A method includes receiving a sequence of acoustic frames characterizing one or more utterances. At each of a plurality of output steps, the method also includes generating, by an encoder network of a speech recognition model, a higher order feature representation for a corresponding acoustic frame of the sequence of acoustic frames, generating, by a prediction network of the speech recognition model, a hidden representation for a corresponding sequence of non-blank symbols output by a final softmax layer of the speech recognition model, and generating, by a first joint network of the speech recognition model that receives the higher order feature representation generated by the encoder network and the dense representation generated by the prediction network, a probability distribution that the corresponding time step corresponds to a pause and an end of speech.
A computing system is described that includes a memory that stores one or more modules and one or more processors. The one or more processors, when executing the one or more modules, are configured to determine, based on application policy information for an application, one or more application policies for the application, monitor execution of the application to determine a set of application behaviors, compare the set of application behaviors to the one or more application policies, and output an indication of whether one or more application behaviors from the set of application behaviors are consistent with the one or more application policies.
G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs
G06F 21/55 - Detecting local intrusion or implementing counter-measures
A method for recognizing a voice input includes receiving a first voice input including a plurality of terms, processing the first voice input based on the plurality of terms to obtain a first speech recognition result including one or more candidate terms corresponding to one or more terms from the plurality of terms, receiving a second voice input providing at least one of contextual information relating to the first voice input or confirmation information relating to the one or more candidate terms, and processing the second voice input based on the at least one of the contextual information or the confirmation information to obtain a second speech recognition result including at least one of the one or more candidate terms or one or more new candidate terms, as corresponding to the one or more terms from the plurality of terms.
Implementations relate to generating multi-modal response(s) through utilization of large language model(s) (LLM(s)) and other generative model(s). Processor(s) of a system can: receive natural language (NL) based input, generate a multi-modal response that is responsive to the NL based output, and cause the multi-modal response to be rendered. In some implementations, and in generating the multi-modal response, the processor(s) can process, using a LLM, LLM input to generate LLM output, and determine, based on the LLM output, textual content and generative multimedia content for inclusion in the multi-modal response. In some implementations, the generative multimedia content can be generated by another generative model (e.g., an image generator, a video generator, an audio generator, etc.) based on generative multimedia content prompt(s) included in the LLM output and that is indicative of the generative multimedia content. In various implementations, the generative multimedia content can be interleaved between segments of the textual content.
G06F 40/40 - Processing or translation of natural language
G06F 16/483 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A method for secure online collaboration is provided. The method includes providing a graphical user interface (GUI) for online collaborative editing of a document in association with a first server of a cloud-based storage system, receiving an edit to a portion of the document via the GUI, encrypting the edit to the portion of the document based on a data encryption key associated with a second server that is independent of the first server, generating encrypted data representing the edit to the portion of the document, wherein the encrypted data includes the encrypted edit to the portion of the document, and providing the encrypted data to the first server that is unable to decrypt (i) the document in the encrypted form, and (ii) the encrypted edit to the portion of the document.
Methods, devices, systems, and means for user equipment slicing assistance information by a user equipment, UE, are described herein. The UE detects a condition of the UE (610) and, based on the detecting, evaluating one or more preferences (612). Based on evaluating the one or more preferences, the UE sends UE Slicing Assistance Information, USAI, to a core network entity (614), the USAI being based on a current network slice configuration. The UE receives, from a base station, a reduced radio resource configuration for operating using the low-throughput network slice (616) and communicates using the low-throughput network slice (618).
Systems and methods include a memory and processing devices configured to perform operations. The operations include obtaining telemetry log data comprising an event log that includes one or more values; parsing, using an event log parser extension, a first portion of the one or more values to insert one or more first key-value pairs into a data object, wherein at least a portion of the one or more first key-value pairs includes a value from the first portion of the one or more values and a key assigned to the value; and performing one or more data analysis operations on the data object.
A method is disclosed for generating an extractive summary of a resource responsive to a query. Extractive resources can be used to rank responsive resources and/or to enhance a search result. An example method can involve determining relevance scores for sentences within the resources, generating extractive summaries from sentences with the highest relevance scores, and calculating a resource relevance scores for each resource based on the extractive summary. The resources are then ranked based on the relevance scores and a search result page generated. In some implementations, a machine learned model is used to generate the relevance score and/or the extractive summary.
A method for predicting color variance using a proxy includes generating a first 3D object proxy based on a stored 3D object, generating a second 3D object proxy based on the stored 3D object, transforming the first 3D object proxy based on a 3D object identified in a frame of a video, transforming the second 3D object proxy based on the 3D object identified in a key frame of the video, mapping color attributes from the 3D object identified in the frame of the video to the transformed first 3D object proxy, mapping color attributes from the 3D object identified in the key frame to the transformed second 3D object proxy, and generating color data for the 3D object based on the color attributes for the transformed first 3D object proxy and the color attributes for the transformed second 3D object proxy.
H04N 19/597 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
H04N 19/186 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a colour or a chrominance component
H04N 19/42 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
10.
Defining Data Structures and Algorithms for Protobuf Based Differential Management Systems
A method for differential management includes obtaining a first instance and a second instance of content of a content management system, the first instance including a first plurality of objects of the content, and the second instance including a second plurality of objects of the content. The method includes determining a first tree data structure representing the first plurality of objects at the first instance and a second tree data structure representing the second plurality of objects at the second instance. The method includes identifying, based on a comparison of the first tree data structure and the second tree data structure, a set of deltas. The method includes transmitting, to a client device, the set of deltas that, when received by the client device, cause the client device to display the set of deltas via a user-interface of the client device.
Generally disclosed herein are electronic circuits with high bandwidth interfaces (HBI) for multi-directional die-to-die communications. The HBIs are designed to allow for sharing of data between all sides of the memory chiplets. By using all sides of the memory chiplets and multiplexing the data between the multiple connected chiplets, the total bandwidth of the memory available to the connected chiplets can increase. The sharing and multiplexing of the data can also be dynamically configured to accommodate various options for the allocation of performance levels and the associated cost.
