Abstract: Methods, systems, and apparatus for designing a quantum control trajectory for implementing a quantum gate using quantum hardware. In one aspect, a method includes the actions of representing the quantum gate as a sequence of control actions and applying a reinforcement learning model to iteratively adjust each control action in the sequence of control actions to determine a quantum control trajectory that implements the quantum gate and reduces leakage, infidelity and total runtime of the quantum gate to improve its robustness of performance against control noise during the iterative adjustments.

Abstract: In one general aspect, a computing device includes a hardware processor, a memory, a first housing portion including a touch screen display, and a second housing portion coupled to the first housing portion by a hinge, where the second housing portion includes a rotatable keyboard.

Abstract: The disclosure provides technology for importing a set of media items from a content source by optically analyzing a graphical interface of the content source. An example method includes initiating, by a processing device, an import of a set of media items from a content source; capturing image content of a graphical interface of the content source; extracting data from the image content of the graphical interface; identifying a media item of the content source based on the data from the image content; and storing a reference to the media item.

Abstract: Various arrangements for using captured voice to generate a custom interface controller are presented. A vocal recording from a user may be captured in which a spoken command and multiple smart-home devices are indicated. One or more common functions that map to the multiple smart-home devices may be determined. A custom interface controller may be generated that controls the one or more common functions of each smart-home device of the multiple smart-home devices.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.

Abstract: This document describes a three-party cryptographic handshake protocol in a wireless network in which a sighter receives, from a beacon, a packet including an exponentiation of a random value and a proxy value and generates an end-to-end encrypted ephemeral identifier (E2EE-EID) from the exponentiation of the random value and the proxy value. The sighter generates a message for an owner, selects a private key, and computes an exchanged key using the private key and the E2EE-EID. The sighter extracts a common symmetric key from the exchanged key, encrypts the message using the common symmetric key, and transmits the encrypted message to the owner.

Abstract: This disclosure describes methods, apparatuses, and techniques for capturing a fingerprint image using an electronic device with an under-display fingerprint sensor (UDFPS) embedded under a display screen of a display system. The display system utilizes a pulse-width modulation circuit to generate a pulse-width modulated (PWM) signal to control light emitted by the display screen. As the display screen illuminates a user's touch, the UDFPS captures light reflected off the user's touch, therefore, capturing the fingerprint image. The captured fingerprint image, however, includes a PWM noise. The electronic device uses a noise-filtering algorithm to filter out and/or reduce the PWM noise in the captured fingerprint image. In one aspect, the noise-filtering algorithm estimates and/or determines the PWM noise in the captured fingerprint image. The noise-filtering algorithm then reduces, extracts, and/or filters out the PWM noise from the captured fingerprint image.

Abstract: An application on a viewer client device receives a user input to access a live stream, sends a request to access the live stream, presents information allowing a user to indicate a first anchor of a plurality of anchors of the live stream, the first anchor corresponding to a timestamp for starting a portion of the live stream, receives the live stream and data indicating the timestamp corresponding to the first anchor of the live stream, and displays the live stream beginning at the timestamp corresponding to the first anchor of the live stream.

Abstract: Methods, systems, and apparatus, including computer-readable media, are described for interleaving memory requests to accelerate memory accesses at a hardware circuit configured to implement a neural network model. A system generates multiple requests that are processed against a memory of the system. Each request is used to retrieve data from the memory. For each request, the system generates multiple sub-requests based on a respective size of the data to be retrieved using the request. The system generates a sequence of interleaved sub-requests that includes respective sub-requests of a first request interleaved among respective sub-requests of a second request. Based on the sequence of interleaved sub-requests, a module of the system receives respective portions of data accessed from different address locations of the memory. The system processes each of the respective portions of data to generate a neural network inference using the neural network model implemented at the hardware circuit.

Abstract: Techniques and apparatuses are described for enabling base station-user equipment messaging regarding deep neural networks. A network entity (base station 121, core network server 320) determines a neural network formation configuration (architecture and/or parameter configurations 1208) for a deep neural network (deep neural network(s) 604, 608, 612, 616) for processing communications transmitted over the wireless communication system. The network entity (base station 121, core network server 302) communicates the neural network formation configuration to a user equipment (UE 110). The user equipment (UE 110) configures a first neural network (deep neural network(s) 608, 612) based on the neural network formation configuration. In implementations, the user equipment (UE 110) recovers information communicated over the wireless network using the first neural network (deep neural network(s) 608, 612).

Abstract: Systems and methods for content storage and retrieval are disclosed herein for accessing portions of a file at a client device. A client device receives a request to access a file at the client device. The file includes file portions that are stored at a web-based storage system in communication with the client device via a network. The client device provides the web-based storage system with access to a metafile stored on the client device. The metafile includes an identifier for each of the file portions for the file and an indication of whether each of the file portions are already stored on the client device. In response to the web-based storage system accessing the metafile stored on the client device to identify a set of file portions that is not stored on the client device, the client device receives the identified set of file portions from the web-based storage system via the network.

