Abstract: The present disclosure is directed to positioning animated images within a dynamic keyboard interface. In particular, the methods and systems of the present disclosure can: receive, from a user device on which an application is executed, data indicating a context of: the application, and/or a dynamic keyboard interface provided in association with the application; identify, based at least in part on the data indicating the context, a plurality of different animated images, including an animated image comprising an advertisement, for presentation by the dynamic keyboard interface; communicate, to the user device, data indicating the plurality of different animated images; receive, from the user device, data indicating a selection of the animated image comprising the advertisement; and determine, based at least in part on the data indicating the selection and the data indicating the context, a position within the dynamic keyboard interface for presenting the animated image comprising the advertisement.

Abstract: A system for using mobile data to improve weather information is provided. The system includes a weather prediction station configured to receive stationary observation data provided by a plurality of stationary weather stations along with data from a plurality of input weather models and generate unified weather model estimates based on the stationary observation data, the input weather model data, and a processor. The processor is configured to aggregate mobile observation data provided by a plurality of non-stationary sensors and use the aggregated mobile observation data to adjust the weather model estimates.

Abstract: 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.

Abstract: 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.

Abstract: An electronic device may include a power management subsystem that soft-starts freshly charged batteries upon connection. The device may be configured to operate on power from a number of batteries less than the greatest number of batteries that may be concurrently connected. Because the soft-start reduces current inrush upon connection of a fresh battery, the device may continue operating as fresh batteries are connected and depleted batteries are disconnected.

Abstract: Some implementations relate to performing speech biasing, NLU biasing, and/or other biasing based on historical assistant interaction(s). It can be determined, for one or more given historical interactions of a given user, whether to affect future biasing for (1) the given user account, (2) additional user account(s), and/or (3) the shared assistant device as a whole. Some implementations disclosed herein additionally and/or alternatively relate to: determining, based on utterance(s) of a given user to a shared assistant device, an association of first data and second data; storing the association as accessible to a given user account of the given user; and determining whether to store the association as also accessible by additional user account(s) and/or the shared assistant device.

Abstract: Systems and methods for measuring quantum states of qubits with more than two levels are provided. A method can include, for a plurality of shuffling sequences, applying, by a quantum computer, one or more quantum gates to the one or more qubits to execute a quantum algorithm; applying, by the quantum computer, a shuffling sequence to the one or more qubits; and measuring, using a readout apparatus, the state of the one or more qubits to determine a readout state. The method can further include determining, by a classical computer or the quantum computer, an average occupation for one or more of the quantum states of the one or more qubits using the readout states for each of the shuffling sequences. The readout states can correspond to a state in a subset of the quantum states of the one or more qubits.

Abstract: 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.

Abstract: A graphics pipeline cache reconstruction operation is implemented to reconstruct one or more graphics pipeline caches for a current client gaming session based on one or more pipeline structures. The pipeline structures each represent a graphical object rendered during a respective previous client gaming session and are used to reconstruct one or more graphics pipeline caches that include graphics pipeline cache objects related to the graphical objects of the pipeline structures. These graphics pipeline cache objects are used to initialize one or more graphics pipelines used to render the graphical objects in a gaming application for a current client gaming session.

Abstract: A computing system and method that can be used for organizing product-related emails, wherein product-related emails can pertain to products such as objects/items or otherwise pertain to entities such as experiences, subscriptions, services etc. In particular, example aspects of the present disclosure involve computing systems and computer-implemented methods for organizing product-related emails based on historical user data and characteristics extracted from the product-related emails. The systems and methods of the present disclosure allow for use of email that more conveniently conveys pertinent information contained in product-related emails through presentation of various information predicted as more valuable to a user and methods to more easily find product-related emails associated with a user's particular desires.

Abstract: An enhanced LBT procedure (200) mitigates unnecessary delays in delivering transmissions between User Equipment and base stations over unlicensed spectrum. A UE or base station selects a particular CAPC corresponding to an intended transmission (225) based on an intelligent mapping of different types of transmission payload (e.g., transmission payload other than or in in addition to pre-defined, QoS-related UP message data payload) to different CAPCs. Most (if not all) of the mapped CAPCs corresponding to the different types of transmission payload are of a higher priority than a lowest priority CAPC (212-222), resulting in channel access procedures that are more commensurate with respective transmission payloads.

Abstract: Implementations relate to effectively localizing system responses, that include dynamic information, to target language(s), such that the system responses are grammatical and/or natural in the target language(s). Some of those implementations relate to various techniques for resource efficient generation of templates for a target language. Some versions of those implementations relate to resource efficient generation of target language natural language generation (NLG) templates and, more particularly, to techniques that enable a human user to generate a target language NLG template more efficiently and/or with greater accuracy. The more efficient target language NLG template generation enables less utilization of various client device resources and/or can mitigate the risk of flawed NLG templates being provided for live use in one or more systems.

