outputting, for display by the display device and at least partially concealed by the scaled version of the graphical user interface of the application, a visual indication of a result of the user input swipe gesture: and responsive to receiving an indication of a commitment of the user input swipe gesture, outputting, for display by the display device, a graphical user interface that corresponds to the result of the user input swipe gesture.[[Category:G06F3/04883]][[Category:G06F3/0483]][[Category:google llc]]



[[20240160375.GARBAGE COLLECTION FOR DATA STORAGE_simplified_abstract_(google llc)]]

Inventor(s): Konstantinos Nikoloudakis of San Francisco CA (US) for google llc, Sven Koehler of Sunnyvale CA (US) for google llc, Danyao Wang of Kitchener  (CA) for google llc, Sahand Saba of Kitchener  (CA) for google llc, Long Fei of Campbell CA (US) for google llc, Simon Tyler Wise of New Hamburg  (CA) for google llc, David Halladay Schneider of Mountain View CA (US) for google llc

IPC Code(s): G06F3/06




Abstract: methods, systems, apparatus, including computer programs encoded on computer storage media, for reclaiming storage space in a storage environment. in one aspect, the method includes actions of aggregating data that is indicative of access to one or more data objects, determining a future storage cost associated with each of a plurality of data objects, determining an access window for each of the plurality of data objects, identifying a data object based on (i) the future storage cost that satisfies a predetermined threshold and (ii) a data object access window, providing a notification to a user device that requests feedback from a user indicating whether the data object can be deleted, and in response to receiving data that indicates that the data object can be deleted, generating an instruction to cause deletion of the data object upon the expiration of the access window.[[Category:G06F3/06]][[Category:google llc]]



[[20240160399.Spatial Rediscovery Using On-Device Hardware_simplified_abstract_(google llc)]]

Inventor(s): Wei Liang Liu of Taoyuan  (TW) for google llc, Pei-Chen Chuang of Taipei  (TW) for google llc

IPC Code(s): G06F3/16




Abstract: this document describes systems and techniques for facilitating spatial rediscovery using on-device hardware. for example, an audio input mechanism associated with a compact device can be activated and an audio signal can be generated by an audio output mechanism associated with an external device. the audio signal can be received at the audio input mechanism associated with the compact device. the receipt of the audio signal may cause the audio input mechanism to produce electrical signals having encoded information associated with the audio signal. the electrical signals can then be transmitted to the external device as wireless signals. based on an analysis of the transmitted wireless signals, a spatial positioning of the compact device relative to the external device can be determined. based on the determination of the spatial positioning, a location indicator can be provided via the external device.[[Category:G06F3/16]][[Category:google llc]]



[[20240160403.MULTI-MODAL INPUT ON AN ELECTRONIC DEVICE_simplified_abstract_(google llc)]]

Inventor(s): Brandon M. Ballinger of San Franciso CA (US) for google llc, Johan Schalkwyk of Scarsdale NY (US) for google llc, Michael H. Cohen of Portola Valley CA (US) for google llc, William J. Byrne of Davis CA (US) for google llc, Gudmundur Hafsteinsson of Los Gatos CA (US) for google llc, Michael J. Lebeau of New York NY (US) for google llc

IPC Code(s): G06F3/16, G06F3/04886, G06F40/284, G06F40/58, G10L15/00, G10L15/18, G10L15/183, G10L15/22, G10L15/26, G10L15/30




Abstract: a computer-implemented input-method editor process includes receiving a request from a user for an application-independent input method editor having written and spoken input capabilities, identifying that the user is about to provide spoken input to the application-independent input method editor, and receiving a spoken input from the user. the spoken input corresponds to input to an application and is converted to text that represents the spoken input. the text is provided as input to the application.[[Category:G06F3/16]][[Category:G06F3/04886]][[Category:G06F40/284]][[Category:G06F40/58]][[Category:G10L15/00]][[Category:G10L15/18]][[Category:G10L15/183]][[Category:G10L15/22]][[Category:G10L15/26]][[Category:G10L15/30]][[Category:google llc]]



[[20240160497.COMPUTATIONAL GRAPH CRITICAL SECTIONS_simplified_abstract_(google llc)]]

Inventor(s): Eugene Brevdo of San Bruno CA (US) for google llc, Alexandre Tachard Passos of San Francisco CA (US) for google llc

IPC Code(s): G06F9/52, G06F9/46, G06F9/48, G06F9/50, G06F16/901




Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing critical section subgraphs in a computational graph system. one of the methods includes executing a lock operation including providing, by a task server, a request to a value server to create a shared critical section object. if the task server determines that the shared critical section object was created by the value server, the task server executes one or more other operations of the critical section subgraph in serial. the task server executes an unlock operation including providing, by the task server, a request to the value server to delete the shared critical section object.[[Category:G06F9/52]][[Category:G06F9/46]][[Category:G06F9/48]][[Category:G06F9/50]][[Category:G06F16/901]][[Category:google llc]]



[[20240160499.Augmenting Handling of Logs Generated in PaaS Environments_simplified_abstract_(google llc)]]

Inventor(s): Tissa Rohitha Senevirathne of Sunnyvale CA (US) for google llc, Bo Eric Wang of Seattle WA (US) for google llc, Carlos Lugtu of Mountain View CA (US) for google llc, Bharadwaj Venkateswara Sridhar Subramanian of San Jose CA (US) for google llc, Madhukar Narayan Thakur of San Jose CA (US) for google llc

IPC Code(s): G06F9/54, G06F21/62




Abstract: a method for augmenting handling of logs generated in platform as a system (paas) environments includes transmitting, to an external cloud computing environment, an application programming interface (api) request. the api request includes a trace identification (id), a concealment indicator, and a policy id. the method also includes updating the first entry in the first log corresponding to the api request based on the trace id and the concealment indicator. the method also includes storing the first entry in the first log corresponding to the api request based on the storage criteria of the policy id.[[Category:G06F9/54]][[Category:G06F21/62]][[Category:google llc]]



