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, 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.

Abstract: An IC chip can provide silicon root of trust (RoT) functionality. In described implementations, the IC chip includes a processor, an alert handler, and multiple peripheral devices, which generate alert indications. The alert handler processes the alert indications, which have security implications. The alert handler includes multiple alert receiver modules to communicate with the multiple peripheral devices. The alert handler also includes a controller, multiple accumulation units, multiple escalation timers, and multiple escalation sender modules. These components can be organized into a hierarchy of increasing escalation severity. In operation, the controller classifies an alert and flexibly implements an adaptable alert handler path that is established through the escalation components responsive to the classification and based on a source of the alert. A path can conclude with an escalation sender module commanding an escalation handler to implement a security countermeasure.

Abstract: Optical systems may include MEMS mirrors having elliptical mirror plates. A laser scanning system may include a MEMS mirror that scans an incident light beam along a single scanning axis. The MEMS mirror may include an elliptical mirror plate having a semi-major axis that is aligned parallel or perpendicular to the rotational axis of the elliptical mirror plate. The incident light beam may have an elliptical cross-section, such that the incident light beam completely or substantially overlaps the reflecting surface of the elliptical mirror plate. After being reflected by the elliptical mirror plate, the light beam may be circularized via one or more shaping lenses disposed in the optical path of the reflected light beam, prior to projection of the light beam.

Abstract: Implementations set forth herein relate to an automated assistant that can be invoked while a user is interfacing with a foreground application in order to retrieve data from one or more different applications, and then provide the retrieved data to the foreground application. A user can invoke the automated assistant while operating the foreground application by providing a spoken utterance, and the automated assistant can select one or more other applications to query based on content of the spoken utterance. Application data collected by the automated assistant from the one or more other applications can then be used to provide an input to the foreground application. In this way, the user can bypass switching between applications in the foreground in order to retrieve data that has been generated by other applications.

Abstract: In one example, a method includes receiving, by a computing system, context information associated with a computing device; inferring, by the computing system and based on the context information, an action of a user of the computing device, the action associated with at least one entity; determining, by the computing system and based on stored attribute information associated with the at least one entity, and based on a stored set of rules associated with the inferred action, that the inferred action is not advisable; and responsive to determining that the inferred action is not advisable, outputting, by the computing system and for display on the computing device, notification data indicating that the inferred action is not advisable.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a plurality of model representations of predictive models, each model representation associated with a respective user and expresses a respective predictive model, and selecting a model implementation for each of the model representations based on one or more system usage properties associated with the user associated with the corresponding model representation.

Abstract: Systems and methods for identifying related videos based on elements tagged in the videos are presented. In an aspect, a system includes an identification component configured to identify tagged elements in a video, a matching component configured to identify other videos that include one or more of the tagged elements, and a recommendation component configured to recommend the other videos for viewing based on a current or past request to play the video.

Abstract: A computer-implemented method for generating results for a client-requested query involves receiving a query produced by a client communication device, generating a result for the query in response to reception of the query, determining one or more predictive follow-up requests before receiving an actual follow-up request from the client device, and initiating retrieval of information associated with the one or more predictive follow-up requests, and transmitting at least part of the result to the client device, and then transmitting to the client device at least part of the information associated with the one or more predictive follow-up requests.

Abstract: Aspects of the disclosure are directed to methods, systems, and apparatuses using an instruction prefetch pipeline architecture that provides good performance without the complexity of a full cache coherent solution deployed in conventional CPUs. The architecture can include components which can be used to construct an instruction prefetch pipeline, including instruction memory (TiMem), instruction buffer (iBuf), a prefetch unit, and an instruction router.

Abstract: Systems and methods of the present disclosure are directed to a method for machine-learned code segment prediction for optimizing software development. The method includes obtaining an incomplete segment of code. The method includes processing the incomplete segment of code with a machine-learned code prediction model to obtain a sampled set of segment completion predictions that include code that completes the incomplete segment of code. The method includes determining an aggregated segment completion prediction from the sampled set of segment completion predictions. The method includes replacing a portion of the aggregated segment completion prediction with an input field, wherein the portion of the aggregated segment completion prediction is associated with a degree of certainty less than a threshold degree of certainty.