Abstract: Systems and methods for optimizing videos are disclosed. A method of the present disclosure includes analyzing a video using a plurality of rules to determine one or more optimizations for the video, the one or more optimizations reflecting a subset of properties to improve viewership statistics of the video by automatically modifying characteristics of the video based on the subset of properties that is indicative of improved viewership statistics pertaining to a plurality of users of a media hosting service, wherein the characteristics comprise at least one characteristic, which when automatically modified, results in a change to the video that correlates to improved viewership statistics pertaining to the plurality of users. The method further includes causing the characteristics of the video to be modified to implement the one or more optimizations, and causing the video with the modified characteristics to be presented to at least a subset of the plurality of users.

Abstract: A device for generating a qubit control signal includes: a first signal envelope generator circuit including a first multiple of signal sources, in which an output of each signal source of the first multiple of signal sources is combined to provide a first cumulative output; and a first mixer circuit coupled to the first signal envelope generator circuit, in which the first cumulative output is coupled to a first input of the first mixer circuit, and an output of the first mixer circuit includes a first qubit control signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural network compression. In one aspect, a method comprises receiving a neural network and identifying a particular set of multiple weights of the neural network. Multiple anchor points are determined based on current values of the particular set of weights of the neural network. The neural network is trained by, at each of multiple training iterations, performing operations comprising adjusting the values of the particular set of weights by backpropagating gradients of a loss function. The loss function comprises a first loss function term based on a prediction accuracy of the neural network and a second loss function term based on a similarity of the current values of the particular set of weights to the anchor points. After training, the values of the particular set of weights are quantized based on the anchor points.

Abstract: A method includes receiving a point data anomaly detection query from a user. The query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. The method includes training a model using the set of point data values. For at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. Based on the variance value satisfying the threshold value, the method includes determining that the respective point data value is an anomalous point data value. The method includes reporting the determined anomalous point data value to the user.

Abstract: A method can include determining that a measured distance, of an object in contact with a touchscreen, from a sensor included in the touchscreen, is less than or equal to a first distance and equal to or greater than a second distance, based on determining that the measured distance of the object from the sensor is less than or equal to the first distance and equal to or greater than the second distance, providing haptic feedback as a function of the measured distance, the haptic feedback being greater for smaller measured distances; determining that the measured distance is less than the second distance; and in response to determining that the measured distance is less than the second distance, decreasing the haptic feedback.

Abstract: Operations of a method include receiving a configuration request requesting configuration management of a base configuration package that describes infrastructure of an application. The operations include determining, for the base configuration package, a plurality of package functions. Each package function of the plurality of package functions extends functionality of the base configuration package. The operations include determining, for the base configuration package and the plurality of package functions, a change-proposal function. The change-proposal function proposes one or more of the plurality of package functions to extend the functionality of the base configuration package. The operations include transmitting, to a user device, the change-proposal function and receiving, from the user device, approval of the change-proposal function.

Abstract: A method for training a speech recognition model includes receiving a set of training utterance pairs each including a non-synthetic speech representation and a synthetic speech representation of a same corresponding utterance. At each of a plurality of output steps for each training utterance pair in the set of training utterance pairs, the method also includes determining a consistent loss term for the corresponding training utterance pair based on a first probability distribution over possible non-synthetic speech recognition hypotheses generated for the corresponding non-synthetic speech representation and a second probability distribution over possible synthetic speech recognition hypotheses generated for the corresponding synthetic speech representation. The first and second probability distributions are generated for output by the speech recognition model.

Abstract: Methods, apparatus, and computer readable media related to receiving textual input of a user during a dialog between the user and an automated assistant (and optionally one or more additional users), and generating responsive reply content based on the textual input and based on user state information. The reply content is provided for inclusion in the dialog. In some implementations, the reply content is provided as a reply, by the automated assistant, to the user's textual input and may optionally be automatically incorporated in the dialog between the user and the automated assistant. In some implementations, the reply content is suggested by the automated assistant for inclusion in the dialog and is only included in the dialog in response to further user interface input.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting errors in a client device and its associated applications while preserving the privacy of the user of the device. Methods can include obtaining and blinding contextual application data for an application on a device. Data regarding the application's digital certificate and device trustworthiness data are obtained and provided to a trust assessment server along with the blinded data. This server can provide indications that the device is trustworthy and the application is authentic, and can digitally sign the blinded data. The digital signature can be validated and the unblinded contextual application data can be obtained. If the unblinded data matches the contextual application data, the application can provide the digital signature, the indications, and the unblinded contextual application data to an error detection server, which in turn can indicate the application does not have errors.