[[20240160594.CONNECTING NON-PCIe ACCELERATORS AS PCIe DEVICES_simplified_abstract_(google llc)]]

Inventor(s): Yiftach Benjamini of Givat Elah  (IL) for google llc, Jonathan Charles Masters of Boston MA (US) for google llc, Henrietta Bezbroz of Or Akiva  (IL) for google llc

IPC Code(s): G06F13/42




Abstract: generally disclosed herein is an approach for enabling the connection of non-pcie accelerators as pcie devices using a peripheral component interconnect express (pcie) abstraction layer (“pal”). once the operating system accesses and configures any on-soc devices and accelerators using standard pcie apis, all pcie configuration transactions may be routed to the pal. the pal's firmware may present the operating system with a virtual pcie space that contains all available soc pcie and non-pcie devices. the firmware of the pal may translate pcie configuration transactions into device-specific configuration transactions.[[Category:G06F13/42]][[Category:google llc]]



[[20240160641.DISTRIBUTED DATABASE CONFIGURATION_simplified_abstract_(google llc)]]

Inventor(s): Alexander Shraer of Stanford CA (US) for google llc, Artyom Sharov of Haifa  (IL) for google llc, Arif Abdulhusein Merchant of Los Altos CA (US) for google llc, Brian F. Cooper of San Jose CA (US) for google llc

IPC Code(s): G06F16/27, G06F16/25, G06F16/955, H04L67/1023, H04L67/1025, H04L67/1097, H04L67/52




Abstract: replicas are selected in a large distributed network, and the roles for these replicas are identified. in one example, a leader is selected from among candidate computing clusters. to make this selection, an activity monitor predicts or monitors the workload of one or more clients. different activities of the workload are given corresponding weights. the delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.[[Category:G06F16/27]][[Category:G06F16/25]][[Category:G06F16/955]][[Category:H04L67/1023]][[Category:H04L67/1025]][[Category:H04L67/1097]][[Category:H04L67/52]][[Category:google llc]]



[[20240160678.DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES_simplified_abstract_(google llc)]]

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, H04L67/50




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.[[Category:G06F16/9535]][[Category:G06F16/906]][[Category:G06N20/00]][[Category:H04L67/50]][[Category:google llc]]



[[20240160680.Integration Of Web And Media Snippets Into Map Applications_simplified_abstract_(google llc)]]

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

IPC Code(s): G06F16/9537, G01C21/34, G01C21/36, G06F16/29, G06F16/9538, G06F40/103, G06T11/60




Abstract: the technology relates to integrating web content into a map application. a query is sent from the map application. at least one snippet of web content identified as relevant to the query is received in response to the query, the at least one snippet of content including a portion of media or textual content from a source on the web. the portion of media or textual content is formatted for display in the map application and output for display in the map application.[[Category:G06F16/9537]][[Category:G01C21/34]][[Category:G01C21/36]][[Category:G06F16/29]][[Category:G06F16/9538]][[Category:G06F40/103]][[Category:G06T11/60]][[Category:google llc]]



[[20240160723.Data Transfer in Secure Processing Environments_simplified_abstract_(google llc)]]

Inventor(s): Justin Lewis of South San Francisco CA (US) for google llc, Scott Davies of Santa Monica CA (US) for google llc

IPC Code(s): G06F21/53, G06F9/445, G06F16/432, H04L67/53




Abstract: data transfer in a secure processing environment is provided. a digital assistant can receive audio input detected by a microphone of a computing device. the digital assistant can determine, based on the audio input, to invoke a third-party application associated with the computing device. the digital assistant can generate, responsive to the determination to invoke the third-party application, a packaged data object. the digital assistant can forward, to the third-party application invoked by the digital assistant component to execute in a secure processing environment on the computing device, the packaged data object. the third-party application can transmit, responsive to a digital component request triggered in the third-party application, the packaged data object to a digital component selector to execute a real-time selection process based on the packaged data object.[[Category:G06F21/53]][[Category:G06F9/445]][[Category:G06F16/432]][[Category:H04L67/53]][[Category:google llc]]



[[20240160779.PRIVACY PRESERVING APPLICATION AND DEVICE ERROR DETECTION_simplified_abstract_(google llc)]]

Inventor(s): Gang Wang of Frederick MD (US) for google llc, Marcel M. Moti Yung of New York NY (US) for google llc, David Bruce Turner of Newark CA (US) for google llc

IPC Code(s): G06F21/62, G06F21/44, G06F21/57, H04L9/32




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting errors in a client device and its associated applications while preserving the privacy of the user of the device. methods can include obtaining and blinding contextual application data for an application on a device. data regarding the application's digital certificate and device trustworthiness data are obtained and provided to a trust assessment server along with the blinded data. this server can provide indications that the device is trustworthy and the application is authentic, and can digitally sign the blinded data. the digital signature can be validated and the unblinded contextual application data can be obtained. if the unblinded data matches the contextual application data, the application can provide the digital signature, the indications, and the unblinded contextual application data to an error detection server, which in turn can indicate the application does not have errors.[[Category:G06F21/62]][[Category:G06F21/44]][[Category:G06F21/57]][[Category:H04L9/32]][[Category:google llc]]



[[20240160783.USER CONSENT FRAMEWORK_simplified_abstract_(google llc)]]

Inventor(s): Gang Wang of Frederick MD (US) for google llc, Yian Gao of Sunnyvale CA (US) for google llc

IPC Code(s): G06F21/62, G06F21/60




Abstract: methods, systems, and apparatus, including an apparatus for managing user data according to user consent settings are described. in some aspects, a method includes determining that a request for transmission by a client device to a recipient will include user data of a user of the client device. in response determining that the request will include the user data, the method includes requesting, from a consent management module of the client device, current user consent settings specified by the user which define at least one of (i) user data that can be transmitted from the client device, (ii) how user data transmitted from the client device can be used or (iii) which recipients can receive and retain user data from the client device. the method further includes receiving, from the consent management module, the current user consent settings and generating request data according the current user consent settings.[[Category:G06F21/62]][[Category:G06F21/60]][[Category:google llc]]