Abstract: Systems and methods of combining digital video are described. A system can receive digital video comprising frames. The system can analyze the frames to identify a subset of consecutive frames that have a static portion defined by a spatial region with matching pixels across two or more frames. The system can tag the digital video with an indication of the subset and a trigger that causes transmission, at a temporal offset during playback prior to the subset, of a request for content used to overwrite the static portion. The system can receive the request from the client device, the request transmitted by the client device based on the temporal offset during playback prior to the subset. The system can select and transmit a content item responsive to the request to cause the client device to render the content item at the static portion of the subset.

Abstract: Implementations disclose comprehensibility-based identification of educational content of multiple content types. A method includes determining respective comprehensibility ranking signals for content items corresponding to a user request, the comprehensibility ranking signals based on learning attribute scores generated for the content items from at least one machine learning model, determining a learning level of a user corresponding to the user request, ranking the content items based on a mapping between the learning level and the respective comprehensibility ranking signals of the content items, and providing a recommendation for the content items according to the ranking of the content items.

Abstract: Implementations are described herein for analyzing existing interactive web sites to facilitate automatic engagement with those web sites, e.g., by automated assistants or via other user interfaces, with minimal effort from the hosts of those websites. For example, in various implementations, techniques described herein may be used to extract, validate, maintain, generalize, extend and/or distribute individual actions and “traces” of actions that are useable to navigate through various interactive websites. Additionally, techniques are described herein for leveraging these actions and/or traces to automate aspects of interaction with a third party website.

Abstract: Methods, apparatus, and computer readable media related to determining that no resources responsive to a query of a user at a first time satisfy one or more criteria (e.g., one or more quality criteria) and, in response to such a determination: providing for presentation to the user at a later time, content that is based on a given resource that is responsive to the query at the later time and that satisfies the criteria. The given resource that is responsive to the query at the later time may be a resource that is in addition to any resources responsive to the query at the first time or may be a refined version of a resource that was responsive to the query at the first time.

Abstract: This disclosure describes systems and techniques directed to using a supplementary uplink (SUL) to mitigate a desensitization condition. The described systems and techniques include a user equipment having a desensitization manager application that directs the user equipment to determine a presence of a desensitization condition. The desensitization manager application further directs the user equipment to transmit, to a base station, a first message that requests the base station to allocate, to the user equipment, a portion of resources used for a supplementary uplink between the user equipment and the base station. After receiving a second a message from the base station that identifies the allocated portion of the resources, the desensitization manager application directs the user equipment perform uplink transmissions using the allocated portion of the resources.

Abstract: The technology relates to factors regarding the external environment around a vehicle that are used to trigger enhanced driving directions for use by the driver. The factors can include issues such as adverse weather conditions, low light conditions and temporary obstacles or other obstructions that may prevent or reduce the ability of the driver to see street signs or other landmarks that are part of an initial set of driving directions. Upon determination of one or more relevant factors, the system is able to modify or otherwise enhances directions in real time. This allows the driver to be able to quickly and easily identify other visible landmarks and use such information to navigate to a desired destination. This approach employs one or more on-board cameras configured to detect objects and conditions in the environment adjacent to or otherwise nearby the vehicle, such as within line of sight of the vehicle's front end.

Abstract: A system and method are provided for sizing and fitting a head mounted wearable computing device for a user based on image data of the head of the user, including a known reference device having a known scale. The system and method may include capturing image data including a face of the user to be fitted for the head mounted wearable computing device. The known reference device having the known scale is compared to features detected in the image data to determine a scaling factor. The scaling factor is used to size, or assign measures to facial features detected in the image data. A three-dimensional model of the head of the user may be generated from the captured image data.

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for route planning are provided. The disclosed technology can include accessing travel data that includes information associated with a starting location and a destination. Routes from the starting location to the destination can be determined and each of the routes can be associated regions. Travel costs associated with travelling from the starting location to the destination via each of the routes can be determined. Convenience costs associated with an availability of facilities within the regions associated with each of routes can also be determined. A travel route can be selected from the routes. The travel route can be selected based in part on the travel costs, the convenience costs, and travel criteria. The travel criteria can be associated with travel preferences. Furthermore, route data that can include information associated indications based in part on the travel route can be generated.