Dynamically controlling output from a device, such as an automated assistant device. Control of the output can be based on, for example, a condition and/or physiological attribute(s) of a user of the device. Various implementations dynamically control the output to improve sleep quality for the user and/or mitigate waste of computational and/or network resources.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
A61M 21/00 - Other devices or methods to cause a change in the state of consciousnessDevices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
A61M 21/02 - Other devices or methods to cause a change in the state of consciousnessDevices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia
H04N 21/485 - End-user interface for client configuration
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
According to an aspect, a method for searching within user-generated reviews includes receiving, from a client device, a search query to search within a plurality of user-generated reviews relating to a plurality of entities, and identifying, in response to the search query, a set of user-generated reviews from the plurality of user-generated reviews that correspond to one or more search terms of the search query, where the set of user-generated reviews includes a user-generated review for a first entity and a user-generated review for a second entity. The first entity is different from the second entity. The method includes providing at least a portion of the user-generated review for the first entity and at least a portion of the user-generated review for the second entity for simultaneous display on a comparison layout of a user interface of the client device.
An interface for electrically coupling a biosensor to electrodes of a wearable computing device is provided. The interface includes a first portion that includes a first material configured to provide a conductive path between the biosensor and the electrodes of the wearable electronic device. The interface further includes a second portion that is different than the first portion. The second portion includes a second material that is different than the first material and is configured to removably couple the interface to the wearable electronic device such that the first portion contacts the electrodes of the wearable electronic device to provide the conductive path between the biosensor and the electrodes.
In a method of managing a configured grant small data transmission (CG-SDT) time alignment timer that indicates validity of a CG-SDT configuration, a user equipment (UE) receives a radio resource control (RRC) release message from a radio access network (RAN). In response to the RRC release message, the UE resets a medium access control (MAC) entity of the UE and, after resetting the MAC entity, starts the CG-SDT time alignment timer.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for compressed-domain compositing of video streams. A server obtains compressed video streams, each compressed video stream including multiple frames, each frame including a video content region that is a portion of the frame, encoded using a segment identifier for pixels included in the video content region, and encoded using a set of static symbol frequencies. The server receives, from a user device, a request for video stream content, and composites a first and a second compressed video stream to obtain a compressed-domain composite video stream including a first video content region of the first compressed video stream and a second video content region of the second compressed video stream, and provides, to the user device, a packet including a set of frames of the compressed-domain composite video stream decodable by a single decoder.
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
Technique or mechanism in which network security policies are applied close to the source or origin associated with policy decisions. For example. the disclosed technology moves dropped flows from a firewall cluster to a leaf switch based on host location.
This document describes systems and techniques directed at extending touch-sensitive regions in electronic devices. In aspects, an electronic device includes a cover layer, a touch sensor panel, and an electronic visual display panel (“display panel”). The cover layer includes a top face and a side face. The touch sensor panel has a first sensing region corresponding to a surface of the top face and a second sensing region at least partially corresponding to a second surface of the side face. The display panel has an active area corresponding at least partially to the first surface of the top face. The active area of the touch sensor panel is greater than an active area of the display panel. Despite the display panel and the touch sensor panel having different active area sizes, an integrated circuit is configured to control both of them, maximizing an internal volumetric efficiency.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a network input to generate a network output. In one aspect, one of the systems includes a neural network configured to perform the machine learning task, the neural network including one or more merger neural network blocks that each generate block output sequence that has fewer elements than the block input sequence that is processed by the merger neural network block.
A high-resolution display that is a small size suitable for mobile applications is disclosed. The display is color and so includes different color subpixels arranged in subpixel groups. To minimize power consumption, each subpixel includes its own power rail supplying the subpixel with a rail voltage that is based on a forward voltage of a corresponding light emitting diode. To minimize the area of the subpixel group, transistors of the subpixels are fabricated within a common well and the body terminals of the transistors are connected to a common well rail that is separate from the power rails.
G09G 3/32 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED]
H01L 25/16 - Assemblies consisting of a plurality of individual semiconductor or other solid-state devices the devices being of types provided for in two or more different subclasses of , , , , or , e.g. forming hybrid circuits
21.
INCREMENTAL HEAD-RELATED TRANSFER FUNCTION UPDATES
Disclosed implementations for generating personalized audio. Sensor data corresponding with at least one physical characteristic of a user is received. A three-dimensional mesh of the user is updated based on the sensor data. An impulse response for the user is determined based on the three-dimensional mesh. An audio stream is generated based on the impulse response.
This specification describes memory controllers with adaptive precharge scheduling. In one aspect, a memory controller includes a refresh scheduler configured to send refresh commands to dynamic random-access memory (DRAM) banks of a DRAM memory system that includes DRAM banks arranged in a set of DRAM bank groups each comprising one or more DRAM banks. The memory controller includes an adaptive precharge scheduler configured to determine a priority score for each DRAM bank group based on a set of parameters, select, based on the priority score for each DRAM bank group, a particular DRAM bank group to close so that each DRAM bank in the DRAM bank group can be refreshed by the refresh scheduler, and send the precharge command to at least one DRAM bank of the particular DRAM group.
Implementations set forth herein relate to generating training data, such that each instance of training data includes a corresponding instance of vision data and drivability label(s) for the instance of vision data. A drivability label can be determined using first vision data from a first vision component that is connected to the robot. The drivability label(s) can be generated by processing the first vision data using geometric and/or heuristic methods. Second vision data can be generated using a second vision component of the robot, such as a camera that is connected to the robot. The drivability labels can be correlated to the second vision data and thereafter used to train one or more machine learning models. The trained models can be shared with a robot(s) in furtherance of enabling the robot(s) to determine drivability of areas captured in vision data, which is being collected in real-time using one or more vision components.
G06N 3/008 - Artificial life, i.e. computing arrangements simulating life based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
Systems and methods for generating a machine-learned model are disclosed herein. The method can include receiving, by a computing system comprising one or more processors, one or more data items, the one or more data items being associated with usage of a user device by a user and inferring, by the one or more processors, one or more data labels based on the one or more data items, the data labels being indicative of the usage of the user device by the user. The method can also include generating, by the one or more processors, a personalized model using the one or more data labels and a base model.
Visual search in an operating system of a computing device can process and provide additional information on the content being provided for display. The computing device can include an operating system that includes a visual search interface that obtains and processes display data associated with content currently being provided for display. The visual search interface can generate display data based on the current content provided for display, process the display data with one or more on-device machine-learned models, and provide additional information to the user. The visual search interface may transmit data associated with the display data to perform additional data processing tasks. Application suggestions may be determined and provided based on the visual search data.
A motion field is generated for a current frame. At least one sub-block of a largest coding block is determined to be orphaned. An orphaned sub-block is one that is not associated with any motion vector. An extended region of the current frame that includes the largest coding block is identified. A motion vector is set to the sub-block based on respective motion vectors of sub-blocks within the extended region.