[[20240160857.Contrastive Pre-Training for Language Tasks_simplified_abstract_(google llc)]]

Inventor(s): Thang Minh Luong of Santa Clara CA (US) for google llc, Quoc V. Le of Sunnyvale CA (US) for google llc, Kevin Stefan Clark of San Francisco CA (US) for google llc

IPC Code(s): G06F40/40, G06N5/04, G06N20/00




Abstract: systems and methods are provided that train a machine-learned language encoding model through the use of a contrastive learning task. in particular, the present disclosure describes a contrastive learning task where the encoder learns to distinguish input tokens from plausible alternatives. in some implementations, on each training example the proposed method masks out some subset (e.g., 15%) of the original input tokens, replaces the masked tokens with samples from a “generator” (e.g., which may be a small masked language model), and then trains the encoder to predict whether each token comes from the original data or is a replacement produced by the generator.[[Category:G06F40/40]][[Category:G06N5/04]][[Category:G06N20/00]][[Category:google llc]]



[[20240160909.SHARED SCRATCHPAD MEMORY WITH PARALLEL LOAD-STORE_simplified_abstract_(google llc)]]

Inventor(s): Thomas Norrie of Mountain View CA (US) for google llc, Andrew Everett Phelps of Middleton WI (US) for google llc, Norman Paul Jouppi of Palo Alto CA (US) for google llc, Matthew Leever Hedlund of Sun Prairie WI (US) for google llc

IPC Code(s): G06N3/063, G06F9/54, G06F13/16, G06F15/80, G06F17/16




Abstract: methods, systems, and apparatus, including computer-readable media, are described for a hardware circuit configured to implement a neural network. the circuit includes a first memory, respective first and second processor cores, and a shared memory. the first memory provides data for performing computations to generate an output for a neural network layer. each of the first and second cores include a vector memory for storing vector values derived from the data provided by the first memory. the shared memory is disposed generally intermediate the first memory and at least one core and includes: i) a direct memory access (dma) data path configured to route data between the shared memory and the respective vector memories of the first and second cores and ii) a load-store data path configured to route data between the shared memory and respective vector registers of the first and second cores.[[Category:G06N3/063]][[Category:G06F9/54]][[Category:G06F13/16]][[Category:G06F15/80]][[Category:G06F17/16]][[Category:google llc]]



[[20240160937.TRAINING IMAGE-TO-IMAGE TRANSLATION NEURAL NETWORKS_simplified_abstract_(google llc)]]

Inventor(s): Rui Zhang of Beijing  (CN) for google llc, Jia Li of Palo Alto CA (US) for google llc, Tomas Jon Pfister of Foster City CA (US) for google llc

IPC Code(s): G06N3/084, G06F18/21, G06F18/2134, G06F18/214, G06F18/22, G06F18/2413, G06N3/045, G06N3/047, G06V10/74, G06V10/764, G06V10/774, G06V10/82




Abstract: a method includes obtaining a source training dataset that includes a plurality of source training images and obtaining a target training dataset that includes a plurality of target training images. for each source training image, the method includes translating, using the forward generator neural network g, the source training image to a respective translated target image according to current values of forward generator parameters. for each target training image, the method includes translating, using a backward generator neural network f, the target training image to a respective translated source image according to current values of backward generator parameters. the method also includes training the forward generator neural network g jointly with the backward generator neural network f by adjusting the current values of the forward generator parameters and the backward generator parameters to optimize an objective function.[[Category:G06N3/084]][[Category:G06F18/21]][[Category:G06F18/2134]][[Category:G06F18/214]][[Category:G06F18/22]][[Category:G06F18/2413]][[Category:G06N3/045]][[Category:G06N3/047]][[Category:G06V10/74]][[Category:G06V10/764]][[Category:G06V10/774]][[Category:G06V10/82]][[Category:google llc]]



[[20240160948.PROCESSING COMPUTATIONAL GRAPHS_simplified_abstract_(google llc)]]

Inventor(s): Paul A. Tucker of Los Altos CA (US) for google llc, Jeffrey Adgate Dean of Palo Alto CA (US) for google llc, Sanjay Ghemawat of Mountain View CA (US) for google llc, Yuan Yu of Cupertino CA (US) for google llc

IPC Code(s): G06N3/098, G06F9/50, G06N3/045, G06N3/063, G06N3/08, G06N3/084, G06N20/00




Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving a request from a client to process a computational graph; obtaining data representing the computational graph, the computational graph comprising a plurality of nodes and directed edges, wherein each node represents a respective operation, wherein each directed edge connects a respective first node to a respective second node that represents an operation that receives, as input, an output of an operation represented by the respective first node; identifying a plurality of available devices for performing the requested operation; partitioning the computational graph into a plurality of subgraphs, each subgraph comprising one or more nodes in the computational graph; and assigning, for each subgraph, the operations represented by the one or more nodes in the subgraph to a respective available device in the plurality of available devices for operation.[[Category:G06N3/098]][[Category:G06F9/50]][[Category:G06N3/045]][[Category:G06N3/063]][[Category:G06N3/08]][[Category:G06N3/084]][[Category:G06N20/00]][[Category:google llc]]



[[20240160976.Backtesting Quantum Device Calibration_simplified_abstract_(google llc)]]

Inventor(s): Paul Victor Klimov of Santa Barbara CA (US) for google llc

IPC Code(s): G06N10/20




Abstract: an example computer-implemented method for calibrating a qubit of a quantum device is disclosed. the example method includes obtaining a candidate calibration model for calibrating an operating characteristic of the qubit. the example method includes determining, using one or more quantum device models, a simulated quantum device performance metric associated with implementation of the candidate calibration model based on log data descriptive of observed qubit operating characteristics and associated observed quantum device performance metrics.[[Category:G06N10/20]][[Category:google llc]]