Abstract: Systems, methods and computer program products are provided for managing contactless transactions. A first tap is performed when a system is placed within a predetermined proximity to a payment terminal. A first select command including an AID corresponding to a first application is received from the payment terminal. A first response based on the first select command is transmitted to the payment terminal. A data request including information indicating supported data types is received from the payment terminal. A second response based on the data request and including transaction data is transmitted to the payment terminal. The transaction data includes at least a portion of commerce data stored in the at least one memory.

Abstract: A method at an electronic device with an array of indicator lights includes: obtaining first visual output instructions stored at the electronic device, where the first visual output instructions control operation of the array of indicator lights based on operating state of the electronic device; receiving a voice input; obtaining from a remote system a response to the voice input and second visual output instructions, where the second visual output instructions are provided by the remote system along with the response in accordance with a determination that the voice input satisfies one or more criteria; executing the response; and displaying visual output on the array of indicator lights in accordance with the second visual output instructions, where otherwise in absence of the second visual output instructions the electronic device displays visual output on the array of indicator lights in accordance with the first visual output instructions.

Abstract: Implementations relate to using deep reinforcement learning to train a model that can be utilized, at each of a plurality of time steps, to determine a corresponding robotic action for completing a robotic task. Implementations additionally or alternatively relate to utilization of such a model in controlling a robot. The robotic action determined at a given time step utilizing such a model can be based on: current sensor data associated with the robot for the given time step, and free-form natural language input provided by a user. The free-form natural language input can direct the robot to accomplish a particular task, optionally with reference to one or more intermediary steps for accomplishing the particular task. For example, the free-form natural language input can direct the robot to navigate to a particular landmark, with reference to one or more intermediary landmarks to be encountered in navigating to the particular landmark.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate generating stable real-time textual translations in a target language of an input audio data stream that is recorded in a source language. An audio stream that is recorded in a first language is obtained. A partial transcription of the audio can be generated at each time interval in a plurality of successive time intervals. Each partial transcription can be translated into a second language that is different from the first language. Each translated partial transcription can be input to a model that determines whether a portion of an input translated partial transcription is stable. Based on the input translated partial transcription, the model identifies a portion of the translated partial transcription that is predicted to be stable. This stable portion of the translated partial transcription is provided for display on a user device.

Abstract: Systems and methods of predicting documentation associated with an encounter between attendees are provided. For instance, attendee data indicative of one or more previous visit notes associated with a first attendee can be obtained. The attendee data can be inputted into a machine-learned note prediction model that includes a neural network. The neural network can generate one or more context vectors descriptive of the attendee data. Data indicative of a predicted visit note can be received as output of the machine-learned note prediction model based at least in part on the context vectors. The predicted visit note can include a set of predicted information expected to be included in a subsequently generated visit note associated with the first attendee.

Abstract: An electronic document associated with users of a collaborative document platform is identified. The electronic document is associated with an approval data structure including entries that correspond to approval requests. A portion of an approval data structure is included within the content of the electronic document for presentation to a first user. A first user updates a first entry of the portion of the approval data structure included within the content of the electronic is detected. The update to the first entry corresponds to a first approval request for a second user to approve a portion of the electronic document. A first notification is transmitted to a second client device associated with the second user. The first notification indicates the first approval request. The approval data structure is updated to include data of the first entry.

Abstract: Implementations are described herein for leveraging digital media files retrieved and/or created by users to predict/determine topics of potential relevance to the users. In various implementations, digital media file(s) created and/or retrieved by a user with a client device may be applied as input across trained machine learning model(s), which in some cases are local to the client device, to generate output that indicates object(s) detected in the digital media file(s). Data indicative of the indicated object(s) may be provided to a remote computing system without providing the digital media file(s) themselves. In some implementations, information associated with the indicated object(s) may be retrieved and proactively output to the user. In some implementations, a frequency at which objects occur across a corpus of digital media files may be considered when determining a likelihood that a detected object is potentially relevant to a user.