H04N 19/17 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
H04N 19/176 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
H04N 19/543 - Motion estimation other than block-based using regions
H04N 19/105 - Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
H04N 19/577 - Motion compensation with bidirectional frame interpolation, i.e. using B-pictures
A brightness level of a display is set to a brightness level by using one or more dimming techniques such that the display maintains a uniform appearance. One or more processors perform operations including determining, via one or more processors, to change a brightness level of a display, wherein the display includes pixels that can be individually turned on and off; analyzing the brightness level with respect to a minimum brightness level associated with the display; in response to analyzing the brightness level, determining, via the one or more processors, individual pixels of the display to turn off to reduce the brightness level; and causing the individual pixels of the display to turn off.
G09G 3/20 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix
G09G 3/3208 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED] organic, e.g. using organic light-emitting diodes [OLED]
An example mobile computing device includes a main logic board (MLB); a first antenna array positioned on the MLB and configured to transmit signals in a first direction, the first antenna array comprising one or more planes; and a second antenna array positioned on the MLB and configured to transmit signals in a second direction, the second, direction being different than the first direction, the second antenna array comprising one or more planes and the second direction being different than the first direction, wherein at least one of the one or more of the planes in the first antenna array or at least one of the one or more of the pianos in the second antenna array comprises a meshed patch structure.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using cryptographic protocols to generate network measurements in privacy preserving ways are described. In one aspect, a method includes sending, by a network measurement system and to a client device, data indicating a size for a partial identifier for an application of the client device. The network measurement system receives, from the client device, (i) a partial masked identifier generated by masking a complete identifier for the client device or a user of the client device and removing a portion of a resulting complete masked identifier based on the size and (ii) a first encrypted identifier generated by encrypting the complete masked identifier using an encryption key of the client device.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/06 - Arrangements for secret or secure communicationsNetwork security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
A computing device may include a display having a periodic structure. The computing device includes a light source that emits light towards at least a portion of the display, and the periodic structure of the display may diffract tire light into a plurality of light dots that are projected onto a scene. The computing device includes a camera, that may capture the plurality of light dots in the scene. The computing device may determine depth values associated with the plurality of light dots.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G06V 10/145 - Illumination specially adapted for pattern recognition, e.g. using gratings
H04M 1/02 - Constructional features of telephone sets
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for compressed-domain compositing of video streams. A server obtains compressed video streams, each compressed video stream including multiple frames, each frame including a video content region that is a portion of the frame, encoded using a segment identifier for pixels included in the video content region, and encoded using a set of static symbol frequencies. The server receives, from a user device, a request for video stream content, and composites a first and a second compressed video stream to obtain a compressed-domain composite video stream including a first video content region of the first compressed video stream and a second video content region of the second compressed video stream, and provides, to the user device, a packet including a set of frames of the compressed-domain composite video stream decodable by a single decoder.
H04N 21/2343 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
H04N 21/2365 - Multiplexing of several video streams
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
32.
MANAGING SMALL DATA TRANSMISSION FOR A USER EQUIPMENT
A method of managing configuration information for SDT operation is performed by a DU of a distributed base station. The method includes receiving, from a CU of the distributed base station, a CU-to-DU message including a full SDT configuration for a UE, generating a delta SDT configuration to update the full SDT configuration, and transmitting to the CU a DU-to-CU message that includes the delta SDT configuration.
A multi-try encoding operation is implemented to encode one or more game frames into a game stream. The multi-try encoding operation includes determining an initial quantization parameter for a current frame. From the determined initial quantization parameter, one or more alternative quantization parameters are derived. Multiple encoders then perform multiple encodings on the current frame based on the initial quantization parameter and the alternative quantization parameters, respectively, to produce a plurality of encoded frames. An applicable encoded frame is then selected from the plurality of encoded frames according to a streaming application. The applicable encoded frame is then transmitted as part of a game stream to a client system.
H04N 19/126 - Details of normalisation or weighting functions, e.g. normalisation matrices or variable uniform quantisers
A63F 13/52 - Controlling the output signals based on the game progress involving aspects of the displayed game scene
H04N 19/14 - Coding unit complexity, e.g. amount of activity or edge presence estimation
H04N 19/164 - Feedback from the receiver or from the transmission channel
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
34.
PERFORMING SEGMENTED INFERENCE OPERATIONS OF A MACHINE LEARNING MODEL
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing inference operations of machine learning models, are described in this document. In one aspect, the method includes receiving data representing a first machine learning model that includes inference operations. An estimated duration for the system to perform the inference operations is obtained. A priority time period reserved for performing priority inference operations of a priority machine learning model during each occurrence of a recurring time window is obtained. A remaining time period of each occurrence of the recurring time window that remains after reserving the priority time period is determined. A determination is made that the estimated duration is greater than the remaining time period. In response, the first machine learning model is partitioned into a group of sub-models. The hardware processing unit(s) perform inference operations of a sub-model during the remaining time period.
A method, performed by a UE, of managing time alignment includes receiving a timing advance command from a RAN, starting or restarting a first time alignment timer that indicates validity of a CG configuration when the UE is in an RRC connected state with the RAN, and then receiving a first message from the RAN. The method also includes, in response to the first message, transitioning from the RRC connected state to an RRC inactive state, stopping the first time alignment timer, and starting or restarting a second time alignment timer that indicates validity of a CG-SDT configuration when the UE is in the RRC inactive state, and then receiving a second message from the RAN. The method also includes, in response transitioning to the RRC connected state, again starting the first time alignment timer, and communicating data with the RAN.
A method of managing configuration information for SDT operation is performed by a RAN node. The method includes transmitting to a UE, while the UE is in an RRC connected state, a first message, the first message including an SDT configuration for use by the UE when the UE operates in an RRC inactive state. The method also includes, after transmitting the first message, determining to release the SDT configuration. The method also includes, in response to the determining and while the UE is in the RRC inactive state, transmitting to the UE an RRC release message including a release indication for indicating that the UE is to release the SDT configuration.
A system for controlling a head mounted device (HMD). The system includes a processor of a controller of the HMD connected to an Internal Measurement Unit (IMU) and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: receive Internal Measurement Unit (IMU) data generated in response to vibrations produced by voiced nasal consonant vocalizations produced by an HMD user, analyze the IMU data to determine whether the IMU data corresponds to an HMD control command, and responsive to a determination that the IMU data corresponds to the HMD control command, execute the HMD control command.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for object detection using neural networks. In one aspect, one of the methods includes obtaining an input image; processing the input image using an object detection neural network to generate an output sequence that comprises respective token at each of a plurality of time steps, wherein each token is selected from a vocabulary of tokens that comprises (i) a first set of tokens that each represent a respective discrete number from a set of discretized numbers and (ii) a second set of tokens that each represent a respective object category from a set of object categories; and generating, from the tokens in the output sequence, an object detection output for the input image.