[[20240160987.QUANTUM DATA PROCESSING SYSTEM_simplified_abstract_(google llc)]]

Inventor(s): Jarrod Ryan McClean of Marina Del Rye CA (US) for google llc

IPC Code(s): G06N10/60, G06N10/40




Abstract: methods, systems, and apparatus for quantum data processing. in one aspect, a method includes storing, in a quantum memory, multiple copies of a quantum state, comprising, for each copy of the quantum state, i) probing, by an initialized quantum sensor, a target system to obtain an evolved quantum state of the quantum sensor, ii) transducing the evolved quantum state of the quantum sensor into a quantum state of a quantum buffer, iii) logically encoding the quantum state of the quantum buffer into a quantum error correcting code, and iv) moving the logically encoded quantum state of the quantum buffer into the quantum memory; loading the multiple copies of the quantum state in the quantum memory into a quantum computer; processing, by the quantum computer, the multiple copies of the quantum state to obtain a purified quantum state; and measuring the purified quantum state to determine properties of the target system.[[Category:G06N10/60]][[Category:G06N10/40]][[Category:google llc]]



[[20240161097.Transaction Authentication_simplified_abstract_(google llc)]]

Inventor(s): Ankit Aggarwal of Singapore  (SG) for google llc, Sakshi Gopal of Singapore  (SG) for google llc, John J. Geewax, JR. of Singapore  (SG) for google llc, Jia Lin Cai of Singapore  (SG) for google llc, Ishaan Malhi of Singapore  (SG) for google llc

IPC Code(s): G06Q20/38, G06Q20/40




Abstract: a method for authenticating a transaction between two entities includes receiving, by one or more processors, a request associated with the transaction between a first entity associated with a first computing device and a second entity, generating, by the one or more processors, transaction details information associated with completion of the transaction between the first entity and the second entity, encrypting, by the one or more processors, the transaction details information by digitally signing the transaction details information, and transmitting, by the one or more processors, the transaction details information encrypted by the one or more processors, to the first computing device.[[Category:G06Q20/38]][[Category:G06Q20/40]][[Category:google llc]]



[[20240161340.CALIBRATING CAMERA IN ELECTRONIC DEVICE_simplified_abstract_(google llc)]]

Inventor(s): Idris Syed Aleem of Kitchener  (CA) for google llc, Zhiheng Jia of Sunnyvale CA (US) for google llc

IPC Code(s): G06T7/80, G06V40/16




Abstract: a method performed by a server can include sending a first webpage to a first computing device, the first computing device including a camera, the first webpage including an image-capturing function and including an instruction for a user to obtain a second webpage via a second computing device, the second webpage including a calibration image file; receiving, from the first computing device, multiple captured images that were captured by the camera, the multiple calibration images including instances of a calibration image presented by a display included in the second computing device, the calibration image being a representation of the calibration image file; and based on the multiple captured images, calibrating the camera.[[Category:G06T7/80]][[Category:G06V40/16]][[Category:google llc]]



[[20240161459.OPEN-VOCABULARY OBJECT DETECTION IN IMAGES_simplified_abstract_(google llc)]]

Inventor(s): Matthias Johannes Lorenz Minderer of Zurich  (CH) for google llc, Alexey Alexeevich Gritsenko of Amsterdam  (NL) for google llc, Austin Charles Stone of San Francisco CA (US) for google llc, Dirk Weissenborn of Berlin  (DE) for google llc, Alexey Dosovitskiy of Berlin  (DE) for google llc, Neil Matthew Tinmouth Houlsby of Zürich  (CH) for google llc

IPC Code(s): G06V10/764, G06F40/40, G06V10/22, G06V10/74, G06V10/774, G06V10/776, G06V10/82




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. in one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.[[Category:G06V10/764]][[Category:G06F40/40]][[Category:G06V10/22]][[Category:G06V10/74]][[Category:G06V10/774]][[Category:G06V10/776]][[Category:G06V10/82]][[Category:google llc]]



[[20240161470.Machine-Learned Models for Implicit Object Representation_simplified_abstract_(google llc)]]

Inventor(s): Cristian Sminchisescu of Zürich  (CH) for google llc, Thiemo Andreas Alldieck of Zürich  (CH) for google llc, Hongyi Xu of Zürich  (CH) for google llc

IPC Code(s): G06V10/774, G06T7/50, G06T15/80, G06T17/20, G06V10/26, G06V10/776, G06V20/64, G06V20/70, G06V40/10




Abstract: systems and methods of the present disclosure are directed to a computer-implemented method for training a machine-learned model for implicit representation of an object. the method can include obtaining a latent code descriptive of a shape of an object comprising one or more object segments. the method can include determining spatial query points. the method can include processing the latent code and spatial query points with segment representation portions of a machine-learned implicit object representation model to obtain implicit segment representations for the object segments. the method can include determining an implicit object representation of the object and semantic data. the method can include evaluating a loss function. the method can include adjusting parameters of the machine-learned implicit object representation model based at least in part on the loss function.[[Category:G06V10/774]][[Category:G06T7/50]][[Category:G06T15/80]][[Category:G06T17/20]][[Category:G06V10/26]][[Category:G06V10/776]][[Category:G06V20/64]][[Category:G06V20/70]][[Category:G06V40/10]][[Category:google llc]]



[[20240161538.Perspective Distortion Correction on Faces_simplified_abstract_(google llc)]]

Inventor(s): Yichang Shih of Cupertino CA (US) for google llc, Chia-Kai Liang of San Jose CA (US) for google llc