Abstract: Implementations are directed to biasing speaker authentication on a per-user basis and on a device-by-device basis and/or contextual feature(s) basis. In some of those implementations, in performing speaker authentication based on a spoken utterance, different biasing parameters are determined for each of multiple different registered users of an assistant device at which the spoken utterance was detected. In those implementations, each of the biasing parameters can be used to make it more likely or less likely (in dependence of the biasing parameter) that a corresponding registered user will be verified using the speaker authentication. Through utilization of biasing parameter(s) in performing speaker authentication, accuracy and/or robustness of speaker authentication can be increased.

Abstract: Implementations are described herein for adapting existing source code snippets to new contexts. In various implementations, a command may be detected to incorporate an existing source code snippet into destination source code. An embedding may be generated based on the existing source code snippet, e.g., by processing the existing source code snippet using an encoder. The destination source code may be processed to identify one or more decoder constraints. Subject to the one or more decoder constraints, the embedding may be processed using a decoder to generate a new version of the existing source code snippet that is adapted to the destination source code.

Abstract: Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, based on content of an existing human-to-computer dialog session between a user and an automated assistant, an entity mentioned by the user or automated assistant may be identified. Fact(s)s related to the entity or to another entity that is related to the entity may be identified based on entity data contained in database(s). For each of the fact(s), a corresponding measure of potential interest to the user may be determined. Unsolicited natural language content may then be generated that includes one or more of the facts selected based on the corresponding measure(s) of potential interest. The automated assistant may then incorporate the unsolicited content into the existing human-to-computer dialog session or a subsequent human-to-computer dialog session.

Abstract: Processor(s) of a client device can: receive audio data that captures a spoken utterance of a user of the client device; process, using an on-device speech recognition model, the audio data to generate a predicted textual segment that is a prediction of the spoken utterance; cause at least part of the predicted textual segment to be rendered (e.g., visually and/or audibly); receive further user interface input that is a correction of the predicted textual segment to an alternate textual segment; and generate a gradient based on comparing at least part of the predicted output to ground truth output that corresponds to the alternate textual segment. The gradient is used, by processor(s) of the client device, to update weights of the on-device speech recognition model and/or is transmitted to a remote system for use in remote updating of global weights of a global speech recognition model.

Abstract: A computing system (100) that includes at least one microapp (202) and a container application (204) configured to receive an application output from the microapp(s) (202,602) via an application programming interface. The computing system (100) can include at least one processor (112,132) and at least one tangible, non-transitory computer-readable medium that stores instructions that, when executed by the at least one processor (112,132), cause the at least one processor (112,132) to perform operations. The operations can include providing, for display within a first panel (304) in a user interface (306), a navigation bar (302) based on data received from the container application (204); receiving, at the container application (204), the application output from the at least one microapp (202) via the application programming interface; and providing, for display within a second panel in the user interface (306), data describing the application output.

Abstract: Processing stacked data structures is provided. A system receives an input audio signal detected by a sensor of a local computing device, identifies an acoustic signature, and identifies an account corresponding to the signature. The system establishes a session and a profile stack data structure including a first profile layer having policies configured by a third-party device. The system pushes, to the profile stack data structure, a second profile layer retrieved from the account. The system parses the input audio signal to identify a request and a trigger keyword. The system generates, based on the trigger keyword and the second profile layer, a first action data structure compatible with the first profile layer. The system provides the first action data structure for execution. The system disassembles the profile stack data structure to remove the first profile layer or the second profile layer from the profile stack data structure.

Abstract: Systems and methods for fast merging of panelist activity are disclosed. The system can maintain a plurality of panelist identifiers each stored with a respective plurality of offline content events, and identify, from the plurality of panelist identifiers, a subset of panelist identifiers that are stored with a respective offline content event that matches a target offline content event. The system can map each of the subset to a respective plurality of unique identifiers corresponding to virtual devices having virtual device attributes. The system can reduce, for each of the subset, the respective plurality of unique identifiers to a sketch that represents the respective plurality of unique identifiers. The system can combine the sketch of each of the subset of panelist identifiers into an aggregated sketch, and transmit the aggregated sketch to a computing device for analysis with an aggregated sketch representing online content events.

Abstract: Systems, apparatuses, and methods for capturing voice messages are provided. In one embodiment, a method can include receiving, by one or more processors of a mobile user device, a user input indicative of a voice message at a first time. The method can further include identifying contextual data indicative of one or more computing devices within proximity of the mobile user device. The method can include providing a set of data for storage in one or more memory devices of the mobile user device. The set of data can indicate the voice message and the contextual data indicative of the computing devices. The method can further include providing an output indicative of the voice message and the contextual data to one or more secure computing devices at a second time.