Abstract: A foldable device may include a foldable layer and a hinge mechanism. The hinge mechanism may include a hinge cover fixedly coupled to a hinge base. A plurality of rotation pivots may be rotatably coupled to the hinge base and the hinge cover. A housing of a computing device may be coupled to the rotation pivots, such that, as the rotation pivots rotate into the hinge base and hinge cover, the computing device is unfolded, and as the rotation pivots rotate out of the hinge base and hinge cover, the computing device is folded. Rotation of the rotation pivots into and out of the hinge base and hinge cover may be restricted by one or more stopping mechanisms, so as to maintain a foldable display of the computing device within allowable bending limits.

Abstract: This document describes systems and directed at rejecting display leakage light in under-display sensors. In aspects, an ambient light sensor of an electronic device rejects leakage light originating from pixels in a display using a look-up table and an ambient light calculating formula. In implementations, the look-up table is developed based on a variety of operating conditions that the electronic device may experience, including variable refresh rates and display luminosities. The look-up table includes pre-calculated values of a leakage light ratio, for given operating conditions, that can be used to reject leakage light originating from displays by computing the ambient light calculating formula.

Abstract: A method includes obtaining a batch of training samples. For each particular training sample in the batch of training samples, the method includes generating, using a data value estimator model and the particular training sample, a corresponding predicted value of the particular training sample when used to train a machine learning model. The method includes selecting, based on the corresponding predicted values, a subset of the batch of training samples. For each particular training sample in the subset of the batch of training samples, the method includes determining, using the machine learning model and the particular training sample, a corresponding prediction performance measurement. The method includes adjusting one or more estimator parameter values of the data value estimator model based on the corresponding prediction performance measurements.

Abstract: In some implementations, a method of generating a constraint-based adaptive graphical user interface (GUI) from a static GUI design includes, obtaining a static GUI that includes a plurality of views, identifying a root view and a child view of the static GUI, applying one or more constraints to the child view based on a spatial relation of the child view to borders of the root view, determining that the child view is not fully constrained, in response to determining that the child view is not fully constrained, applying one or more additional constraints to the child view based on a spatial distance between the child view and an additional view that is a neighbor of the child view, and generating the constraint-based adaptive GUI in one or more sizes that differ from a size of the static GUI based on the one or more constraints.

Abstract: Techniques are described herein for warm word arbitration between automated assistant devices. A method includes: determining that warm word arbitration is to be initiated between a first assistant device and one or more additional assistant devices, including a second assistant device; broadcasting, by the first assistant device, to the one or more additional assistant devices, an active set of warm words for the first assistant device; for each of the one or more additional assistant devices, receiving, from the additional assistant device, an active set of warm words for the additional assistant device; identifying a matching warm word included in the active set of warm words for the first assistant device and included in the active set of warm words for the second assistant device; and enabling or disabling detection of the matching warm word by the first assistant device, in response to identifying the matching warm word.

Abstract: A backplane for controlling a display is disclosed. The backplane includes a plurality of tiles formed into an array. Each of the plurality of tiles includes a plurality of complementary metal-oxide-semiconductor backplane dies. Edges of the backplane dies that form a perimeter of the array include electrical connections that direct electrical signals to at least one of the CMOS backplane dies. A display assembly is also disclosed wherein the display assembly includes a backplane having an array of tiles. Each tile includes a plurality of electrically coupled CMOS backplane dies, where edges of the tiles that form an outer perimeter of the array include electrical connections directing electrical signals to one or more of the plurality of CMOS backplane dies. The display assembly further includes at least one light emitting diode array electrically coupled with at least one tile.

Abstract: Analyzing or debugging applications is provided. The system identifies an action for an application provided by a developer. The system determines a first classification score based on historical execution of the action. The system generates a machine generated action for the application based on metadata associated with the application. The system determines a second classification score based on a comparison of the action with the machine generated action. The system selects, via a matching program, a second application that matches the application. The system determines a third classification score based on a comparison of an action approved for the second application with the action provided by the application developer. The system updates a delivery control parameter based on the first classification score, the second classification score and the third classification score. The system controls delivery of the application based on the delivery control parameter.

Abstract: A method for performing speech recognition using sequence-to-sequence models includes receiving audio data for an utterance and providing features indicative of acoustic characteristics of the utterance as input to an encoder. The method also includes processing an output of the encoder using an attender to generate a context vector, generating speech recognition scores using the context vector and a decoder trained using a training process, and generating a transcription for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.

Abstract: Example embodiments of the present disclosure provide, in one example aspect, an example computer-implemented method for verification of a shared cache. The example method can include retrieving a precompiled shared cache entry corresponding to a shared cache key, the shared cache key being associated with an operation request. The example method can include obtaining a directly compiled resource associated with the operation request. The example method can include certifying one or more portions of the shared cache based at least in part on a comparison of the precompiled shared cache entry and the directly compiled resource.