IPC Code(s): G06V40/16, G06T3/18, G06T5/80, G06T17/20, G06T19/20




Abstract: apparatus and methods related to image processing are provided. a computing device can determine a first image area of an image, such as an image captured by a camera. the computing device can determine a warping mesh for the image with a first portion of the warping mesh associated with the first image area. the computing device can determine a cost function for the warping mesh by: determining first costs associated with the first portion of the warping mesh that include costs associated with face-related transformations of the first image area to correct geometric distortions, and determining second costs associated with the warping mesh that include costs of edge-related transformations for preserving straightness of edges of the image. the computing device can determine an optimized mesh based on optimizing the cost function. the computing device can modify the first image area based on the optimized mesh.[[Category:G06V40/16]][[Category:G06T3/18]][[Category:G06T5/80]][[Category:G06T17/20]][[Category:G06T19/20]][[Category:google llc]]



[[20240161542.Authentication Management Through IMU and Radar_simplified_abstract_(google llc)]]

Inventor(s): Alok Chandel of Mountain View CA (US) for google llc, Leonardo Giusti of San Francisco CA (US) for google llc, Artur Tsurkan of San Francisco CA (US) for google llc, Selim Flavio Cinek of Los Angeles CA (US) for google llc, Johan Prag of Mountain View CA (US) for google llc, Tyler Reed Kugler of Palo Alto CA (US) for google llc, Lucas Dupin Moreira Costa of Mountain View CA (US) for google llc, Vignesh Sachidanandam of Redwood City CA (US) for google llc, Brandon Barbello of Mountain View CA (US) for google llc

IPC Code(s): G06V40/16, G01S7/41, G06T7/50, H04N5/33




Abstract: this document describes techniques and systems for authentication management through imu and radar. the techniques and systems use inertial sensor data from an inertial measurement unit (imu) and/or radar data to manage authentication for a computing device. by so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for computing-device authentication.[[Category:G06V40/16]][[Category:G01S7/41]][[Category:G06T7/50]][[Category:H04N5/33]][[Category:google llc]]



[[20240161730.Parallel Tacotron Non-Autoregressive and Controllable TTS_simplified_abstract_(google llc)]]

Inventor(s): Isaac Elias of Mountain View CA (US) for google llc, Jonathan Shen of Mountain View CA (US) for google llc, Yu Zhang of Mountain View CA (US) for google llc, Ye Jia of Mountain View CA (US) for google llc, Ron J. Weiss of New York NY (US) for google llc, Yonghui Wu of Fremont CA (US) for google llc, Byungha Chun of Tokyo  (JP) for google llc

IPC Code(s): G10L13/08, G06F40/126, G06N3/044, G06N3/045, G06N3/08, G06N3/088, G10L13/047, G10L21/10




Abstract: a method for training a non-autoregressive tts model includes receiving training data that includes a reference audio signal and a corresponding input text sequence. the method also includes encoding the reference audio signal into a variational embedding that disentangles the style/prosody information from the reference audio signal and encoding the input text sequence into an encoded text sequence. the method also includes predicting a phoneme duration for each phoneme in the input text sequence and determining a phoneme duration loss based on the predicted phoneme durations and a reference phoneme duration. the method also includes generating one or more predicted mel-frequency spectrogram sequences for the input text sequence and determining a final spectrogram loss based on the predicted mel-frequency spectrogram sequences and a reference mel-frequency spectrogram sequence. the method also includes training the tts model based on the final spectrogram loss and the corresponding phoneme duration loss.[[Category:G10L13/08]][[Category:G06F40/126]][[Category:G06N3/044]][[Category:G06N3/045]][[Category:G06N3/08]][[Category:G06N3/088]][[Category:G10L13/047]][[Category:G10L21/10]][[Category:google llc]]



[[20240161732.MULTI-DIALECT AND MULTILINGUAL SPEECH RECOGNITION_simplified_abstract_(google llc)]]

Inventor(s): Zhifeng Chen of Sunnyvale CA (US) for google llc, Bo Li of Santa Clara CA (US) for google llc, Eugene Weinstein of New York NY (US) for google llc, Yonghui Wu of Fremont CA (US) for google llc, Pedro J. Moreno Mengibar of Jersey City NJ (US) for google llc, Ron J. Weiss of New York NY (US) for google llc, Khe Chai Sim of Dublin CA (US) for google llc, Tara N. Sainath of Jersey City NJ (US) for google llc, Patrick An Phu Nguyen of Palo Alto CA (US) for google llc

IPC Code(s): G10L15/00, G10L15/07, G10L15/16




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. in some implementations, audio data indicating audio characteristics of an utterance is received. input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. the speech recognition model can be one that has been trained using cluster adaptive training. output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. a transcription of the utterance generated based on the output of the speech recognition model is provided.[[Category:G10L15/00]][[Category:G10L15/07]][[Category:G10L15/16]][[Category:google llc]]



[[20240161740.Multi-Assistant Warm Words_simplified_abstract_(google llc)]]

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

IPC Code(s): G10L15/22, G10L15/08




Abstract: a method using multi-assistant warm words includes, for each digital assistant in a group of digital assistants enabled on a multi-assistant device, receiving a respective active set of warm words that each specify a respective action to perform. based on the respective active set of warm words, the method also includes executing a warm word arbitration routine to enable a final set of warm words for detection, each warm word in the final set of warm words selected from the respective active set of warm words for at least one digital assistant. while the final set of warm words are enabled for detection, the method includes receiving audio data corresponding to an utterance, detecting a warm word from the final set of warm words, and instructing the digital assistant associated with the detected warm word to perform the respective action specified by the detected warm word.[[Category:G10L15/22]][[Category:G10L15/08]][[Category:google llc]]



[[20240161741.Short-Lived Repeat Voice Commands_simplified_abstract_(google llc)]]

