Google LLC patent applications on July 4th, 2024
Patent Applications by Google LLC on July 4th, 2024
Google LLC: 55 patent applications
Google LLC has applied for patents in the areas of G10L15/22 (5), G06F3/16 (4), G06F40/35 (3), G06N3/045 (3), G10L15/06 (3) G10L15/22 (3), G06N3/08 (2), G06F40/35 (2), H04L65/1069 (2), A47C7/727 (1)
With keywords such as: data, device, user, based, computing, content, methods, determining, output, and include in patent application abstracts.
Patent Applications by Google LLC
20240215730. ACOUSTIC CHAIR COVE_simplified_abstract_(google llc)
Inventor(s): Christine Jean Wu of San Francisco CA (US) for google llc, Shokofeh Darbari of Palo Alto CA (US) for google llc, Shane Anton Myrbeck of Los Angeles CA (US) for google llc, Caitlyn Emily Riggs of San Francisco CA (US) for google llc, Jack Godfrey Wood of San Francisco CA (US) for google llc, Andy Furner of London (GB) for google llc, Harc Lee of London (GB) for google llc
IPC Code(s): A47C7/72
CPC Code(s): A47C7/727
Abstract: an acoustic chair cove includes a lower cove mountable on a chair such that a first wing of the lower cove is positioned at a first side of the chair, a second wing of the lower cove is positioned at a second side of the chair, and a top portion of the lower cove is positioned at a top portion of a back of the chair. an upper cove is mounted to the lower cove such that the upper cove is selectively movable relative to the lower cove between a retracted configuration and an extended configuration.
20240217091. Shared Dense Network with Robot Task-Specific Heads_simplified_abstract_(google llc)
Inventor(s): Michael Quinlan of Sunnyvale CA (US) for google llc, Sean Kirmani of San Francisco CA (US) for google llc
IPC Code(s): B25J5/00, G06F18/214, G06V10/40, G06V10/44, G06V10/764, G06V10/776, G06V10/82, G06V10/94, G06V20/10, G06V20/64
CPC Code(s): B25J5/007
Abstract: a method includes receiving image data representing an environment of a robotic device from a camera on the robotic device. the method further includes applying a trained dense network to the image data to generate a set of feature values, where the trained dense network has been trained to accomplish a first robot vision task. the method additionally includes applying a trained task-specific head to the set of feature values to generate a task-specific output to accomplish a second robot vision task, where the trained task-specific head has been trained to accomplish the second robot vision task based on previously generated feature values from the trained dense network, where the second robot vision task is different from the first robot vision task. the method also includes controlling the robotic device to operate in the environment based on the task-specific output generated to accomplish the second robot vision task.
Inventor(s): Dongeek Shin of Mountain View CA (US) for google llc
IPC Code(s): B60W60/00, B60W30/165
CPC Code(s): B60W60/0025
Abstract: to automatically follow a host vehicle to a destination location, a client device in a vehicle identifies a host vehicle to follow to a destination location, transmits a communication signal to the identified host vehicle, and receives a response signal from the identified host vehicle. the client device determines a position of the host vehicle relative to the vehicle based on a round trip time of the communication signal and the response signal, and adjusts control of the vehicle in accordance with the position of the host vehicle relative to the vehicle.
Inventor(s): Effie Goenawan of San Francisco CA (US) for google llc, Abraham Lee of Belmont CA (US) for google llc, Arvind Sivaram Sharma of Mountian View CA (US) for google llc, Austin Chang of San Francisco CA (US) for google llc
IPC Code(s): G01C21/36, G06F3/14, G06F3/16, G06F21/32, G10L15/08
CPC Code(s): G01C21/3629
Abstract: implementations set forth herein relate to interactions, between vehicle computing devices and mobile computing devices, that reduce duplicative processes from occurring at either device. reduction of such processes can be performed, in some instances, via communications between a vehicle computing device and a mobile computing device in order to determine, for example, how to uniquely render content at an interface of each respective computing device while the user is driving the vehicle. these communications can occur before a user has entered a vehicle, while the user is in the vehicle, and/or after a user has left the vehicle. for instance, just before a user enters a vehicle, a vehicle computing device can be primed for certain automated assistant interactions between the user and their mobile computing device. alternatively, or additionally, the user can authorize the vehicle computing device to perform certain processes immediately after leaving the vehicle.
20240219559. MULTIPATH AUTOBOUNCE LOCATION DETERMINATION_simplified_abstract_(google llc)
Inventor(s): Dongeek Shin of Santa Clara CA (US) for google llc
IPC Code(s): G01S13/87, G01S13/76
CPC Code(s): G01S13/878
Abstract: a computing device is described that includes one or more processors, a wireless transceiver that broadcasts a message over a wireless signal to locate a target tag, and a locator application. the locator application is operable by the one or more processors to receive, in response to the broadcast message, a plurality of intermediate responses from one or more intermediate tags, determine a first-hop direction and a first-hop distance to at least one first-hop intermediate tag based on the plurality of intermediate responses, and determine a target tag distance and a target tag direction from the computing device to the target tag based on each first-hop direction and the intermediate responses from each intermediate tag, wherein at least one of the plurality of intermediate responses from the one or more intermediate tags includes range data associated with a target-hop distance from the intermediate tag to the target tag.
20240219670. High Density Breakout Panels With Front Access_simplified_abstract_(google llc)
Inventor(s): Charles Poe of Palo Alto CA (US) for google llc, Mathew Berg of Charleston SC (US) for google llc, John David Roselle of Pryor OK (US) for google llc
IPC Code(s): G02B6/44
CPC Code(s): G02B6/44528
Abstract: a fiber optic cable management system includes a patch panel assembly that further includes multiple fiber optic trays with one or more fiber optic module assemblies coupled to each tray. the fiber optic module assemblies may include two different types of adapter modules. in one example, a first type is a lucent connector (“lc”) adapter module, and the second type is a multi-fiber push-on (“mpo”) adapter module. the mpo adapter module and the lc adapter module are arranged adjacent one another. the lc adapter modules may further include a plurality of adapter ports and the mpo adapter module may include a single adapter port. the arrangement of the lc adapter module and mpo adapter module allows for connection with a breakout cable assembly with an mpo connector and a plurality of lc connectors. in some examples, the lc adapter module may be a dual polarity adapter module
Inventor(s): Ozan Cakmakci of San Mateo CA (US) for google llc, Kirill Afanasev of Waterloo (CA) for google llc
IPC Code(s): G02B27/01
CPC Code(s): G02B27/0172
Abstract: systems, devices, and techniques provide an increased size of an eyebox presented by a wearable display device by utilizing multiple outcouplers, each including a set of multiple holographic mirrors. light from a micro-display is polarized via a controllable polarizer that switches between s-type and p-type polarization, collimated, passed to a tir waveguide, and directed via multiple outcouplers to an eye of a user. the outcouplers may include one or more angular bandwidth holograms that reflect light that is incident on the hologram at a specific angle or a specific range of angles.