Abstract: Methods, systems, and apparatus for propagating reduced-precision on computation graphs are described. In one aspect, a method includes receiving data specifying a directed graph that includes operators for a program. The operators include first operators that each represent a numerical operation performed on numerical values having a first level of precision and second operators that each represent a numerical operation performed on numerical values having a second level of precision. One or more downstream operators are identified for a first operator. A determination is made whether each downstream operator represents a numerical operation that is performed on input values having the second level of precision. Whenever each downstream operator represents a numerical operation that is performed on input values having the second level of precision, a precision of numerical values output by the operation represented by the first operator is adjusted to the second level of precision.

Abstract: A non-transitory computer-readable storage medium can include instructions stored thereon that, when executed by at least one processor, are configured to cause a computing device to determine, in response to a change in a refresh rate of a display, an encoded intensity of at least a portion of an image presented by the display, determine that the encoded intensity is within a predetermined range, and based on determining that the encoded intensity is within the predetermined range, adjust an intensity of a signal for the portion of the image.

Abstract: Methods, apparatus, and computer readable media are described for tailoring instructions for configuring a smart device based on feedback received from the smart device and/or based on feedback received from a device that is separate from the smart device. Some implementations additionally or alternatively relate to utilization of data corresponding to previous installations of similar smart devices to tailor provided instructions in order to mitigate the reoccurrence of past issues during configuration of smart devices. Some implementations additionally or alternatively relate to proactively suggesting and/or providing, to a user, guidance related to a smart device in response to determining the smart device is to be configured by the user and/or in response to determining a complete configuration of the smart device has not occurred.

Abstract: Systems and methods for providing audio data, from an initially invoked automated assistant to a subsequently invoked automated assistant. An initially invoked automated assistant may be invoked by a user utterance, followed by audio data that includes a query. The query is provided to a secondary automated assistant for processing. Subsequently, the user can submit a query that is related to the first query. In response, the initially invoked automated assistant provides the query to the secondary automated assistant in lieu of providing the query to other secondary automated assistants based on similarity between the first query and the subsequent query.

Abstract: A method includes collecting user activity data for a first online media item. The user activity data can be data for a user consuming the first online media item. The method further includes segmenting a second online media item into a plurality of segments, and identifying one or more of the plurality of segments with user activity data satisfying one or more criteria. The identified segments comprise a set of frames of the plurality of frames of the second online media item. The method further includes selecting a frame from the set of frames from the second online media item. The method further includes sending a recommendation of the selected frame as a thumbnail recommendation for the second online media item to a client device.

Abstract: Techniques are described herein for detecting and suppressing commands in media that may trigger another automated assistant. A method includes: determining, for each of a plurality of automated assistant devices in an environment that are each executing at least one automated assistant, an active capability of the automated assistant device; initiating playback of digital media by an automated assistant; in response to initiating playback, processing the digital media to identify an audio segment in the digital media that, upon playback, is expected to trigger activation of at least one automated assistant executing on at least one of the plurality of automated assistant devices in the environment, based on the active capability of the at least one of the plurality of automated assistant devices; and in response to identifying the audio segment in the digital media, modifying the digital media to suppress the activation of the at least one automated assistant.

Abstract: Implementations determine log-in information indicating whether a user of a first application is logged into a target application and/or a website of the target application. In response to the log-in information indicating that the user is logged into the target application but not logged into the website of the target application, a first selectable element can be displayed at a user interface of the first application to receive user input that causes the target application to be opened. In response to the log-in information indicating that the user is not logged into the target application but is logged into the website of the target application, a second selectable element can be displayed at the first application to receive user input that leads to the website of the target application, or the first selectable element can be assigned a deeplink that leads to the website of the target application.

Abstract: This document describes techniques and apparatuses for performing listen-before-talk procedures on bandwidth parts. These techniques include a user equipment (UE) initiating a first listen-before-talk (LBT) procedure on an active bandwidth part used in a radio resource control (RRC) connection between a UE and a base station. During the first LBT procedure, the UE receives a configuration message from the base station instructing the UE to change the active bandwidth part from the first bandwidth part to a second bandwidth part. Responsively, the UE changes the active bandwidth part and initiates a second LBT procedure on the second bandwidth part.