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

IPC Code(s): G10L15/22, G10L15/08




Abstract: a method for detecting short-lived repeat voice commands includes activating a set of one or more warm words each associated with a respective action for controlling a long-standing operation performed by a digital assistant. while the digital assistant is performing the long-standing operation, the method includes receiving audio data, and detecting, in the audio data, a warm word from the activated set of one or more warm words. in response to detecting the warm word, the method includes performing the respective action associated with the detected warm word, and activating a set of one or more repeat warm words associated with the detected warm word. the method further includes receiving additional audio data, detecting, in the additional audio data, a repeat warm word from the activated set of one or more repeat warm words, and performing the respective action associated with the detected repeat warm word.[[Category:G10L15/22]][[Category:G10L15/08]][[Category:google llc]]



[[20240161743.SELECTIVELY GENERATING EXPANDED RESPONSES THAT GUIDE CONTINUANCE OF A HUMAN-TO-COMPUTER DIALOG_simplified_abstract_(google llc)]]

Inventor(s): Michael Fink of Tel Aviv  (IL) for google llc, Vladimir Vuskovic of Zolikerberg  (CH) for google llc, Shimon Or Salant of Rechovot Center District  (IL) for google llc, Deborah Cohen of Tel Aviv  (IL) for google llc, Asaf Revach of Nordia  Center  District  (IL) for google llc, David Kogan of Natick MA (US) for google llc, Andrew Callahan of Somerville MA (US) for google llc, Richard Borovoy of Boston MA (US) for google llc, Andrew Richardson of Cambridge MA (US) for google llc, Eran Ofek of Rdhovot  (IL) for google llc, Idan Szpektor of Kfar Saba  (IL) for google llc, Jonathan Berant of Tel Aviv  (IL) for google llc, Yossi Matias of Tel Aviv  (IL) for google llc

IPC Code(s): G10L15/22, G06F40/284, G06N3/08, G10L15/06, G10L15/18, G10L15/20




Abstract: generating expanded responses that guide continuance of a human-to computer dialog that is facilitated by a client device and that is between at least one user and an automated assistant. the expanded responses are generated by the automated assistant in response to user interface input provided by the user via the client device, and are caused to be rendered to the user via the client device, as a response, by the automated assistant, to the user interface input of the user. an expanded response is generated based on at least one entity of interest determined based on the user interface input, and is generated to incorporate content related to one or more additional entities that are related to the entity of interest, but that are not explicitly referenced by the user interface input.[[Category:G10L15/22]][[Category:G06F40/284]][[Category:G06N3/08]][[Category:G10L15/06]][[Category:G10L15/18]][[Category:G10L15/20]][[Category:google llc]]



[[20240161769.Method for Detecting and Classifying Coughs or Other Non-Semantic Sounds Using Audio Feature Set Learned from Speech_simplified_abstract_(google llc)]]

Inventor(s): Jacob Garrison of Seattle WA (US) for google llc, Jacob Scott Peplinski of Chandler AZ (US) for google llc, Joel Shor of Tokyo  (JP) for google llc

IPC Code(s): G10L25/66, A61B5/00, A61B5/08, G10L15/02, G10L15/04, G10L15/06, G10L25/30, G10L25/51, G10L25/78, G16H40/67




Abstract: a method of detecting a cough in an audio stream includes a step of performing one or more pre-processing steps on the audio stream to generate an input audio sequence comprising a plurality of time-separated audio segments. an embedding is generated by a self-supervised triplet loss embedding model for each of the segments of the input audio sequence using an audio feature set, the embedding model having been trained to learn the audio feature set in a self-supervised triplet loss manner from a plurality of speech audio clips from a speech dataset. the embedding for each of the segments is provided to a model performing cough detection inference. this model generates a probability that each of the segments of the input audio sequence includes a cough episode. the method includes generating cough metrics for each of the cough episodes detected in the input audio sequence.[[Category:G10L25/66]][[Category:A61B5/00]][[Category:A61B5/08]][[Category:G10L15/02]][[Category:G10L15/04]][[Category:G10L15/06]][[Category:G10L25/30]][[Category:G10L25/51]][[Category:G10L25/78]][[Category:G16H40/67]][[Category:google llc]]



[[20240161783.GENERATING VIDEOS_simplified_abstract_(google llc)]]

Inventor(s): Nathan James Frey of Venice CA (US) for google llc, Zheng Sun of Sunnyvale CA (US) for google llc

IPC Code(s): G11B27/031, G06T7/20, G06V20/40




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating videos. in one aspect, a method comprises: receiving: (i) an input video comprising a sequence of video frames, and (ii) data indicating a target object type; processing the input video to generate tracking data that identifies and tracks visual locations of one or more instances of target objects of the target object type in the input video; generating a plurality of sub-videos based on the input video and the tracking data, including: for each sub-video, generating a respective sequence of sub-video frames that are each extracted from a respective video frame of the input video to include a respective instance of a given target object from among the identified target objects of the target object type; and generating an output video that comprises the plurality of sub-videos.[[Category:G11B27/031]][[Category:G06T7/20]][[Category:G06V20/40]][[Category:google llc]]



[[20240162050.SIGNAL DISTRIBUTION FOR A QUANTUM COMPUTING SYSTEM_simplified_abstract_(google llc)]]

Inventor(s): Evan Jeffrey of Santa Barbara CA (US) for google llc, Joshua Yousouf Mutus of Santa Barbara CA (US) for google llc

IPC Code(s): H01L21/48, G06N10/00, H01L23/498, H01L33/06




Abstract: a method of fabricating a carrier chip for distributing signals among circuit elements of a quantum computing device, includes: providing a multilayer wiring stack, the multilayer wiring stack comprising alternating layers of dielectric material and wiring; bonding a capping layer to the multilayer wiring stack, in which the capping layer includes a single crystal silicon dielectric layer; forming a via hole within the capping layer, in which the via hole extends to a first wiring layer of the multilayer wiring stack; forming an electrically conductive via within the via hole and electrically coupled to the first wiring layer; and forming a circuit element on a surface of the capping layer, in which the circuit element is directly electrically coupled to the electrically conductive via.[[Category:H01L21/48]][[Category:G06N10/00]][[Category:H01L23/498]][[Category:H01L33/06]][[Category:google llc]]