Abstract: Systems and methods of the present technical solution enable a multi-modal interface for voice-based devices, such as digital assistants. The solution can enable a user to interact with video and other content through a touch interface and through voice commands. In addition to inputs such as stop and play, the present solution can also automatically generate annotations for displayed video files. From the annotations, the solution can identify one or more break points that are associated with different scenes, video portions, or how-to steps in the video. The digital assistant can receive input audio signal and parse the input audio signal to identify semantic entities within the input audio signal. The digital assistant can map the identified semantic entities to the annotations to select a portion of the video that corresponds to the users request in the input audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting intermediate reinforcement learning goals. One of the methods includes obtaining a plurality of demonstration sequences, each of the demonstration sequences being a sequence of images of an environment while a respective instance of a reinforcement learning task is being performed; for each demonstration sequence, processing each image in the demonstration sequence through an image processing neural network to determine feature values for a respective set of features for the image; determining, from the demonstration sequences, a partitioning of the reinforcement learning task into a plurality of subtasks, wherein each image in each demonstration sequence is assigned to a respective subtask of the plurality of subtasks; and determining, from the feature values for the images in the demonstration sequences, a respective set of discriminative features for each of the plurality of subtasks.

Abstract: A client device of a game streaming system generates an overlay that identifies discontinuities and other changes in features between streamed frames. The client device receives a stream of frames, representing game content for display, from a server via a network. The client device analyzes the received frames to identify discontinuities and other changes in features of the plurality of frames, such as a particular feature changing one or more of position, size, texture, or other visual characteristic between successively received frames. The client device generates the overlay to indicate the identified features and displays the overlay with at least one of the received frames.

Abstract: Methods and apparatus related to generating a model for an object encountered by a robot in its environment, where the object is one that the robot is unable to recognize utilizing existing models associated with the robot. The model is generated based on vision sensor data that captures the object from multiple vantages and that is captured by a vision sensor associated with the robot, such as a vision sensor coupled to the robot. The model may be provided for use by the robot in detecting the object and/or for use in estimating the pose of the object.

Abstract: Methods, systems, and apparatus, for generated labeled training examples for machine learning. In one aspect, a method includes receiving sets of audio recordings by a user device. For each set of audio recordings, each audio recording in the set is recorded over a respective separate microphone in the user device during a particular time interval, and each particular time interval is different for each set of audio recordings. For each set of audio recordings, a detector determines whether an audio recording in the set of audio recordings includes a particular audio feature, and whether another one of the audio recordings does not include the particular audio feature. For each set of audio recordings determined to include an audio recording that includes the particular audio feature and to include another audio recording that does not include the particular audio feature, a labeled training example is generated.

Abstract: Methods, systems, and apparatus for receiving a command for controlling a robot, the command referencing an object, receiving sensor data for a portion of an environment of the robot, identifying, from the sensor data, a gesture of a human that indicates a spatial region located outside of the portion of the environment described by the sensor data, searching map data for the object, determining, based at least on searching the map data for the object referenced in the command, that the object referenced in the command is present in the spatial region, and in response to determining that the object referenced in the command is present in the spatial region, controlling the robot to perform an action with respect to the object referenced in the command.

Abstract: Methods, systems, and computer media provide attestation tokens that protect the integrity of communications transmitted from client devices, while at the same time avoiding the use of stable device identifiers that could be used to track client devices or their users. In one approach, client devices can receive batches of N device integrity elements from a device integrity computing system, each corresponding to a different public key. The N device elements can be signed by a device integrity computing system. The signing by the device integrity computing system can be signing with a blind signature scheme. Client devices can include throttlers imposing limits on the quantity of attestation tokens created by the client device.

Abstract: Systems and methods are provided for a personalized entity repository. For example, a computing device comprises a personalized entity repository having fixed sets of entities from an entity repository stored at a server, a processor, and memory storing instructions that cause the computing device to identify fixed sets of entities that are relevant to a user based on context associated with the computing device, rank the fixed sets by relevancy, and update the personalized entity repository using selected sets determined based on the rank and on set usage parameters applicable to the user. In another example, a method includes generating fixed sets of entities from an entity repository, including location-based sets and topic-based sets, and providing a subset of the fixed sets to a client, the client requesting the subset based on the client's location and on items identified in content generated for display on the client.

Abstract: A head-wearable display device is configured to support a plurality of combiners (e.g., at least two combiners) to expand an eyebox associated with the head-wearable display device. The plurality of combiners may expand the pupil and the head-wearable display device may be configured to align the magnification between the plurality of combiners, such that a single magnified virtual image with an expanded eyebox may be delivered to the user.