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
Systems and methods for image understanding can include one or more object recognition systems and one or more vision language models to generate an augmented language output that can be both scene-aware and object-aware. The systems and methods can process an input image with an object recognition model to generate an object recognition output descriptive of identification details for an object depicted in the input image. The systems and methods can include processing the input image with a vision language model to generate a language output descriptive of a predicted scene description. The object recognition output can then be utilized to augment the language output to generate an augmented language output that includes the scene understanding of the language output with the specificity of the object recognition output.
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 20/40 - ScenesScene-specific elements in video content
40.
POWER SAVING IN OLED DISPLAYS WITH MULTIPLE REFRESH RATES
Rendering images on an active area of an OLED includes rendering images on the active area of the display panel with a plurality of different frame rates. For a plurality of the different frame rates having a frame rate that matches or is above a threshold frame rate, an image refresh operation is performed once per frame period and a self-refresh operation is not performed during the frame period. When rendering images on the active area, for at least one of the different frame rates having a frame rate that is lower than the threshold frame rate, an image refresh operation is performed once per frame period and a self-refresh operation is performed at least once during the frame period.
G09G 3/20 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix
G09G 3/3233 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED] organic, e.g. using organic light-emitting diodes [OLED] using an active matrix with pixel circuitry controlling the current through the light-emitting element
41.
OVERLAPPING IMAGE FIELD UPDATES IN A DISPLAY SYSTEM
An illustrative display system includes an array of pixels and a frame controller configured to cause the array of pixels to display an image frame by performing a series of successive field updates. The series of successive field updates includes a first field update in which a first write pointer circuit tracks a first traversal, during a first update period, across the array of pixels to update the array of pixels from a first to a second image field in the sequence, and a second field update in which a second write pointer circuit tracks a second traversal, during a second update period, across the array of pixels to update the array of pixels from the second to a third image field in the sequence. The second update period of the second field update overlaps the first update period of the first field update.
Methods, systems, and apparatus, including medium-encoded computer program products, for adaptive privacy-preserving information retrieval. An information server can accept from a user a request for privacy sensitive information accessible to the information server. The information server can determine a remaining privacy allocation for the user of the information server and can determine a noise parameter for a response to the request, where application of the noise parameter to the response can decrease a privacy loss associated with the response. The information server can determine a privacy modifier for the response. In response to the information server determining that the remaining privacy allocation satisfies the privacy modifier, the information server can: (i) determining the response to the request; (ii) apply the noise parameter to the response to produce a noised response; (iii) provide the noised response to the user; and (iv) adjust the remaining privacy allocation according to the privacy modifier.
A rotational lens assembly reduces the size of a gap between a lens and a frame of an optical light engine projector assembly. The lens includes a thread structure arranged around the outside edge of the lens. The thread structure allows the lens to align and lock within the optical assembly via at least a partial rotation of the lens. In addition, the rotation of the lens during assembly results in a relatively small gap between the lens and the frame. The smaller gap, in turn allows the other components of the optical assembly to be manufactured with lower tolerances for variation, improving the overall performance of the optical assembly.
Aspects of the present disclosure are directed to a computer-implemented method including receiving, by a user computing device, data that describes a destination for the media content item. Example destinations can include a location of a recipient of message including the media content item and a digital location (e.g., website, social networking page, etc.). The method can include selecting, by a computing system comprising the user computing device, one or more media content items based on the data that describes the destination for the media content item. Media content items that are more relevant and/or appropriate can be selected by considering the destination of the media content item. The selected media content item(s) can be provided for display by the user computing device in a dynamic keyboard interface.
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
G06F 16/435 - Filtering based on additional data, e.g. user or group profiles
G06F 16/487 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
To determine the location of a user, a computing device determines a current location of the user and a destination location. The computing device then determines a plurality of paths for traveling from the current location to the destination location. As the user travels to the destination location, the computing device estimates a plurality of waypoints traversed by the user. The computing device compares the estimated plurality of waypoints to each of the plurality of paths to identify a path of the plurality of paths in which the user travels to the destination location. Then the computing device adjusts the estimated plurality of waypoints according to the identified path to determine precise waypoints for the user.
G01C 21/20 - Instruments for performing navigational calculations
H04W 4/02 - Services making use of location information
H04W 4/33 - Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
An example method includes presenting a user interface facilitating a creation of a video from an image associated with a first media item of a plurality of media items, wherein the first media item comprises the image and a video clip that are captured concurrently, receiving user input via the user interface, wherein the user input comprises a selection of a selectable control element presented in the user interface, and upon receiving the user input, presenting the video clip of the first media item in the user interface, wherein the video clip of the first media item is played in the user interface and comprises video content from before and after the image is captured.
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G11B 27/028 - Electronic editing of analogue information signals, e.g. audio or video signals with computer assistance
A method, performed by a DU of a distributed base station that includes the DU and a CU, of managing time alignment includes transmitting a timing advance command to a UE, starting or restarting a first time alignment timer that indicates validity of a configured grant configuration when the UE is in an RRC connected state with a RAN, and, after starting or restarting the first time alignment timer, determining to transition the UE from the RRC connected state to an RRC inactive state. The method also includes, in response to the determining, (i) transitioning the UE from the RRC connected state to the RRC inactive state by transmitting a first message to the UE, (ii) stopping the first time alignment timer, and (iii) starting or restarting a second time alignment timer that indicates validity of a CG-SDT configuration when the UE is in the RRC inactive state.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for constructing and programming quantum hardware for machine learning processes. A Quantum Statistic Machine (QSM) is described, consisting of three distinct classes of strongly interacting degrees of freedom including visible, hidden and control quantum subspaces or subsystems. The QSM is defined with a programmable non-equilibrium ergodic open quantum Markov chain with a unique attracting steady state in the space of density operators. The solution of an information processing task, such as a statistical inference or optimization task, can be encoded into the quantum statistics of an attracting steady state, where quantum inference is performed by minimizing the energy of a real or fictitious quantum Hamiltonian. The couplings of the QSM between the visible and hidden nodes may be trained to solve hard optimization or inference tasks.