[[20240162179.PILLARS AS STOPS FOR PRECISE CHIP-TO-CHIP SEPARATION_simplified_abstract_(google llc)]]

Inventor(s): Erik Anthony Lucero of Goleta CA (US) for google llc

IPC Code(s): H01L23/00, G06N10/00, H10N60/12




Abstract: a stacked device including a first substrate that includes a quantum information processing device, a second substrate bonded to the first substrate, and multiple bump bonds and at least one pillar between the first substrate and the second substrate. each bump bond of the multiple bump bonds provides an electrical connection between the first substrate and the second substrate. at least one pillar defines a separation distance between a first surface of the first substrate and a first surface of the second substrate. a cross-sectional area of each pillar is greater than a cross-sectional area of each bump bond of the multiple bump bonds, where the cross-sectional area of each pillar and of each bump bond is defined along a plane parallel to the first surface of the first substrate or to the first surface of the second substrate.[[Category:H01L23/00]][[Category:G06N10/00]][[Category:H10N60/12]][[Category:google llc]]



[[20240162726.Switched Multi-Cell Battery System_simplified_abstract_(google llc)]]

Inventor(s): Liang Jia of Palo Alto CA (US) for google llc

IPC Code(s): H02J7/00




Abstract: this disclosure describes apparatuses and techniques for a switched multi-cell battery system for electronic devices. in some aspects, a switched multi-cell battery system may transfer, via a plurality of power control switches electrical power from a power adapter to components of the electronic device by charging battery cells in series and by discharging the battery cells in parallel or as a single battery cell. as a result, the switched multi-cell battery system may reduce or eliminate a voltage step-down conversion stage to increase a power-transfer efficiency of an electronic device. by doing so, charging times may be reduced or operating times may be increased, thereby improving users' experience with their electronic devices.[[Category:H02J7/00]][[Category:google llc]]



[[20240162742.System and Method for Transitioning to Backup Power Pooling_simplified_abstract_(google llc)]]

Inventor(s): Sangsun Kim of San Jose CA (US) for google llc, Krishnanjan Gubba Ravikumar of Pullman WA (US) for google llc

IPC Code(s): H02J9/06, H02J3/00, H02J3/32, H02J3/38




Abstract: a system and method for power pooling, the system including a shared power line, a plurality of backup power supplies connected to the shared power line through respective transformers and one or more controllers configured to, for each respective backup power supply, after passage of a different respective predetermined amount of time, determine whether a transformer connected to the backup power supply is energized. in response to the transformer being energized, the controllers synchronize the backup power supply with the transformer and then set a switch positioned between the backup power supply and the transformer to a fully closed state. in response to the transformer not being energized, the controllers transition the switch from a fully open state to the fully closed state according to an inrush current limiting scheme.[[Category:H02J9/06]][[Category:H02J3/00]][[Category:H02J3/32]][[Category:H02J3/38]][[Category:google llc]]



[[20240163193.Network Anomaly Detection_simplified_abstract_(google llc)]]

Inventor(s): Mikhal Shemer of Tel Aviv  (IL) for google llc, Roee Engelberg of Tel Aviv  (IL) for google llc, Yonit Tova Halperin Worzel of Tel Aviv  (IL) for google llc, Alex Gontmakher of Holon  (IL) for google llc, Alexander Goldshtein of Tel Aviv  (IL) for google llc, Gal Elidan of Modiin  (IL) for google llc, Benjamin Dov Kessler of Jerusalem  (IL) for google llc

IPC Code(s): H04L43/0817, G06F9/455, G06F18/214, H04L41/0604, H04L41/0631, H04L43/065




Abstract: a cloud network is a complex environment in which hundreds and thousands of users or entities can each host, create, modify, and develop multiple virtual machines. each virtual machine can have complex behavior unknown to the provider or maintainer of the cloud. technologies disclosed include methods, systems, and apparatuses to monitor the complex environment to detect network anomalies using machine learning techniques. in addition, techniques to modify and adapt to user feedback are provided allowing the developed models to be tuned for specific use cases, virtual machine types, and users.[[Category:H04L43/0817]][[Category:G06F9/455]][[Category:G06F18/214]][[Category:H04L41/0604]][[Category:H04L41/0631]][[Category:H04L43/065]][[Category:google llc]]



[[20240163259.PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION_simplified_abstract_(google llc)]]

Inventor(s): Wei HUANG of Kirkland WA (US) for google llc, Michael William DAUB of Woodinville WA (US) for google llc, Robert F. Day of Bellevue WA (US) for google llc, Arthur ASUNCION of Bothell WA (US) for google llc

IPC Code(s): H04L9/40, H04L67/50




Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium for displaying digital components on client devices based on predicted user attributes of users are described. in one aspect, a method includes updating, at a client device of a user, a list of user group identifiers for the user to include a particular user group identifier that identifies a particular user group. a determination is made, for each user attribute of multiple user attributes, a score based on a quantity of user groups identified in the list of group identifiers for the user that include, as a membership attribute, the user attribute. a digital component request including data representing the list of user-group identifiers is sent to a content distribution system. digital component data identifying a set of digital components selected based on the data of the digital component request is received.[[Category:H04L9/40]][[Category:H04L67/50]][[Category:google llc]]



[[20240163322.METHODS, SYSTEMS, AND MEDIA FOR DELIVERING MANIFESTLESS STREAMING MEDIA CONTENT_simplified_abstract_(google llc)]]

Inventor(s): Tristan Schmelcher of Sammamish WA (US) for google llc, William Cyr of Boston MA (US) for google llc, Thomas DeWeese of Boxborough MA (US) for google llc, Nils Krahnstoever of Brookline MA (US) for google llc, Matthew Carson of San Francisco CA (US) for google llc, Pawel Jurczyk of Newton MA (US) for google llc, Thomas Dinger of Waltham MA (US) for google llc, Jeffrey Calow of Arlington MA (US) for google llc