20240220202. Multi-Modal Systolic Array For Matrix Multiplication_simplified_abstract_(google llc)
Inventor(s): Matthew Leever Hedlund of Sun Prairie WI (US) for google llc, Christopher Aaron Clark of Madison WI (US) for google llc, Andrew Everett Phelps of Middleton WI (US) for google llc, Thomas James Norrie of San Jose CA (US) for google llc, Norman Paul Jouppi of Palo Alto CA (US) for google llc, Sushma Honnavara-Prasad of Los Gatos CA (US) for google llc, Vinayak Anand Gokhale of Austin TX (US) for google llc, Pareesa Ameneh Golnari of Bellevue WA (US) for google llc
IPC Code(s): G06F7/544, G06F7/485, G06F7/487, G06F15/80
CPC Code(s): G06F7/5443
Abstract: a system and method for matrix multiplication using a systolic array configurable between multiple modes of operation. a systolic processor may receive a data type indicator for the matrix multiplication. for a first data type, the systolic processor may load the right-hand side data from the right-hand matrix register into the data processing cells of the systolic array between row 0 and row m−1, and pass the respective row of the left-hand side data through a corresponding row of the systolic array between rows 0 and m−1. for a second data type, the systolic processor may split each element of the left-hand side data and the right-hand side data into respective first and second element halves, and move each element half through a corresponding row of the systolic array between rows 0 and 2m−1.
20240220364. Data Reconstruction in Distributed Storage Systems_simplified_abstract_(google llc)
Inventor(s): Lidor Carmi of New York NY (US) for google llc, Christian Eric Schrock of Cold Spring Harbor NY (US) for google llc, Steven Robert Schirripa of Hazlet NJ (US) for google llc
IPC Code(s): G06F11/14, G06F11/07
CPC Code(s): G06F11/1402
Abstract: a method of operating a distributed storage system, the method includes identifying missing chunks of a file. the file is divided into stripes that include data chunks and non-data chunks. the method also includes identifying non-missing chunks available for reconstructing the missing chunks and reconstructing missing data chunks before reconstructing missing non-data chunks using the available non-missing chunks.
20240220527. CLASSIFYING DATA OBJECTS_simplified_abstract_(google llc)
Inventor(s): Gregory Sean Corrado of San Francisco CA (US) for google llc, Tomas Mikolov of Jersey City NJ (US) for google llc, Samuel Bengio of Los Altos CA (US) for google llc, Yoram Singer of Palo Alto CA (US) for google llc, Jonathon Shlens of San Francisco CA (US) for google llc, Andrea L. Frome of Oakland CA (US) for google llc, Jeffrey Adgate Dean of Palo Alto CA (US) for google llc, Mohammad Norouzi of Richmond Hill (CA) for google llc
IPC Code(s): G06F16/35, G06F16/50
CPC Code(s): G06F16/35
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. one of the methods includes obtaining data that associates each term in a vocabulary of terms with a respective high-dimensional representation of the term; obtaining classification data for a data object, wherein the classification data includes a respective score for each of a plurality of categories, and wherein each of the categories is associated with a respective category label; computing an aggregate high-dimensional representation for the data object from high-dimensional representations for the category labels associated with the categories and the respective scores; identifying a first term in the vocabulary of terms having a high-dimensional representation that is closest to the aggregate high-dimensional representation; and selecting the first term as a category label for the data object.
Inventor(s): Dhruv Bakshi of Zurich (CH) for google llc, Jakob Nicolaus Foerster of Zurich (CH) for google llc
IPC Code(s): G06F16/435, G06F16/951, G06F16/9535, G06F16/9538
CPC Code(s): G06F16/435
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating suggested search queries. one method includes receiving, during a search session, a request for a suggested search query; in response to receiving the request for the suggested search query, identifying an entity that is associated with an item of media content; generating a suggested search query based on the identified entity; and providing data that causes the generated suggested search query to be presented in a user interface.
20240220538. STORING SEMI-STRUCTURED DATA_simplified_abstract_(google llc)
Inventor(s): Martin Probst of Munich (DE) for google llc
IPC Code(s): G06F16/84, G06F16/21, G06F16/83, G06F16/835, G06F16/33
CPC Code(s): G06F16/86
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing semi-structured data. one of the methods includes maintaining a plurality of schemas; receiving a first semi-structured data item; determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas; and in response to determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas: generating a new schema, encoding the first semi-structured data item in the first data format to generate the first new encoded data item in accordance with the new schema, storing the first new encoded data item in the data item repository, and associating the first new encoded data item with the new schema.
20240220654. SECURE ATTRIBUTION USING ATTESTATION TOKENS_simplified_abstract_(google llc)
Inventor(s): Gang WANG of Mountain View CA (US) for google llc, Marcel M. Moti YUNG of Mountain View CA (US) for google llc, Alex Daniel JACOBSON of Mountain View CA (US) for google llc
IPC Code(s): G06F21/62
CPC Code(s): G06F21/6254
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for securely attributing a content platform while maintain user data privacy are described. in one aspect, a method includes receiving, by a content platform and from a first application executing on a client device, a request for digital components. the request includes a first anonymous token that includes a set of content. the content platform transmits, to the first application, a response including data for a digital component that includes content related to a second application and a hash value of the first anonymous token. the content platform receives, from the first application, a display notification indicating the display of the digital component via the application, the display notification including a second anonymous token and the hash value of the first anonymous token.
Inventor(s): Emily Cahill of Brooklyn NY (US) for google llc, Shamil Parbhoo of Brooklyn NY (US) for google llc, Lloyd Mckenzie of Denver CO (US) for google llc, John Gabriel D’Angelo of New York NY (US) for google llc, Jeffery Hoehl of New York NY (US) for google llc, Gregory George Galante of Little Silver NJ (US) for google llc, Behnoosh Hariri of New York NY (US) for google llc, Joy Xi of Lakewood CO (US) for google llc
IPC Code(s): G06F40/166, G06F16/176, G06F40/194
CPC Code(s): G06F40/166
Abstract: an electronic document associated with users of a collaborative document platform is identified. the electronic document is associated with a data structure including entries that each correspond to an approval request for a respective user to approve at least a portion of content of the electronic document. at least a portion of the data structure is embedded within the content of the electronic document for presentation to a first user. a first user updating a first entry of at least a portion of the data structure is detected. the update to the first entry corresponds to a first approval request for a second user to approve one or more portions of the content of the electronic document. the data structure is updated to include data of the first entry in accordance with the update to the first entry by the first user.