A method includes identifying, by a processing device, a data structure including cells to store data, wherein the cells are arranged within rows and columns of the initial data structure. A scrambled data structure is created in which at least a subset of cells of the initial data structure is rearranged such that each cell of the rearranged subset of cells is located in at least one of a different row or a different column of the initial data structure. Responsive to receiving a user request to access the data of the initial data structure, the processing device determines whether to provide the user with access to the initial data structure or the scrambled data structure.
Generally disclosed herein is a method for synthesizing low-voltage power flow in an electrical distribution system. The method may include connecting a generator to the electrical distribution system. The generator may include a voltage regulator and excitation system. The electrical distribution system may be shorted with a shunt. The output voltage of the generator may be manually set using the voltage regulator. The output current of the generator may be set using the excitation system. The generator may then generate a power flow with the set output voltage and the set output current. The power flow may be supplied to the electrical distribution system.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting a continued conversation are disclosed. In one aspect, a method includes the actions of receiving first audio data of a first utterance. The actions further include obtaining a first transcription of the first utterance. The actions further include receiving second audio data of a second utterance. The actions further include obtaining a second transcription of the second utterance. The actions further include determining whether the second utterance includes a query directed to a query processing system based on analysis of the second transcription and the first transcription or a response to the first query. The actions further include configuring the data routing component to provide the second transcription of the second utterance to the query processing system as a second query or bypass routing the second transcription.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
52.
CODEC-AGNOSTIC ADAPTIVE QUANTIZATION OF IMAGES AND VIDEO USING A PIXEL-BASED PRE- AND POST-PROCESSOR
A method including generating base values and delta values based on an image, generating weighted delta values based on the delta values, generating an enhanced image based on the base values and the weighted delta values, and compressing the enhanced image.
A chip package assembly is disclosed that includes an integrated circuit chip and an optical interconnect system. The optical interconnect system has a first optical transmitter having a plurality of first microLEDs and a first optical receiver having a plurality of light sensors. The first optical transmitter and first optical receiver communicate with a respective second external optical receiver and second external optical transmitter of one or more external chip package assemblies. The external optical transmitter transmits an unmodulated optical light signal to the light sensor indicating whether first microLEDs of the external optical transmitter are in the first “on” state or the first “off” state. The light sensors convert the received and second corresponding unmodulated optical light signal to an electrical signal.
H01L 25/16 - Assemblies consisting of a plurality of individual semiconductor or other solid-state devices the devices being of types provided for in two or more different subclasses of , , , , or , e.g. forming hybrid circuits
G02B 6/43 - Arrangements comprising a plurality of opto-electronic elements and associated optical interconnections
54.
EFFICIENT IMAGE GENERATION USING ARTIFICIAL INTELLIGENCE
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for using artificial intelligence to generate images are described. In one aspect, a method includes obtaining, by an artificial intelligence system and from one or more data sources, information related to one or more digital components for an item. The obtained information can include an identifier for the item and text presented by at least one of the one or more digital components. The artificial intelligence system generates an image generation prompt based on the obtained information. The image generation prompt includes image generation instructions for generating an image based on the extracted information. The artificial intelligence system provides the image generation prompt to an image generation model trained to generate images based on input image generation prompts. The artificial intelligence system generates an updated digital component using an output image output by the image generation model.
Filtering an interpolated reference frame is described. The interpolated reference frame is generated by determining, from a motion field, a motion vector pointing towards a forward reference frame and a motion vector pointing towards a backward reference frame. Expanded prediction blocks, compared to the size of the block of the interpolated reference frame, are determined using the motion vectors and reference frames. The expanded prediction blocks form overlapping areas with adjacent blocks of the interpolated reference frame. The overlapping areas are filtered to mitigate discontinuities.
H04N 19/105 - Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
H04N 19/137 - Motion inside a coding unit, e.g. average field, frame or block difference
H04N 19/159 - Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
H04N 19/176 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
H04N 19/80 - Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
56.
ADAPTIVE MANAGEMENT OF CASTING REQUESTS AND/OR USER INPUTS AT A RECHARGEABLE DEVICE
Implementations set forth herein relate to management of casting requests and user inputs at a rechargeable device, which provides access to an automated assistant and is capable of rendering data that is cast from a separate device. Casting requests can be handled by the rechargeable device despite a device SoC of the rechargeable device operating in a sleep mode. Furthermore, spoken utterances provided by a user for invoking the automated assistant can also be adaptively managed by the rechargeable device in order mitigate idle power consumption by the device SoC. Such spoken utterances can be initially processed by a digital signal processor (DSP), and, based on one or more features (e.g., voice characteristic, conformity to a particular invocation phrase, etc.) of the spoken utterance, the device SoC can be initialized for an amount of time that is selected based on the features of the spoken utterance.
Techniques are described herein for detecting and/or enrolling (or commissioning) new “hot commands” that are useable to cause an automated assistant to perform responsive action(s) without having to be first explicitly invoked. In various implementations, an automated assistant may be transitioned from a limited listening state into a full speech recognition state in response to a trigger event. While in the full speech recognition state, the automated assistant may receive and perform speech recognition processing on a spoken command from a user to generate a textual command. The textual command may be determined to satisfy a frequency threshold in a corpus of textual commands. Consequently, data indicative of the textual command may be enrolled as a hot command. Subsequent utterance of another textual command that is semantically consistent with the textual command may trigger performance of a responsive action by the automated assistant, without requiring explicit invocation.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a network input to generate a network output. In one aspect, one of the systems includes a neural network configured to perform the machine learning task, the neural network including one or more attentive layers that each include a gated attention unit.
The present disclosure provides computer-implemented methods, systems, and devices for efficient bilateral training of users and devices with touch input systems. An interactive object generates, based on a first output of the machine-learned model in response to sensor data associated with a first touch input, first inference data indicating a negative inference corresponding to a first gesture. The interactive object generates, based on an output of the machine-learned model in response to sensor data associated with a second touch input, second inference data indicating a positive inference corresponding to the first gesture. The interactive object, in response to generating the positive inference subsequent to the negative inference, generates training data as a positive training example of the first gesture. The interactive object trains the machine-learned model based at least in part on the training data.