IPC Code(s): H04L65/613, H04L65/612, H04N21/2187, H04N21/84, H04N21/858




Abstract: methods, systems, and media for delivering manifestless streaming media content are provided. in some embodiments, the method comprises: receiving, from a user device, a request for a url corresponding to a format of a live stream that is provided in a plurality of formats, wherein the live stream comprises a plurality of segments for each of the plurality of formats; resolving the request to a specific segment of the live stream based on the url, wherein the resolving comprises: identifying the format of the live stream associated with the request from the plurality of formats based on the url; and identifying a segment of the plurality of segments corresponding to the identified format to the user device in a response to the request.[[Category:H04L65/613]][[Category:H04L65/612]][[Category:H04N21/2187]][[Category:H04N21/84]][[Category:H04N21/858]][[Category:google llc]]



[[20240163341.PRIVACY PRESERVING CENTROID MODELS USING SECURE MULTI-PARTY COMPUTATION_simplified_abstract_(google llc)]]

Inventor(s): Gang Wang of Frederick MD (US) for google llc, Marcel M. Moti Yung of New York NY (US) for google llc

IPC Code(s): H04L67/306, H04L9/08




Abstract: this disclosure relates to a privacy preserving machine learning platform. in one aspect, a method includes receiving, from a client device and by a computing system of multiple multi-party computation (mpc) systems, a first request for user group identifiers that identify user groups to which to add a user. the first request includes a model identifier for a centroid model, first user profile data for a user profile of the user, and a threshold distance. for each user group in a set of user groups corresponding to the model identifier, a centroid for the user group that is determined using a centroid model corresponding to the model identifier is identified. the computing system determines a user group result based at least on the first user profile data, the centroids, and the threshold distance. the user group result is indicative of user group(s) to which to add the user.[[Category:H04L67/306]][[Category:H04L9/08]][[Category:google llc]]



[[20240163499.PERSISTENT MEDIA PLAYER_simplified_abstract_(google llc)]]

Inventor(s): Justin Lewis of Marina del Rey CA (US) for google llc, Gavin James of Los Angeles CA (US) for google llc

IPC Code(s): H04N21/431, H04N21/262, H04N21/482




Abstract: a persistent media player is disclosed. a method for providing the persistent media player includes displaying, by an electronic device, a first portion of a scrollable document in a user interface (ui) of an application executed on the electronic device. the first portion includes a media player that is to present a first media item. the method further includes receiving an input to scroll to a second portion of the scrollable document. the method also includes displaying the second portion of the scrollable document, where the first portion is no longer visible and where the media player continues to be visible.[[Category:H04N21/431]][[Category:H04N21/262]][[Category:H04N21/482]][[Category:google llc]]



[[20240163523.OPTIMIZING TIMING OF DISPLAY OF A VIDEO OVERLAY_simplified_abstract_(google llc)]]

Inventor(s): Jakob Foerster of Zürich  (CH) for google llc, Dhruv Bakshi of Zurich  (CH) for google llc

IPC Code(s): H04N21/488, G06Q30/00, G06Q30/0201, G06Q30/0241, H04N21/442, H04N21/81




Abstract: the timing for displaying an overlay a video is optimized using a system that includes an engagement component that receives information regarding frames of a video at which respective users of a plurality of users stop engaging with the video and an analysis component that calculates user engagement scores for the frames based on the information, wherein the user engagement scores reflect a percentage of the plurality of users that stop engaging with the video at the respective frames, and wherein the higher the percentage the lower the user engagement score. the system further includes an identification component that identifies a subset of the frames associated with relatively lower user engagement scores in comparison to other frames of the video and an overlay component that configures an overlay for displaying over the video near at least one of the frames included in the subset.[[Category:H04N21/488]][[Category:G06Q30/00]][[Category:G06Q30/0201]][[Category:G06Q30/0241]][[Category:H04N21/442]][[Category:H04N21/81]][[Category:google llc]]



[[20240163602.PANEL AUDIO LOUDSPEAKERS INCLUDING MECHANICALLY GROUNDED MAGNETIC CIRCUIT_simplified_abstract_(google llc)]]

Inventor(s): Andrew Phillis of Campbell CA (US) for google llc, Timothy A. Gladwin of Mountain View CA (US) for google llc, Rajiv Bernard Gomes of San Jose CA (US) for google llc, Anthony King of San Jose CA (US) for google llc, Jason David Walker of Mountain View CA (US) for google llc, Neil John Harris of Los Altos CA (US) for google llc

IPC Code(s): H04R1/28, H04R1/02, H04R7/04, H04R9/02, H04R9/04, H04R9/06




Abstract: a device includes: a panel and an electromagnetic actuator mechanically coupled to a rear side of the panel to form a panel audio loudspeaker, the electromagnetic actuator comprising a coil attached to the rear side of the panel and a magnet suspended with respect to the coil via one or more spring elements, the coil defining an axis, wherein during operation of the device an electric current through the coil varies a relative displacement of the magnet with respect to the coil along the axis. the device includes: a chassis supporting the panel, the chassis comprising a housing for the device, the housing comprising a rear panel on an opposite side of the device from the panel; and a grounding assembly positioned along the axis between the magnet and the rear panel of the device, wherein the grounding assembly mechanically grounds the magnet to the chassis.[[Category:H04R1/28]][[Category:H04R1/02]][[Category:H04R7/04]][[Category:H04R9/02]][[Category:H04R9/04]][[Category:H04R9/06]][[Category:google llc]]



[[Google LLC patent applications on May 16th, 2024]]



[[Category:Google LLC]] [[Category:G10L15/22]] [[Category:G06N3/08]] [[Category:G06N3/045]] [[Category:G06N20/00]] [[Category:G06V10/774]]