20240220732. Description-driven Task-oriented Dialogue Modeling_simplified_abstract_(google llc)
Inventor(s): Raghav Gupta of Mountain View CA (US) for google llc, Yuan Cao of Mountain View CA (US) for google llc, Abhinav Kumar Rastogi of Mountain View CA (US) for google llc, Harrison J. Lee of Seattle WA (US) for google llc, Jeffrey Liangjie Zhao of Mountain View CA (US) for google llc
IPC Code(s): G06F40/35, G06F16/36
CPC Code(s): G06F40/35
Abstract: example methods include determining an input schema representation for a task. the schema representation comprises natural language descriptions of slot and intent descriptions, wherein respective indices are associated with each of the slot descriptions and each of the intent descriptions. the methods include determining a contextual representation comprising a concatenation of a history of dialog sequences exchanged between a user and a service agent, wherein the dialog sequences describe a context for the task. the methods include training, a sequence-to-sequence language model and based on a concatenation of the input schema representation and the contextual representation, to predict a sequence of dialog states for an input task, wherein the sequence of dialog states comprises an assignment of values to slots for which the user has indicated a preference in dialog sequences corresponding to the input task. the methods include providing the trained sequence-to-sequence language model.
Inventor(s): Noam Shazeer of Palo Alto CA (US) for google llc, Daniel De Freitas Adiwardana of Mountain View CA (US) for google llc
IPC Code(s): G06F40/35, G06F40/20, G06F40/284, G10L13/02
CPC Code(s): G06F40/35
Abstract: the present disclosure is directed to systems and methods that include and/or leverage one or more machine-learned language models that generate intermediate textual analysis (e.g., including usage of structural tools such as apis) in service of contextual text generation. for example, a computing system can obtain a contextual text string that includes one or more contextual text tokens. the computing system can process the contextual text string with the machine-learned language model to generate one or more intermediate text strings that include one or more intermediate text tokens. the computing system can process the one or more intermediate text strings with the machine-learned language model to generate an output text string comprising one or more output text tokens. the one or more intermediate text strings can include textual analysis of the contextual text string that supports the output text string.
20240220735. GENERATIVE SUMMARIES FOR SEARCH RESULTS_simplified_abstract_(google llc)
Inventor(s): Matthew K. Gray of Reading MA (US) for google llc, John Blitzer of Mountain View CA (US) for google llc, Corinn Herrick of Mountain View CA (US) for google llc, Srinivasan Venkatachary of Sunnyvale CA (US) for google llc, Jayant Madhavan of San Francisco CA (US) for google llc, Sam Oates of Cambridge MA (US) for google llc, Phiroze Parakh of San Jose CA (US) for google llc, Aditya Shah of Mountain View CA (US) for google llc, Mahsan Rofouei of Menlo Park CA (US) for google llc, Ibrahim Badr of Zurich (CH) for google llc
IPC Code(s): G06F40/40, G06F16/332
CPC Code(s): G06F40/40
Abstract: at least selectively utilizing a large language model (llm) in generating a natural language (nl) based summary to be rendered in response to a query. in some implementations, in generating the nl based summary additional content is processed using the llm. the additional content is in addition to query content of the query itself and, in generating the nl based summary, can be processed using the llm and along with the query content—or even independent of the query content. processing the additional content can, for example, mitigate occurrences of the nl based summary including inaccuracies and/or can mitigate occurrences of the nl based summary being over-specified and/or under-specified.
Inventor(s): Michael Greenberg of Mountain View CA (US) for google llc, Bertrand Damiba of Mountain View CA (US) for google llc, Olivia Grace of Mountain View CA (US) for google llc, Fei Wu of Mountain View CA (US) for google llc, Shane Brennan of Mountain View CA (US) for google llc
IPC Code(s): G06F40/58, G06F40/51, G10L15/00, G10L15/22
CPC Code(s): G06F40/58
Abstract: the systems and methods described herein can generate a voice-based interface to increase the accuracy of translations. the voice-based interface can result in fewer input audio signals being transmitted between devices of a network. reducing the number of redundant translation requests that are sent between the devices of a network can save bandwidth and other computational resources by processing fewer input audio signals.
Inventor(s): Dan Zhang of San Bruno CA (US) for google llc, Safeen Huda of San Jose CA (US) for google llc, Azalia Mirhoseini of Mountain View CA (US) for google llc, Anna Darling Goldie of San Francisco CA (US) for google llc, Ebrahim Songhori of San Jose CA (US) for google llc
IPC Code(s): G06N3/04
CPC Code(s): G06N3/04
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining a hardware datapath for a hardware accelerator computer chip.
Inventor(s): Andreas Georg Nowatzyk of San Jose CA (US) for google llc, Olivier Temam of Antony (FR) for google llc
IPC Code(s): G06N3/045, G06F11/14, G06F11/20, G06N3/063, H02J50/10, H04L12/42, H04L45/02, H04L45/28
CPC Code(s): G06N3/045
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. in one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. the three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. the three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.
Inventor(s): Noam M. Shazeer of Palo Alto CA (US) for google llc, Lukasz Mieczyslaw Kaiser of San Francisco CA (US) for google llc, Etienne Pot of Palo Alto CA (US) for google llc, Mohammad Saleh of Santa Clara CA (US) for google llc, Ben David Goodrich of San Francisco CA (US) for google llc, Peter J. Liu of Santa Clara CA (US) for google llc, Ryan Sepassi of Beverly Hills CA (US) for google llc
IPC Code(s): G06N3/08, G06N3/045
CPC Code(s): G06N3/08
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. one of the methods includes, at each of a plurality of generation time steps: generating a combined sequence for the generation time step that includes the input sequence followed by the output tokens that have already been generated as of the generation time step; processing the combined sequence using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens; and selecting, using the time step output, an output token from the set of possible output tokens as the next output token in the output sequence.
20240220799. CONTROLLING AGENTS USING SCENE MEMORY DATA_simplified_abstract_(google llc)
Inventor(s): Kuan Fang of Stanford CA (US) for google llc, Alexander Toshkov Toshev of San Francisco CA (US) for google llc
IPC Code(s): G06N3/08, G06N3/045
CPC Code(s): G06N3/08
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling an agent. one of the methods includes receiving a current observation characterizing a current state of the environment as of the time step; generating an embedding of the current observation; processing scene memory data comprising embeddings of prior observations received at prior time steps using an encoder neural network, wherein the encoder neural network is configured to apply an encoder self-attention mechanism to the scene memory data to generate an encoded representation of the scene memory data; processing the encoded representation of the scene memory data and the embedding of the current observation using a decoder neural network to generate an action selection output; and causing the agent to perform the selected action.
20240220836. Measuring Quantum Gate Fidelity Relative to a Unitary_simplified_abstract_(google llc)
Inventor(s): Dripto Mazumdar Debroy of Los Angeles CA (US) for google llc, Vadim Smelyanskiy of Mountain View CA (US) for google llc, Wojciech Jerzy Mruczkiewicz of Zürich (CH) for google llc, Zhang Jiang of El Segundo CA (US) for google llc, Élie Genois of Sherbrooke (CA) for google llc, Jonathan Arthur Gross of Venice CA (US) for google llc
IPC Code(s): G06N10/20, G06N10/40, G06N10/70
CPC Code(s): G06N10/20
Abstract: systems and methods for quantum computing devices are provided. in one example, a method may include preparing one or more qubits in a selected initial state of a set of initial states. the method may include implementing a first quantum circuit for n repetitions on the one or more qubits, the first quantum circuit comprising one or more quantum gates. the method may include implementing a second quantum circuit to map a state of the one or more qubits towards a target state, the second quantum circuit based on a unitary associated with the first quantum circuit. the method may include performing a measurement of the one or more qubits. the method may include determining a fidelity between the first quantum circuit and the unitary based at least in part on the measurement of the one or more qubits.