G06F 3/044 - Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A database system comprising an interface and a processor may perform techniques described in this disclosure. The interface may receive a query for accessing a first dataset and a second dataset, where the query identifies multiple dimensions of the first dataset and the second dataset. The first dataset may include a first dimension, and the second dataset may include a second dimension, but excludes the first dimension. The processor may translate the query into a structured query that conforms to a database query language, where the structured query defines a join between the first dataset and the second dataset over the second dimension. The processor may also transmit the structured query to a database, and receive, responsive to the structured query, an indication that a virtual table was created that combines the first dataset and the second dataset over the second dimension of the second dataset.
Aspects of the disclosure are directed to generating label randomizers for training regression models constrained by label differential privacy. The label randomizers can leverage trade-offs between bias and variance based on a privately estimated prior distribution over the labels. The label randomizers can achieve state-of-the-art privacy-utility trade-offs on several datasets, highlighting the importance of reducing bias when training neural networks with label differential privacy.
Methods and devices described in this document provide a power efficient manner of pursuing a non-terrestrial network (NTN) connection. A UE (102) first obtains (614) a terrestrial network (TN) identifier of a TN operating in an area where the UE is currently located. The UE then selectively (615, 616) performs an NTN search (620) depending on whether the UE obtains, based on the TN identifier, an NTN identifier of an NTN to which the UE is able to connect.
An example wireless communication device includes a plurality of multi-layer substrates attached to each other with layers of a first substrate of the plurality of substrates being substantially parallel to layers of a second substrate of the plurality of substrates; and a plurality of antenna arrays that each have planes formed by features of the plurality of substrates, wherein the features of the plurality of substrates that form planes of a first antenna array include a plurality of vias and a plurality of traces arranged in a mesh structure.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for dynamic distance adjustment for stride prefetcher. One of the systems includes a processor; a stride prefetcher; and a cache subsystem, wherein the stride prefetcher is configured to dynamically compute a stride prefetch distance based on a measure of cache miss latency and a duration between requests in a sequence of strided memory accesses issued by the processor.
G06F 12/0862 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches with prefetch
G06F 12/0811 - Multiuser, multiprocessor or multiprocessing cache systems with multilevel cache hierarchies
65.
EFFICIENTLY SERVING MACHINE-LEARNED MODEL COMPUTATIONS WITH HIGH THROUGHPUT AND LOW LATENCY
An example method includes receiving input requests to process a plurality of input sequences using the machine-learned sequence processing model to generate a plurality of output sequences respectively corresponding to the plurality of input sequences; generating a plurality of initial attention tensors respectively for the plurality of input sequences, wherein: one or more respective initial attention tensors are generated for each respective input sequence in parallel over input elements of the respective input sequence; and the one or more respective initial attention tensors are generated in one or more batches having a first batch size using a prefill system that comprises one or more prefill computing devices and executes one or more layers of the machine-learned sequence processing model; and autoregressively generating, using the plurality of initial attention tensors, a plurality of output elements for each of the plurality of output sequences in one or more batches having a second batch size, wherein: the plurality of output elements are generated using a generation system that comprises one or more generation computing devices.
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06N 3/063 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
G06F 3/045 - Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means using resistive elements, e.g. a single continuous surface or two parallel surfaces put in contact
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for software development, customization, and editing; Downloadable application programming interface (API) software; Downloadable software for teaching software development, customization, and editing; Downloadable game software for teaching software development and coding; Downloadable tutorials and guides on software development and coding Providing online non-downloadable software for software development, customization, and editing; Providing online non-downloadable application programming interface (API) software; Providing online non-downloadable software for teaching software development, customization, and editing; Providing online non-downloadable game software for teaching software development and coding; Providing a website and databases featuring software coding examples, plug-ins, and projects; Creating an on-line community for users to participate in discussions about software development and coding
71.
SYSTEMS AND METHODS FOR VULNERABILITY SCANNING OF DEPENDENCIES IN CONTAINERS
A method includes identifying, by a processing device, a set of parameters to generate a container image for a container. The parameters comprise one or more dependencies associated with running the container in a cloud-based environment. A manifest file referencing the one or more dependencies is obtained and the container image is generated based on the set of parameters, wherein the manifest file is stored in a predetermined location associated with the container.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
72.
Efficient Training Mixture Calibration for Training Machine-Learned Models
Systems and methods are provided for efficiently calibrating a data mixture for training machine-learned models (e.g., machine-learned sequence processing models, such as transformer-based models). For example, machine-learned models can be trained over a broad dataset that can include multiple different categories of data. The mixture of data categories within the dataset can influence model performance. To improve the performance of machine-learned models, example implementations of the present disclosure can learn a distribution of data categories using a lightweight proxy model before initiating training of a large primary model. In this manner, for instance, example implementations can obtain an improved training data distribution with less computational expense and can leverage the learned training data distribution to better train a large primary model.
An example method is provided for resuming a communication session encrypted using a post-quantum cipher. The example method can include receiving, by a first computing system, a resumption message from a second computing system. The example method can include decrypting, by the first computing system, the resumption message to obtain a resumption secret, wherein the resumption secret is based on at least a portion of a shared secret that was obtained using a post-quantum cipher during a prior handshake sequence between the first computing system and the second computing system. The example method can include encrypting, by the first computing system, one or more messages using a session key based on the resumption secret. The example method can include sending, by the first computing system, the encrypted one or more messages to the second computing system.
Provided is a malware detection system that provides structure-aware neural networks for performing malware detection. In particular, rather than treat the entire computer file as one large input to a deep neural network, the malware detection system can break the file up based on the internal file structure. Each portion of the computer file can then be processed using individual neural networks and the outputs of these networks can be combined and similarly processed. In this way the overall system can evaluate the file with knowledge of the structure of the file, enabling the malware detection to have a higher-order understanding of the interoperation of different portions of the computer file.
A method, device, and computer-readable storage medium for predicting pronunciation of a text sample, including generating an encoding of allowable pronunciations of the text sample, selecting predicted text samples corresponding to an audio sample, the predicted text samples including the text sample and one or more co-emitted text samples, outputting the text sample, and updating the encoding of allowable pronunciations of the text sample based on pronunciations of the one or more co-emitted text samples.
G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
An example folding device includes a first assembly; a second assembly; a hinge assembly comprising: a first gear defining a first gear axis; a first scoop receiver defining a first scoop axis; and a continuous display spanning the hinge assembly from the first assembly to the second assembly; and first assembly linkage components comprising: a first arm having a. medial end rotatably connected to the hinge assembly about the first gear axis and a lateral end slidably connected to the first assembly; and a first scoop having a. curved medial end that slides within the first scoop receiver about the first scoop axis and a lateral end rotatably connected to the first assembly about a first scoop rotating center.