Abstract: An autostereoscopic display system includes a transmissive display panel including a backlight having an array of backlight pixels, a selectively-selectively-transmissive display pixel matrix having a first side facing the backlight and an opposing second side, the selectively-transmissive display pixel matrix comprising an array of display pixels, a first lenticular array disposed between the backlight and the first side of the selectively-transmissive display pixel matrix, and a second lenticular array disposed facing the second side of the selectively-transmissive display pixel matrix. The backlight is configured to separately activate different subsets of the backlight pixels such that light emitted from an activated subset of backlight pixels and transmitted through the first lenticular array, the selectively-transmissive display pixel matrix, and the second lenticular array is emitted by the display panel as display light in a corresponding separate direction relative to the display panel.

Abstract: This document describes a light-sealing gasket with crossbar force distribution. The gasket can be used in an electronic device with a sensor package that is capable of transmitting and receiving signals and is positioned behind a display of the device. The gasket provides a shield between the receive signals and the transmit signals, prevents signal crosstalk, and protects the delicate panel layer of the display. Use of this gasket in an electronic device allows manufacturers to add more features to the device and enrich the user experience.

Abstract: A method for residual adapters for few-shot text-to-speech speaker adaptation includes obtaining a text-to-speech (TTS) model configured to convert text into representations of synthetic speech, the TTS model pre-trained on an initial training data set. The method further includes augmenting the TTS model with a stack of residual adapters. The method includes receiving an adaption training data set including one or more spoken utterances spoken by a target speaker, each spoken utterance in the adaptation training data set paired with corresponding input text associated with a transcription of the spoken utterance. The method also includes adapting, using the adaption training data set, the TTS model augmented with the stack of residual adapters to learn how to synthesize speech in a voice of the target speaker by optimizing the stack of residual adapters while parameters of the TTS model are frozen.

Abstract: A method includes obtaining a multi-utterance training sample that includes audio data characterizing utterances spoken by two or more different speakers and obtaining ground-truth speaker change intervals indicating time intervals in the audio data where speaker changes among the two or more different speakers occur. The method also includes processing the audio data to generate a sequence of predicted speaker change tokens using a sequence transduction model. For each corresponding predicted speaker change token, the method includes labeling the corresponding predicted speaker change token as correct when the predicted speaker change token overlaps with one of the ground-truth speaker change intervals. The method also includes determining a precision metric of the sequence transduction model based on a number of the predicted speaker change tokens labeled as correct and a total number of the predicted speaker change tokens in the sequence of predicted speaker change tokens.

Abstract: The present disclosure relates to a streaming speech-to-speech conversion model, where an encoder runs in real time while a user is speaking, then after the speaking stops, a decoder generates output audio in real time. A streaming-based approach produces an acceptable delay with minimal loss in conversion quality when compared to other non-streaming server-based models. A hybrid model approach for combines look-ahead in the encoder and a non-causal stacker with non-causal self-attention.

Abstract: The present disclosure describes techniques and apparatuses that are directed to using memory protection data within a computing device. Techniques include allocating regions of a memory for storing application data and protection data. Techniques also include creating a bitmap having bit values corresponding to memory blocks within the allocated regions. The one or more bit values can be indicative of whether application data and/or protection data are present in a memory block. The techniques and apparatuses can enable memory protection, such as memory security (e.g., encryption) and memory safety (e.g., error correction code (ECC) usage), to be efficiently used while permitting discontiguous memory allocations and without substantial operating system modification.

Abstract: A method for proactive notifications in a voice interface device includes: receiving a first user voice request for an action with an future performance time; assigning the first user voice request to a voice assistant service for performance; subsequent to the receiving, receiving a second user voice request and in response to the second user voice request initiating a conversation with the user; and during the conversation: receiving a notification from the voice assistant service of performance of the action; triggering a first audible announcement to the user to indicate a transition from the conversation and interrupting the conversation; triggering a second audible announcement to the user to indicate performance of the action; and triggering a third audible announcement to the user to indicate a transition back to the conversation and rejoining the conversation.