Inventor(s): Deniz Oktay of Mountain View CA (US) for google llc, Saurabh Singh of Mountain View CA (US) for google llc, Johannes Balle of San Francisco CA (US) for google llc, Abhinav Shrivastava of Silver Springs MD (US) for google llc
IPC Code(s): G06N20/00, G06N3/08
CPC Code(s): G06N20/00
Abstract: example aspects of the present disclosure are directed to systems and methods that learn a compressed representation of a machine-learned model (e.g., neural network) via representation of the model parameters within a reparameterization space during training of the model. in particular, the present disclosure describes an end-to-end model weight compression approach that employs a latent-variable data compression method. the model parameters (e.g., weights and biases) are represented in a “latent” or “reparameterization” space, amounting to a reparameterization. in some implementations, this space can be equipped with a learned probability model, which is used first to impose an entropy penalty on the parameter representation during training, and second to compress the representation using arithmetic coding after training. the proposed approach can thus maximize accuracy and model compressibility jointly, in an end-to-end fashion, with the rate-error trade-off specified by a hyperparameter.
20240220867. INCORPORATION OF DECISION TREES IN A NEURAL NETWORK_simplified_abstract_(google llc)
Inventor(s): Claudionor Jose Nunes Coelho, Jr. of Redwood City CA (US) for google llc, Aki Oskari Kuusela of Palo Alto CA (US) for google llc, Satrajit Chatterjee of Palo Alto CA (US) for google llc, Piotr Zielinski of Cambridge (GB) for google llc, Hao Zhuang of San Jose CA (US) for google llc
IPC Code(s): G06N20/20
CPC Code(s): G06N20/20
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for scheduling operations represented on a computation graph. one of the methods comprises receiving data representing a neural network comprising a plurality of layers arranged in a sequence; selecting one or more groups of layers each comprising one or more layers adjacent to each other in the sequence; generating a new machine learning model, comprising: for each group of layers, a respective decision tree that replaces the group of layers, wherein the respective decision tree receives as input a quantized version of the inputs to a respective first layer in the group and generates as output a quantized version of the outputs of a respective last layer in the group, wherein a tree depth of the respective decision tree is based at least in part on a number of layers of the group.
20240220961. Direct Settlement of Hands-Free Transactions_simplified_abstract_(google llc)
Inventor(s): Steven Dieter of Superior CO (US) for google llc, Pramod Adiddam of Sunnyvale CA (US) for google llc, Amit Litsur of Portola Valley CA (US) for google llc, Yangui Tao of Cupertino CA (US) for google llc, Denise Ho of Los Altos CA (US) for google llc, Varouj Chitilian of Hillsborough CA (US) for google llc
IPC Code(s): G06Q20/32, G06Q20/20, G06Q20/40
CPC Code(s): G06Q20/3226
Abstract: a hands-free transaction is processed by utilizing an account management system to authorize a transaction and to provide payment account information to a payment processing system while allowing the transaction settlement to occur between the payment processing system and the merchant. after the account of the user is verified, a pos device generates a payment authorization request based on a user verification and other transaction information. the pos device transmits the payment authorization request to the account management system, and the account management system identifies the user payment data. the account management system receives an authorization from the payment processing system and transmits the payment authorization to the merchant. the merchant salesperson completes the transaction with the user by providing the product or service being purchased. the payment processing system and the merchant system then settle the transaction without involvement of account management system.
20240221007. SCALABLE MATRIX FACTORIZATION IN A DATABASE_simplified_abstract_(google llc)
Inventor(s): Amir Hormati of Mountain View CA (US) for google llc, Lisa Yin of Redmond WA (US) for google llc, Umar Ali Syed of Edison NJ (US) for google llc, Mingge Deng of Kirkland WA (US) for google llc
IPC Code(s): G06Q30/0201, G06F16/22, G06F16/2453, G06F17/16, G06F18/214, G06N5/04
CPC Code(s): G06Q30/0201
Abstract: a method includes obtaining a query to create a matrix factorization machine learning model based on a set of training data and determining a model vector and a data vector based on the set of training data. the method also includes determining a dot product between the model vector and the data vector, determining matrices based on the dot product, and generating item vectors using a linear solver based on the matrices. the method also includes generating the matrix factorization machine learning model based on the item vectors and executing the matrix factorization machine learning model.
20240221030. PREFERENTIAL THIRD-PARTY CONTENT MANAGEMENT_simplified_abstract_(google llc)
Inventor(s): Prabhat Sharma of Mountain View CA (US) for google llc
IPC Code(s): G06Q30/0251, G06Q30/0241
CPC Code(s): G06Q30/0256
Abstract: to manage display of preferential third-party content a method includes receiving, from a first user device, one or more preferential signals obtained by the first user device via a content preference interface, wherein the preferential signals include indications of: (i) a preferential content description, (ii) an expiration time, (iii) a time of day window, and (iv) a preferential user device; receiving, by from the preferential user device, prior to the expiration time and during the time of day window, a query including a query content description identifying, (i) the preferential third-party content based on the preferential content description, and (ii) query third-party content based on the query content description; and causing the preferential user device to display, prior to the expiration time and during the time of day window, both the preferential third-party content and the query third-party content.
Inventor(s): Noritsugu Kanazawa of Campbell CA (US) for google llc
IPC Code(s): G06V10/778, G06V10/771
CPC Code(s): G06V10/7788
Abstract: a method includes obtaining an input matrix and determining a domain index matrix that includes, for each respective input value of the input matrix, a corresponding domain index value that indicates a corresponding training data distribution of a plurality of training data distributions. the method also includes providing the input matrix and the domain index matrix to a machine learning model that has been trained using the plurality of training data distributions, where each respective training data distribution is associated with a different attribute. the method further includes generating, by the machine learning model and based on the input and the domain index matrices, an output matrix that includes, for each respective input value, a corresponding output value generated based on (i) the respective input value and (ii) the corresponding domain index value such that the corresponding output value exhibits the attribute of the corresponding training data distribution.
Inventor(s): Octavio Ponce Madrigal of Mountain View CA (US) for google llc, Patrick M. Amihood of Palo Alto CA (US) for google llc
IPC Code(s): G06V40/40, G06F21/32, G06V40/16
CPC Code(s): G06V40/40
Abstract: techniques and apparatuses are described that implement pattern recognition for face-authentication anti-spoofing. in particular, a face-authentication system distinguishes between a real human face and a presentation attack that uses a display to present a virtual human face. operational settings of a camera system of the face-authentication system are tailored to enable detection of a pattern associated with an operation of the display. a spoofing detector of the face-authentication system analyzes one or more images captured by the camera system and determines whether or not the pattern is present within the image(s). if the pattern is present, the face-authentication system does not provide face authentication. alternatively, if the pattern is not present, the face-authentication system can provide face authentication if facial recognition is successful. in this way, the face-authentication system can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.