To activate reception of multicast and/or broadcast services (MBS), a UE operating in an inactive state of a protocol for controlling radio resources receives, in the inactive state from a radio access network (RAN), a message including an MBS session identifier (ID). The UE initiates reception of MBS data corresponding to the MBS session ID in response to the message.
A method for paging a UE is implemented in a distributed unit (DU) of a distributed base station. The method includes receiving, by processing hardware from a central unit (CU) of the distributed base station and when the UE is not operating in a connected state of a protocol associated with controlling radio resources, a CU-to-DU message related to the UE and indicating a voice call; and transmitting, by the processing hardware to the UE via a radio interface, a paging message including an indication of the voice call.
Base stations perform methods for supporting a conditional procedure for a user equipment (UE). A method performed by a first base station may include receiving (1202), by the first base station from a second base station, an indication of one or more candidate secondary cells to which the UE can connect, subject to a condition, to communicate in dual connectivity (DC); receiving (1204), by the first base station, subsequently to the UE connecting to a secondary cell among the one or more candidate secondary cells for which the condition is satisfied, coordination information for the secondary cell, the coordinating information being usable for coordinating usage of radio resources with the second base station while the UE communicates in DC; and applying (1206), by the first base station, the coordination information to coordinate the usage of radio resources with the second base station.
A master node (MN) can implement a method for managing a conditional procedure that involves a user equipment (UE), a candidate secondary node (C-SN), and the MN. The method may include transmitting, to the C-SN, a request to perform the conditional procedure related to the C-SN and the UE, the conditional procedure associated with a condition and a conditional configuration according to which the UE connects to the C-SN when the condition is satisfied; receiving, from the C-SN, a response to the request, the response including an SN-to-MN container; and retrieving the conditional configuration from the SN-to-MN container.
Systems and methods for classification model training can use feature representation neighbors for mitigating label training overfitting. The systems and methods disclosed herein can utilize neighbor consistency regularization for training a classification model with and without noisy labels. The systems and methods can include a combined loss function with both a supervised learning loss and a neighbor consistency regularization loss.
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
A method comprises causing a plurality of qubit calibration procedures to be performed on one or more qubits in accordance with an automatic qubit calibration process. Log data is stored comprising at least: a record identifying one or more calibration procedures that have been performed, and information relating to the result of the respective calibration procedures. Training data is selected from the log data and is received at a learning module operating at one or more computing devices. A supervised learning model is trained at the learning module to select qubit parameters to be calibrated and/or checked.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a network input to generate a network output. In one aspect, one of the systems includes a neural network configured to perform the machine learning task, the neural network including one or more expert neural network blocks that each include router that performs expert-choice routing between multiple expert neural networks.
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for privacy preserving digital component provider. In some implementations, a method includes accessing a buffer including one or more sets of bits; generating a random sequence of values; generating, from the random sequence of values, a sequence of indices representing an order in which to access particular sets of bits of the buffer; in response to determining an index of the sequence of indices corresponds to a location in the buffer, accessing a set of the particular sets of bits of the buffer at the index in the order of the sequence of indices; and performing one or more memory operations on the set of the one or more sets of bits after accessing the set.
The present disclosure provides systems and methods for providing geographic information for software application development. In one example, a computer-implemented method is provided for determining candidate locations for a playability service, which includes obtaining, by one or more computing devices, a plurality of location points and filtering the plurality of location points to obtain a plurality of candidate location points based at least in part on a suitability of each of the location points for use in generating location-based application content. The method further includes generating, by the one or more computing devices, a candidate location dataset based on the plurality of candidate location points. The method further includes receiving, by the one or more computing devices, a request for one or more of the plurality of candidate location points and providing data associated with one or more of the plurality of candidate location points in response to the request.
A63F 13/79 - Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
A63F 13/216 - Input arrangements for video game devices characterised by their sensors, purposes or types using geographical information, e.g. location of the game device or player using GPS
Implementations can detect respective audio data that captures an acoustic event at multiple assistant devices in an ecosystem that includes a plurality of assistant devices, process the respective audio data locally at each of the multiple assistant devices to generate respective measures that are associated with the acoustic event using respective event detection models, process the respective measures to determine whether the detected acoustic event is an actual acoustic event, and cause an action associated with the actional acoustic event to be performed in response to determining that the detected acoustic event is the actual acoustic event. In some implementations, the multiple assistant devices that detected the respective audio data are anticipated to detect the respective audio data that captures the actual acoustic event based on a plurality of historical acoustic events being detected at each of the multiple assistant devices.
G10L 15/01 - Assessment or evaluation of speech recognition systems
G01S 3/80 - Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic, or infrasonic waves
This document describes a system including a printed circuit board oriented along a first plane, the printed circuit board having a device that extends in a direction away from the first plane and is capable of producing a radiated signal or is sensitive to a radiated signal produced by another device. The system includes a component shield with a wall structure and a cover structure, the cover structure connected to the wall structure. A housing structure oriented along a second plane defines a shielded space within which the component shield and the device reside. A shielding layer oriented along a third plane substantially parallel with the second plane is disposed at least partially between the cover structure and the housing structure and configured to attenuate radiated signals. A number of capacitor spot welds affix the shielding layer to the cover structure to improve component shielding.
Systems and techniques directed at an electronic device with a centrally located under-display image sensor are disclosed. The electronic device includes a first image sensor and a second image sensor, the second image sensor being an under-display sensor located at substantially a center of a display of the electronic device. The first image sensor may be located adjacent to an edge of the display. The second image sensor is configured to capture an eye gaze of a user and provide the captured eye gaze to correct the eye gaze of images captured by the first image sensor. The first image sensor may also be an under-display image sensor. During video communications with the electronic device, a user usually looks at the center of the display of the electronic device. The second image sensor is configured to capture the correct eye gaze of the user during video communications.
G06T 5/50 - Image enhancement or restoration using two or more images, e.g. averaging or subtraction
G06T 5/20 - Image enhancement or restoration using local operators
G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
G06T 7/70 - Determining position or orientation of objects or cameras
H04N 23/56 - Cameras or camera modules comprising electronic image sensorsControl thereof provided with illuminating means
H04N 23/90 - Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
H04N 23/95 - Computational photography systems, e.g. light-field imaging systems
H04N 25/40 - Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
H04N 25/532 - Control of the integration time by controlling global shutters in CMOS SSIS
89.