Abstract: A method includes receiving distillation data including a plurality of out-of-domain training utterances. For each particular out-of-domain training utterance of the distillation data, the method includes generating a corresponding augmented out-of-domain training utterance, and generating, using a teacher ASR model trained on training data corresponding to a target domain, a pseudo-label corresponding to the corresponding augmented out-of-domain training utterance. The method also includes distilling a student ASR model from the teacher ASR model by training the student ASR model using the corresponding augmented out-of-domain training utterances paired with the corresponding pseudo-labels generated by the teacher ASR model.

Abstract: Techniques described herein describe aspects of signal adjustments in user equipment-coordination set, UECS, joint transmissions. A base station analyzes a first joint transmission from multiple user equipments, UEs, participating in a UECS, where the multiple UEs include a coordinating UE of the UECS and at least one non-coordinating UE participating in the UECS. The base station determines that the first joint transmission fails to meet a performance metric and directs the multiple UEs participating in the UECS to add signal adjustments to a second joint transmission.

Abstract: This application is directed to a method for controlling user experience (UX) operations on an electronic device that executes an application. A touchless UX operation associated with the application has an initiation condition including at least detection of a presence and a gesture in a required proximity range with a required confidence level. The electronic device then determines from a first sensor signal the proximity of the presence with respect to the electronic device. In accordance with a determination that the determined proximity is in the required proximity range, the electronic device determines from a second sensor signal a gesture associated with the proximity of the presence and an associated confidence level of the determination of the gesture. In accordance with a determination that the determined gesture and associated confidence level satisfy the initiation condition, the electronic device initializes the touchless UX operation associated with the application.

Abstract: A method includes receiving a sequence of acoustic frames as input to a multilingual automated speech recognition (ASR) model configured to recognize speech in a plurality of different supported languages and generating, by an audio encoder of the multilingual ASR, a higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The method also includes generating, by a language identification (LID) predictor of the multilingual ASR, a language prediction representation for a corresponding higher order feature representation. The method also includes generating, by a decoder of the multilingual ASR, a probability distribution over possible speech recognition results based on the corresponding higher order feature representation, a sequence of non-blank symbols, and a corresponding language prediction representation. The decoder includes monolingual output layer having a plurality of output nodes each sharing a plurality of language-specific wordpiece models.

Abstract: A method for identifying malicious software includes receiving and executing a software application, identifying a plurality of uniform resource identifiers the software application interacts with during execution of the software application, and generating a vector representation for the software application using a feed-forward neural network configured to receive the plurality of uniform resource identifiers as feature inputs. The method also includes determining similarity scores for a pool of training applications, each similarity score associated with a corresponding training application and indicating a level of similarity between the vector representation for the software application and a respective vector representation for the corresponding training application.

Abstract: A method for providing cloud network reachability analysis includes receiving a reachability query requesting a reachability status of a target including a packet header associated with a data packet. The packet header includes a source IP address and a destination IP address. The method also includes generating one or more simulated forwarding paths for the data packet based on the packet header using a data plane model. Each simulated forwarding path includes corresponding network configuration information. The method includes determining the reachability status of the target based on the one or more simulated forwarding paths and providing the determined reachability status and the one or more simulated forwarding paths to a user device associated with the reachability query which causes the user device to present the network configuration information for each simulated forwarding path.

Abstract: A computer-implemented method for using machine learning to handle data in a computing system with improved efficiency can include obtaining a handling request associated with a data item, the handling request instructing the computing system to perform a handling operation with the data item, obtaining a trace log comprising one or more distributed trace items, the one or more distributed trace items including data from each of one or more services interacting with the data item, providing the trace log to a data characteristic prediction model including one or more machine-learned models, receiving, in response to providing the trace log to the data characteristic prediction model, one or more data characteristic predictions associated with the data item, and selecting a handling operation of a plurality of candidate handling operations based at least in part on the one or more data characteristic predictions.