Inventor(s): Chien-Hui Wen of Cupertino CA (US) for google llc, Hsin-Yu Chen of Taoyuan City 330 (TW) for google llc
IPC Code(s): G09G3/20, G06V40/12
CPC Code(s): G09G3/2007
Abstract: an example method includes determining, for a device having a display component configured to operate at multiple brightness levels and for a range of dbvs, a gamma value offset to a default gamma value at the second brightness level. the method includes determining, for a tap point representative of the range, a brightness value offset to a default brightness value at the second brightness level. the method includes storing the gamma value offset and the brightness value offset. subsequent to the storing, the device is configured to transition, in response to a fingerprint authentication triggering event, the display component from a first brightness level to a second brightness level by: overriding a default gamma value based on the gamma value offset, and displaying a portion of the display component by applying a value offset to a default brightness value at the second brightness level based on the brightness value offset.
20240221627. BACKPLANE FOR AN ARRAY OF EMISSIVE ELEMENTS_simplified_abstract_(google llc)
Inventor(s): Edwin Lyle Hudson of San Jose CA (US) for google llc, Bo Li of Folsom CA (US) for google llc
IPC Code(s): G09G3/32, G11C11/412
CPC Code(s): G09G3/32
Abstract: a backplane operative to drive an array of emissive pixel elements is disclosed. a plurality of pixel drive circuits form part of an array of emissive elements. the plurality of pixel drive circuits are disposed to form a plurality of rows and a plurality of columns. the plurality of pixel drive circuits are organized into sets of pixel drive circuits, and each set comprises at least one pixel drive circuit.
Inventor(s): Sangmoo Choi of Palo Alto CA (US) for google llc
IPC Code(s): G09G3/3208
CPC Code(s): G09G3/3208
Abstract: a display includes subpixel emissive areas of first, second, and third colors arranged in an array that includes rows and columns. the display also includes scan lines, column lines, and electronic subpixel circuits arranged in the array, with each subpixel circuit in a column of the array being electrically connected to a same column line and each electronic subpixel circuit configured for receiving electronic signals from a scan line and from a column line and for converting the received signals into a current signal provided to one of the subpixel emissive areas to drive light emission from the subpixel emissive area. the display further includes demultiplexer (demux) switches, where every other column line of the columns lines is configured to be connected to at least two outputs from a column line driver through the demux switches.
20240221717. SYSTEMS AND METHODS FOR ADAPTIVE ADDITIVE SOUND_simplified_abstract_(google llc)
Inventor(s): Christine Jean Wu of San Francisco CA (US) for google llc, Shokofeh Darbari of Palo Alto CA (US) for google llc, Shane Anton Myrbeck of Los Angeles CA (US) for google llc, Caitlyn Emily Riggs of San Francisco CA (US) for google llc
IPC Code(s): G10K11/178
CPC Code(s): G10K11/17881
Abstract: a method for adaptive additive sound includes receiving ambient sound data corresponding to ambient sound in a first zone acquired by a microphone in the first zone, analyzing the ambient sound data from the first zone, generating audio signal data for the second zone based at least in part on the ambient sound data from the first zone, and transmitting the audio signal data for the second zone to a speaker in the second zone. the first zone is separate from the second zone within a space.
Inventor(s): Raghav Gupta of Mountain View CA (US) for google llc, Yuan Cao of Mountain View CA (US) for google llc, Abhinav Kumar Rastogi of Mountain View CA (US) for google llc, Harrison J. Lee of Seattle WA (US) for google llc, Jeffrey Liangjie Zhao of Mountain View CA (US) for google llc
IPC Code(s): G10L15/18, G06F40/35, G10L15/06
CPC Code(s): G10L15/1815
Abstract: example methods include determining an input prompt comprising an utterance labeled with a sequence of slot-value pairs, wherein the sequence of slot-value pairs indicates possible slots and values in the utterance, and wherein the utterance relates to a task. the methods include determining a contextual representation comprising a concatenation of a history of utterances exchanged between a user and a service agent. the utterances describe a context for the task. the methods include training, based on a concatenation of the input prompt and the contextual representation, a sequence-to-sequence language model to predict a sequence of dialog states for an input task. the sequence of dialog states comprise an assignment of values to slots for which the user has indicated a preference in dialog sequences. the methods include providing the trained sequence-to-sequence language model.
20240221737. RECOGNIZING SPEECH IN THE PRESENCE OF ADDITIONAL AUDIO_simplified_abstract_(google llc)
Inventor(s): Diego Melendo Casado of Mountain View CA (US) for google llc, Ignacio Lopez Moreno of Brooklyn NY (US) for google llc, Javier Gonzalez-Dominguez of Madrid (ES) for google llc
IPC Code(s): G10L15/20, G06F3/16, G10L15/22, G10L15/26, G10L17/00, G10L17/06, G10L21/034, G10L25/84, H03G3/30
CPC Code(s): G10L15/20
Abstract: the technology described in this document can be embodied in a computer-implemented method that includes receiving, at a processing system, a first signal including an output of a speaker device and an additional audio signal. the method also includes determining, by the processing system, based at least in part on a model trained to identify the output of the speaker device, that the additional audio signal corresponds to an utterance of a user. the method further includes initiating a reduction in an audio output level of the speaker device based on determining that the additional audio signal corresponds to the utterance of the user.
Inventor(s): Dharma Muppalla of Lawrenceville NJ (US) for google llc, Nikhil Rao of Santa Clara CA (US) for google llc
IPC Code(s): G10L15/22, G06F3/16, G06F9/451, G06F11/07, G06F11/36, G06F16/242, G06F16/2455
CPC Code(s): G10L15/22
Abstract: validating actions in a digital assistant-based application is provided. the system identifies an application with a conversational interface. the system selects an action from an action repository and generates, via a natural language processor, a trigger phrase for input into the application. the system executes the application to process the trigger phrase to identify an action of the application. the system identifies a parameter used by the application to execute the action, and generates, based on the parameter and via execution of the conversational interface of the application, a first query responsive to the trigger phrase.
Inventor(s): Dharma Muppalla of Lawrenceville NJ (US) for google llc, Nikhil Rao of Santa Clara CA (US) for google llc
IPC Code(s): G10L15/22, G06F3/16, G06F9/451, G06F11/07, G06F11/36, G06F16/242, G06F16/2455
CPC Code(s): G10L15/22
Abstract: the system generates a first response to the first query for input into the application. the system determines, based on execution of the application to process the first response, a state of the application. the system evaluates the state to determine an error code and provide a notification based on the error code.