Surfacing Cross-Channel Data for Impression Reporting
Computing systems and methods for surfacing impression data are disclosed herein. The method can include periodically providing a reporting data request to one or more data sources requesting impression data associated with content presented at the data sources. Reporting data is received and processed into a data format usable by the database. The reporting data is then saved in a database. In response to receiving a request from a user to generate a report the reporting data stored in the database is processed using a machine-learned model to generate a model output, and a portion of the reporting data and the model output are output for display to the user.
In some implementations, a language proficiency of a user of a client device is determined by one or more computers. The one or more computers then determines a text segment for output by a text-to-speech module based on the determined language proficiency of the user. After determining the text segment for output, the one or more computers generates audio data including a synthesized utterance of the text segment. The audio data including the synthesized utterance of the text segment is then provided to the client device for output.
G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
91.
WORKLOAD SCHEDULING USING QUEUES WITH DIFFERENT PRIORITIES
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scheduling workloads on computing resources using a high priority queue and a low priority queue. The high priority queue maintains pending high priority workloads to be scheduled for execution, and the low priority queue maintains pending low priority workloads to be scheduled for execution. The computing system as described in this specification schedules the pending low priority workloads for execution by utilizing computing resources provided by the system only when the high priority queue is empty.
To detect a change in lane marker geometry, a computing device receives map patch data from one or more vehicles within a geographic area indicative of measured lane marker positions. For each data point within the map patch data, the computing device determines an error metric based on one or more differences between one or more measured lane marker positions for the data point and one or more reference lane marker positions from a database. The computing device identifies relationships between the data points according to the error metric for each data point, a time when each data point was collected, or a location of each data point, and identifies a lane marker change event occurring within the geographic area based on the relationships between the data points. Then the computing device discards reference lane marker positions from the database corresponding to the lane marker change event.
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
Implementations are directed to simulating automated telephone call(s) to be performed by an automated assistant. Processor(s) can receive user input and determine, based on the user input, that the user input includes: a request to cause the automated assistant to initiate an automated telephone call with an entity, and a task to be performed during the automated telephone call. In some implementations, the processor(s) can cause a simulation of the automated telephone call to be performed to simulate the task, and, based on a result of the simulation, determine whether to initiate the automated telephone call or to refrain from initiating the automated telephone call. In additional or alternative implementations, the processor(s) can determine whether to cause the simulation of the automated telephone call to be performed based on a type of the entity, a type of the task, and/or whether a prior simulation of the task has been performed.
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
Machine-learning systems for meta-reinforcement learning (Meta-RL) can include a transformer-based hypernetwork to generate policy parameters in an episodic fashion. An initial policy can be executed in a computing environment over an initial exploration episode during which the computing environment generates episode data. The episode data can be provided as an input to the hypertransformer network which generates an improved policy which is executed in the computing environment to generate episode data. This process is repeated over a predetermined number of episodes. A cumulative reward associated with execution of the policy for a final policy is optimized. The final policy can be optimized for both exploration and exploitation associated with a particular task. The final policy can include a machine-learned model and/or weights for a machine-learned model.
Text independent speaker recognition models can be utilized by an automated assistant to verify a particular user spoke a spoken utterance and/or to identify the user who spoke a spoken utterance. Implementations can include automatically updating a speaker embedding for a particular user based on previous utterances by the particular user. Additionally or alternatively, implementations can include verifying a particular user spoke a spoken utterance using output generated by both a text independent speaker recognition model as well as a text dependent speaker recognition model. Furthermore, implementations can additionally or alternatively include prefetching content for several users associated with a spoken utterance prior to determining which user spoke the spoken utterance.
Methods, systems, and apparatus, including medium-encoded computer program products, for secure workflows that enhance data security are described. In one aspect, a method includes receiving, by a secure distribution system and from a client device, a digital component request comprising a set of data, in response to receiving the digital component request a customization orchestrator of the secure distribution system identifies a multi-stage workflow for selecting a digital component from candidate digital components of a given content platform based on the set of data. The multi-stage workflow includes a sequence of customization modules that are communicatively coupled to one another by a common data bus. Each customization module includes a set of worklets that include one or more customized worklets provided by the given content platform and one or more standard worklets used in customization modules of multiple content platforms.
Methods, systems (200), and media comprising; a memory controller configured to control writes to a memory, wherein the memory controller is configured to issue fixed writes to the memory either with or without a data clock being enabled, wherein the memory controller is configured to perform operations comprising: receiving write commands comprising regular write commands and fixed write commands; batching (202, WRX=1) the fixed write commands until one or more fixed write batching criteria is satisfied; disabling the data clock; and issuing a batch comprising a plurality of fixed writes corresponding to the fixed write commands.
A machine-learned system includes a first sequence processing model configured to leverage a second sequence processing model to assist in task learning associated with a user query. The user query can be provided as input to the first sequence processing model and the system can obtain, as output of the model, a sequence processing query seeking information for performing a task associated with the user query. The system can transmit the sequence processing query to a computing system storing a second sequence processing model and obtain an output of the second sequence processing model. The system can provide the output of the second sequence processing model as input to the first sequence processing model and generate one or more responses to the user query based at least in part on an output of the first sequence processing model in response to the output of the second sequence processing model.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selective video enhancements on multiple layers of video data. One of the methods includes receiving a plurality of layers of data generated from source data, the plurality of layers comprising one or more layers of video data in a first video format. An output in a second video format is generated, including using a plurality of blending modules to blend the plurality of layers of data in a sequence. A modified alpha value is generated for each data block in the output representing a ratio how much video data from the one or more layers of input video data is represented in the block in the output. One or more enhancements are applied to the output, including selecting, for each enhancement, a configuration based on the modified alpha value.
G09G 5/02 - Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed
G09G 5/06 - Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed using colour palettes, e.g. look-up tables
This disclosure provides systems, methods, and apparatuses for an on-demand pilot signal (ODPS) for paging synchronization. A UE (110) can transmit a request (140) to a network entity (120) during an RRC idle or RRC inactive state. The request (140) can include an explicit ODPS request, clock drift information, one or more proposed parameters for the ODPS, or any combination thereof. The network entity transmits an ODPS configuration (150) to the UE to configure the ODPS. The ODPS configuration can indicate an ODPS pilot pattern, quantity of symbols, frequencies, or other information to inform the UE how to receive the ODPS. The network entity transmits the ODPS (170) during a time period preceding a paging indication or wake-up signal (WUS) (180). The UE achieves time and frequency synchronization using the ODPS before receiving the paging indication or WUS.