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc, Victor Carbune of Zurich (CH) for google llc
IPC Code(s): G10L15/22, G06F16/9032, G06F16/9035, G06F21/12, G10L15/26, G06F3/04812
CPC Code(s): G10L15/22
Abstract: implementations relate to generating a proficiency measure, and utilizing the proficiency measure to adapt one or more automated assistant functionalities. the generated proficiency measure is for a particular class of automated assistant actions, and is specific to an assistant device and/or is specific to a particular user. a generated proficiency measure for a class can reflect a degree of proficiency, of a user and/or of an assistant device, for that class. various automated assistant functionalities can be adapted, for a particular class, responsive to determining the proficiency measure satisfies a threshold, or fails to satisfy the threshold (or an alternate threshold). the adaptation(s) can make automated assistant processing more efficient and/or improve (e.g., shorten the duration of) user-assistant interaction(s).
20240221750. KEY PHRASE SPOTTING_simplified_abstract_(google llc)
Inventor(s): Wei Li of Mountain View CA (US) for google llc, Rohit Prakash Prabhavalkar of Santa Clara CA (US) for google llc, Kanury Kanishka Rao of Santa Clara CA (US) for google llc, Yanzhang He of Mountain View CA (US) for google llc, Ian C. McGraw of Menlo Park CA (US) for google llc, Anton Bakhtin of New York NY (US) for google llc
IPC Code(s): G10L15/22, G10L15/02, G10L15/06, G10L15/08, G10L15/14, G10L15/18, G10L19/00
CPC Code(s): G10L15/22
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting utterances of a key phrase in an audio signal. one of the methods includes receiving, by a key phrase spotting system, an audio signal encoding one or more utterances; while continuing to receive the audio signal, generating, by the key phrase spotting system, an attention output using an attention mechanism that is configured to compute the attention output based on a series of encodings generated by an encoder comprising one or more neural network layers; generating, by the key phrase spotting system and using attention output, output that indicates whether the audio signal likely encodes the key phrase; and providing, by the key phrase spotting system, the output that indicates whether the audio signal likely encodes the key phrase.
20240221772. Phrase Extraction for ASR Models_simplified_abstract_(google llc)
Inventor(s): Ehsan Amid of Mountain View CA (US) for google llc, Om Dipakbhai Thakkar of Sunnyvale CA (US) for google llc, Rajiv Mathews of Sunnyvale CA (US) for google llc, Francoise Beaufays of Mountain View CA (US) for google llc
IPC Code(s): G10L21/0332, G10L15/06, G10L15/08, G10L21/10
CPC Code(s): G10L21/0332
Abstract: a method of phrase extraction for asr models includes obtaining audio data characterizing an utterance and a corresponding ground-truth transcription of the utterance and modifying the audio data to obfuscate a particular phrase recited in the utterance. the method also includes processing, using a trained asr model, the modified audio data to generate a predicted transcription of the utterance, and determining whether the predicted transcription includes the particular phrase by comparing the predicted transcription of the utterance to the ground-truth transcription of the utterance. when the predicted transcription includes the particular phrase, the method includes generating an output indicating that the trained asr model leaked the particular phrase from a training data set used to train the asr model.
Inventor(s): James Robert Lim of Mountain View CA (US) for google llc, Wei Li of Saratoga CA (US) for google llc, Brian Conner of Davenport CA (US) for google llc, Brett Wilson of Los Altos CA (US) for google llc
IPC Code(s): H01M10/42, H01M10/48
CPC Code(s): H01M10/425
Abstract: an example outdoor mounted device includes a first battery configured to operate at a low temperature range that at least includes negative 20 celsius; a second battery configured to operate at a high temperature range; a temperature sensor; and processing circuitry configured to: determine, based on data received from the temperature sensors, a current temperature; responsive to determining that the current temperature is within the low temperature range, cause one or more components of the computing device to operate using electrical energy sourced from the first battery; and responsive to determining that the current temperature is within the high temperature range, cause the one or more components of the computing device to operate using electrical energy sourced from the second battery.
20240223012. WIRELESS CHARGING WITH SPLIT RESONANT CAPACITORS_simplified_abstract_(google llc)
Inventor(s): Li Wang of Mountain View CA (US) for google llc, Liang Jia of Mountain View CA (US) for google llc, Liyu Yang of Mountain View CA (US) for google llc, Stefano Saggini of Udine (IT) for google llc
IPC Code(s): H02J50/12, H02J50/40
CPC Code(s): H02J50/12
Abstract: an example device includes a plurality of capacitor and wireless charging coil series pairs that are collectively in parallel; and one or both of: a driver circuit configured to drive the plurality of capacitor and wireless charging coil series pairs with a first common signal; or a sink circuit configured to receive a second common signal from the plurality of capacitor and wireless charging coil series pairs.
20240223209. Lossy Compression of Time Series Data_simplified_abstract_(google llc)
Inventor(s): Jeffrey Max QUINLAN-GALPER of Issaquah WA (US) for google llc
IPC Code(s): H03M7/30
CPC Code(s): H03M7/3059
Abstract: a method includes obtaining time series data that includes a series of data points listed in temporal order. the method includes determining that a size of the time series data fails to satisfy a threshold size. in response, the method includes determining a range of the series of data points and determining, using the range of the series of data points, a respective score for each respective data point in the series of data points. the method also includes removing, using the respective scores for each data point in the series of data points, a plurality of data points from the series of data points. after removing the plurality of data points from the series of data points, the method includes determining an updated size of the series of data points and determining that the updated size of the series of data points satisfies the threshold size.
Inventor(s): Justin Lewis of Mountain View CA (US) for google llc, Ruxandra Georgiana Davies of Santa Monica CA (US) for google llc
IPC Code(s): H04L51/52, G06Q30/0601, H04L51/10, H04L65/612
CPC Code(s): H04L51/52
Abstract: systems and methods are provided that facilitate selecting videos to share in a messaging session. a system is provided that includes an accessible data mining component configured to generate a first set of data associated with a messaging session between a user and one or more other user, the first set of data excluding data that is inaccessible to the user and comprising data that is accessible to the user, and an identification component configured to identify a set of media items based on the first set of data. an inaccessible data mining component is further configured to generate a second set of data comprising data that is inaccessible to the user but accessible to at least one of the one or more other users, and a recommendation component configured to recommend a subset of the set of media items to the user based on the second set of data.
Inventor(s): Ronald Ho of Sunnyvale CA (US) for google llc, Christopher Paul David Johnson of Mountain View CA (US) for google llc
IPC Code(s): H04L65/1069, H04W4/80, H04W12/06
CPC Code(s): H04L65/1069
Abstract: technology for automatic cross-device meeting authentication. an example method involving initializing, by a mobile computing device, a real-time meeting communication session; receiving information indicative of the mobile computing device being in a physical presence of the first computing device, causing the mobile computing device at the physical location of the first computing device to display a user interface element, which when selected allows the participation of the user in the real-time meeting communication session to continue via the mobile computing device of the user at the physical location of the first computing device, granting control of the real-time meeting communication session to the first computing device from the mobile computing device of the user at the physical location of the first computing device, and allowing the user to participate in the real-time meeting communication session at the physical location of the first computing device upon a user selection of the user interface element.
Inventor(s): Ronald Ho of Sunnyvale CA (US) for google llc, Christopher Paul David Johnson of Mountain View CA (US) for google llc
IPC Code(s): H04L65/1069, H04W4/80, H04W12/06
CPC Code(s): H04L65/1069
Abstract: technology for automatic cross-device meeting authentication. an example method involving initializing, by a first computing device, a real-time meeting communication session, receiving information indicative of a mobile computing device of a user being in a physical presence of the first computing device, wherein the user is associated with the mobile device and a second computing device; granting control of the real-time meeting communication session to the first computing device, causing the second computing device of the user at the physical location of the first computing device to display a user interface element, which when selected allows the participation of the user in the real-time meeting communication session to continue via the second computing device of the user at the physical location of the first computing device, and allowing the user to participate in the real-time meeting communication session to the second computing device of the user at the physical location of the first computing device upon a user selection of the user interface element.
Inventor(s): Debargha Mukherjee of Cupertino CA (US) for google llc, Mohammed Golam Sarwer of San Jose CA (US) for google llc, Rachel Barker of Cambridge (GB) for google llc, Jianle Chen of San Diego CA (US) for google llc, Xiang Li of Saratoga CA (US) for google llc
IPC Code(s): H04N19/52, H04N19/109, H04N19/139, H04N19/17, H04N19/176, H04N19/184
CPC Code(s): H04N19/52
Abstract: coding using local global prediction modes with projected motion fields includes identifying a current frame, identifying a current reference frame, obtaining a projected motion field, for the current frame, using motion data from the current reference frame, identifying a current superblock from the current frame, obtaining reference warp motion parameters for the current superblock by fitting the projected motion field to a warp motion model, and using the reference warp motion parameters to code respective blocks from the superblock.
20240223817. VIDEO COMPRESSION USING OPTICAL FLOW_simplified_abstract_(google llc)
Inventor(s): George Dan Toderici of Mountain View CA (US) for google llc, Eirikur Thor Agustsson of Zurich (CH) for google llc, Fabian Julius Mentzer of Zurich (CH) for google llc, David Charles Minnen of Mountain View CA (US) for google llc, Johannes Balle of San Francisco CA (US) for google llc, Nicholas Johnston of San Jose CA (US) for google llc
IPC Code(s): H04N19/91, G06T3/18, G06T5/70, H04N19/124, H04N19/137
CPC Code(s): H04N19/91
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for compressing video data. in one aspect, a method comprises: receiving a video sequence of frames; generating, using a flow prediction network, an optical flow between two sequential frames, wherein the two sequential frames comprise a first frame and a second frame that is subsequent the first frame; generating from the optical flow, using a first autoencoder neural network: a predicted optical flow between the first frame and the second frame; and warping a reconstruction of the first frame according to the predicted optical flow and subsequently applying a blurring operation to obtain an initial predicted reconstruction of the second frame.
Inventor(s): Bartlomiej Wolowiec of Zürich (CH) for google llc, Andreea-Alexandra Ganciulescu of Oxford (GB) for google llc
IPC Code(s): H04N21/234, G06F18/213, G06F18/2413, G06N3/04, H04N21/258, H04N21/2743, H04N21/454
CPC Code(s): H04N21/23418
Abstract: techniques are disclosed for identifying videos containing objectionable content. an example method comprises identifying, by a computing system, a video uploaded to a video sharing service, generating an embedding for the video using a neural network, wherein the embedding specifies a location of the video in a multi-dimensional space where a plurality of videos are located based on content of the videos, identifying from the videos a plurality of associated videos that each have an associated embedding that is located within a predetermined distance of the embedding, determining whether the video is likely to include a particular type of objectionable content by at least determining at least a predetermined amount of the associated videos that contain the particular type of objectionable content, and responsive to determining that the video is likely to include the particular type of objectionable content, causing the video to be blocked from the video sharing service.
Inventor(s): Benjamin James Schaeffer of Brooklyn NY (US) for google llc, Matthew Stephen Ross of New York NY (US) for google llc
IPC Code(s): H04N21/81, H04N21/85
CPC Code(s): H04N21/81
Abstract: methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for the selection, provision and display of one or more digital components during display of content. methods can include identifying a plurality of digital components that can be presented on the client device. a maximum number of digital components that can be presented in a slot of a content and the time duration of the slot is determined. for each digital component a score is generated based on the duration, a position requirement and the number of times the digital component is available for provision within the slot is generated. a first set of digital component is selected based on the scores and provided to the client device.
20240223868. Managing Audio Assets_simplified_abstract_(google llc)
Inventor(s): Natalie Bennett of Mountain View CA (US) for google llc, Lucy Mao of Mountain View CA (US) for google llc
IPC Code(s): H04N21/81, G06F3/16
CPC Code(s): H04N21/8106
Abstract: a method for managing audio assets includes selecting a content item for display at multiple geographic locations, including selecting a plurality of variants corresponding to the respective geographic locations. the variants include a shared component of the content item. the method also includes determining a set of audio components, where each of the variants includes two or more audio components of the set of audio components, and determining whether any of the variants exceeds a duration limit. the method also includes, in response to determining that a particular one of the variants exceeds the duration limit, generating (i) an indication that the particular one of the variants exceeds the duration limit, and (ii) an indication of an audio component that likely causes the particular one of the variants to exceed the duration limit.
20240223980. TRANSDUCER EXCURSION CORRECTION_simplified_abstract_(google llc)
Inventor(s): Lei Chen of Taipei (TW) for google llc, Yahsin Chou of Taipei City (TW) for google llc, Shin-Horng Chen of Taipei City (TW) for google llc
IPC Code(s): H04R29/00, G01R19/12, H04R3/00
CPC Code(s): H04R29/003
Abstract: in general, various aspects of the techniques are directed to transducer excursion correction. a computing device comprising a memory and a processor may be configured to perform the techniques. the memory may store voltage measurements representative of voltage across a transducer and current measurements representative of current through the transducer. the processor may identify a first voltage measurement of the voltage measurements and a first current measurement of the current measurements associated with nonlinear vibration of the transducer. the processor may perform a principal component analysis with respect to the first voltage measurement and the first current measurement to obtain a principal component representative of variation of the voltage across and the current through the transducer. the processor may modify, based on the principal component, an input voltage to be applied across the transducer to reduce the nonlinear vibration of the transducer.
20240223981. Systems and Methods for Acoustic Behavior Feedback_simplified_abstract_(google llc)
Inventor(s): Christine Jean Wu of San Francisco CA (US) for google llc, Shokofeh Darbari of Palo Alto CA (US) for google llc, Shane Anton Myrbeck of Los Angeles CA (US) for google llc, Caitlyn Emily Riggs of San Francisco CA (US) for google llc, Jack Godfrey Wood of San Francisco CA (US) for google llc, Andy Furner of London (GB) for google llc, Harc Lee of London (GB) for google llc
IPC Code(s): H04R29/00, G01H3/12, G08B5/36, G08B21/18
CPC Code(s): H04R29/008
Abstract: a system for acoustic behavior feedback includes a light emitter and a microphone. ambient sound data from the microphone may be compared to a threshold sound level, and one of a plurality of settings for the light emitter may be selected based at least in part on the comparison between the ambient sound data and threshold sound level. each of the plurality of settings corresponds to a respective sound level alert as feedback for at least one person proximate the microphone and the light emitter.
20240224187. THERMAL MITIGATION FOR CELLULAR DEVICES_simplified_abstract_(google llc)
Inventor(s): Madhusudan Kinthada Venkata of San Diego CA (US) for google llc, Shivank Nayak of Milpitas CA (US) for google llc, Siddharth Ray of Sunnyvale CA (US) for google llc
IPC Code(s): H04W52/02, G06F1/3234
CPC Code(s): H04W52/0251
Abstract: a cellular user equipment (ue) device is configured to determine a thermal trigger event has occurred. responsive to the thermal trigger event, the ue device determines a first data measurement associated with at least a first radio access technology (rat) of the ue device and a second data measurement associated with at least a second rat of the ue device. the ue device performs a first level of thermal mitigation for the first rat and a second level of thermal mitigation for the second rat based on the first data measurement being different than the second data measurement.
20240224223. Evaluating IP Location On A Client Device_simplified_abstract_(google llc)
Inventor(s): Antonio Trapanese of Zurich (CH) for google llc, Ankit Gupta of Zurich (CH) for google llc, Pawel Walczak of Pfaffikon (CH) for google llc
IPC Code(s): H04W64/00, G06F16/9537, H04W4/02, H04W4/029, H04W8/26, H04W80/04
CPC Code(s): H04W64/003
Abstract: aspects of the technology evaluate a client device query to identify an ip address-based estimated location of a mobile device (). one or more candidate wireless stations are selected in accordance with the ip-based estimated location and a location-relevant response to the query is also generated in accordance with the ip-based location. this information is transmitted to the mobile device. (). the mobile device compares the received information about the candidate wireless stations against one or more actual wireless stations with which the mobile device is in communication (). log information is generated as a result of the comparison. the log information is anonymized and transmitted to the network without user id or other client-identifiable information included in the log. (fig. ) the received log information is then used to validate the initial estimated location. aggregation of log information from multiple devices may be used in the validation process. (fig. ).
- Google LLC
- A47C7/72
- CPC A47C7/727
- Google llc
- B25J5/00
- G06F18/214
- G06V10/40
- G06V10/44
- G06V10/764
- G06V10/776
- G06V10/82
- G06V10/94
- G06V20/10
- G06V20/64
- CPC B25J5/007
- B60W60/00
- B60W30/165
- CPC B60W60/0025
- G01C21/36
- G06F3/14
- G06F3/16
- G06F21/32
- G10L15/08
- CPC G01C21/3629
- G01S13/87
- G01S13/76
- CPC G01S13/878
- G02B6/44
- CPC G02B6/44528
- G02B27/01
- CPC G02B27/0172
- G06F7/544
- G06F7/485
- G06F7/487
- G06F15/80
- CPC G06F7/5443
- G06F11/14
- G06F11/07
- CPC G06F11/1402
- G06F16/35
- G06F16/50
- CPC G06F16/35
- G06F16/435
- G06F16/951
- G06F16/9535
- G06F16/9538
- CPC G06F16/435
- G06F16/84
- G06F16/21
- G06F16/83
- G06F16/835
- G06F16/33
- CPC G06F16/86
- G06F21/62
- CPC G06F21/6254
- G06F40/166
- G06F16/176
- G06F40/194
- CPC G06F40/166
- G06F40/35
- G06F16/36
- CPC G06F40/35
- G06F40/20
- G06F40/284
- G10L13/02
- G06F40/40
- G06F16/332
- CPC G06F40/40
- G06F40/58
- G06F40/51
- G10L15/00
- G10L15/22
- CPC G06F40/58
- G06N3/04
- CPC G06N3/04
- G06N3/045
- G06F11/20
- G06N3/063
- H02J50/10
- H04L12/42
- H04L45/02
- H04L45/28
- CPC G06N3/045
- G06N3/08
- CPC G06N3/08
- G06N10/20
- G06N10/40
- G06N10/70
- CPC G06N10/20
- G06N20/00
- CPC G06N20/00
- G06N20/20
- CPC G06N20/20
- G06Q20/32
- G06Q20/20
- G06Q20/40
- CPC G06Q20/3226
- G06Q30/0201
- G06F16/22
- G06F16/2453
- G06F17/16
- G06N5/04
- CPC G06Q30/0201
- G06Q30/0251
- G06Q30/0241
- CPC G06Q30/0256
- G06V10/778
- G06V10/771
- CPC G06V10/7788
- G06V40/40
- G06V40/16
- CPC G06V40/40
- G09G3/20
- G06V40/12
- CPC G09G3/2007
- G09G3/32
- G11C11/412
- CPC G09G3/32
- G09G3/3208
- CPC G09G3/3208
- G10K11/178
- CPC G10K11/17881
- G10L15/18
- G10L15/06
- CPC G10L15/1815
- G10L15/20
- G10L15/26
- G10L17/00
- G10L17/06
- G10L21/034
- G10L25/84
- H03G3/30
- CPC G10L15/20
- G06F9/451
- G06F11/36
- G06F16/242
- G06F16/2455
- CPC G10L15/22
- G06F16/9032
- G06F16/9035
- G06F21/12
- G06F3/04812
- G10L15/02
- G10L15/14
- G10L19/00
- G10L21/0332
- G10L21/10
- CPC G10L21/0332
- H01M10/42
- H01M10/48
- CPC H01M10/425
- H02J50/12
- H02J50/40
- CPC H02J50/12
- H03M7/30
- CPC H03M7/3059
- H04L51/52
- G06Q30/0601
- H04L51/10
- H04L65/612
- CPC H04L51/52
- H04L65/1069
- H04W4/80
- H04W12/06
- CPC H04L65/1069
- H04N19/52
- H04N19/109
- H04N19/139
- H04N19/17
- H04N19/176
- H04N19/184
- CPC H04N19/52
- H04N19/91
- G06T3/18
- G06T5/70
- H04N19/124
- H04N19/137
- CPC H04N19/91
- H04N21/234
- G06F18/213
- G06F18/2413
- H04N21/258
- H04N21/2743
- H04N21/454
- CPC H04N21/23418
- H04N21/81
- H04N21/85
- CPC H04N21/81
- CPC H04N21/8106
- H04R29/00
- G01R19/12
- H04R3/00
- CPC H04R29/003
- G01H3/12
- G08B5/36
- G08B21/18
- CPC H04R29/008
- H04W52/02
- G06F1/3234
- CPC H04W52/0251
- H04W64/00
- G06F16/9537
- H04W4/02
- H04W4/029
- H04W8/26
- H04W80/04
- CPC H04W64/003
