Abstract: A system for collaboratively generating and/or managing a media channel is provided. The system includes an identification component, a generation component and a permissions component. The identification component identifies a first set of media content associated with a first social group and a second set of media content associated with a second social group. The generation component generates a media channel based on the first and second sets of media content identified as being respectively associated with the first and second social groups. The permissions component grants access to the media channel based at least on permissions generated for the first and second sets of media content in connection with the respective first and second social groups.

Abstract: This document describes methods and systems for an antenna system integrated with side-keys of an electronic device. The antenna system enables antenna integration in a metal frame using a metal support structure and fastener(s) to route antenna signals around side-key modules embedded in the frame without encountering or causing interference with the side-key modules. By using these techniques to integrate antennas on areas around the side-key modules, more antennas can be implemented on the electronic device, leading to improved capabilities supporting additional wireless standards and a better user experience in terms of improved communication quality.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting likelihoods of conditions being satisfied using recurrent neural networks. One of the systems is configured to process a temporal sequence comprising a respective input at each of a plurality of time steps and comprises: one or more recurrent neural network layers; one or more logistic regression nodes, wherein each of the logistic regression nodes corresponds to a respective condition from a predetermined set of conditions, and wherein each of the logistic regression nodes is configured to, for each of the plurality of time steps: receive the network internal state for the time step; and process the network internal state for the time step in accordance with current values of a set of parameters of the logistic regression node to generate a future condition score for the corresponding condition for the time step.

Abstract: A method for detecting freeze words includes receiving audio data that corresponds to an utterance spoken by a user and captured by a user device associated with the user. The method also includes processing, using a speech recognizer, the audio data to determine that the utterance includes a query for a digital assistant to perform an operation. The speech recognizer is configured to trigger endpointing of the utterance after a predetermined duration of non-speech in the audio data. Before the predetermined duration of non-speech, the method includes detecting a freeze word in the audio data. In response to detecting the freeze word in the audio data, the method also includes triggering a hard microphone closing event at the user device. The hard microphone closing event prevents the user device from capturing any audio subsequent to the freeze word.

Abstract: This document describes techniques and devices for determining a machine-learning architecture for network slicing. A user equipment (UE) and a network-slice manager communicate with each other to determine a machine-learning (ML) architecture, which the UE then employs to wirelessly communicate data for an application. In particular, the UE selects a machine-learning architecture that provides a quality-of-service level requested by an application. The network-slice manager accepts or rejects the request based on one or more available end-to-end machine-learning architectures associated with a network slice that supports the quality-of-service level requested by the application. By working together, the UE and the network-slice manager can determine an appropriate machine-learning architecture that satisfies a quality-of-service level associated with the application and forms a portion of an end-to-end machine-learning architecture that meets the quality-of-service requested by the application.

Abstract: A location history manager may be configured to determine a location history associated with a user, and a resource usage manager may be configured to determine a computing resource usage history associated with the user. A location monitor may be configured to determine a location of the user. A resource predictor may be configured to generate a prediction of a computing resource, based on the location history, the computing resource usage history, and the location. A resource provider may be configured to provide the computing resource, based on the prediction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining breakpoints in a media item. Methods can include determining a candidate set of breakpoints within a media item. A machine learning model is used to generate a score for each particular candidate breakpoint in the set of candidate breakpoints based on presentation features of the media item. A subset of candidate breakpoints is selected from the set of candidate breakpoints based on the score. A final set of breakpoints is selected from the subset of candidate breakpoints based on a combination of the score for each particular candidate breakpoint and a location of the particular candidate breakpoint relative to a different candidate breakpoint. The final set of breakpoints is stored in a database and during playback of the media item, a digital component is presented when the media item reaches a stored breakpoint.

Abstract: In a system including vector registers storing right-hand side data and left-hand side data, first and second matrix staging registers, and a systolic array of processing cells for conducting matrix multiplication operations using the right-hand side data and left-hand side data, one or more processors load the right-hand side data from the vector registers to the first matrix staging register based on an instruction indicating whether to transpose the right-hand side data, load the left-hand side data from the vector registers into the second matrix staging register based on another instruction indicating whether to transpose the left-hand side data, load the right-hand side data from the first matrix staging register into the systolic array, and, in a cycle of the matrix multiplication operation, pass one or more columns of the left-hand side data from the second matrix staging register to a column of the systolic array.

Abstract: Methods, systems, and computer readable medium facilitating encrypted information retrieval. Methods can include receiving a batch of queries that includes queries to special buckets in each database shard. Query results responsive to the batch of queries are transmitted to the client device. The query results includes server-encrypted secret shares obtained from the special buckets. Client-encrypted versions of the secret shares are received. A full set of server-encrypted secret shares is transmitted to the client device, which is encrypted by the client device to create a full set of client-server-encrypted secret shares. The client device is classified based on how many of the secret shares are included in both of the client-encrypted secret shares received from the client device and the full set of client-server-encrypted secret shares received from the client device.

Abstract: A method includes receiving sensor data representative of surfaces in a physical environment containing an interaction point for a robotic device and determining, based on the sensor data, a height map of the surfaces in the physical environment. The method also includes determining, by inputting the height map and the interaction point into a pre-trained model, one or more candidate positions for a base of the robotic device to allow a manipulator of the robotic device to reach the interaction point. The method additionally includes determining a collision-free trajectory to be followed by the manipulator of the robotic device to reach the interaction point when the base of the robotic device is positioned at a selected candidate position of the one or more candidate positions and, based on determining the collision-free trajectory, causing the base of the robotic device to move to the selected candidate position within the physical environment.

Abstract: Systems and techniques are provided for sound model localization within an environment. Sound recordings of sounds in the environment may be received from devices in the environment. Preliminary labels for the sound recordings may be determined using pre-trained sound models. The preliminary labels may have associated probabilities. Sound clips with preliminary labels may be generated based on sound recordings that have preliminary labels whose probability is over a high-recall threshold for the pre-trained sound model that determined the preliminary label. The sound clips with preliminary labels may be sent to a user device. Labeled sound clips may be received from the user device. The labeled sound clips may be based on the sound clips with preliminary labels. Training data sets may be generated for the pre-trained sound models using the labeled sound clips. The pre-trained sound models may be trained using the training data sets to generate localized sound models.

Abstract: This document describes methods, devices, systems, and means for a switching scheme for opting in and out of multi-user orthogonal frequency-division multiple access (MU-OFDMA). In one aspect, an electronic device enters the MU-OFDMA mode to communicate via a wireless network over a shared-channel bandwidth. During the MU-OFDMA mode, the electronic device determines that an uplink-queue size is greater than a first threshold size. Responsive to the determining, the electronic device opts out of the MU-OFDMA mode and enters a single-user mode to contend for a transmit channel for transmitting uplink data.

Abstract: Systems and methods for automatic evaluation of the quality of NLG outputs. In some aspects of the technology, a learned evaluation model may be pretrained first using NLG model pretraining tasks, and then with further pretraining tasks using automatically generated synthetic sentence pairs. In some cases, following pretraining, the evaluation model may be further fine-tuned using a set of human-graded sentence pairs, so that it learns to approximate the grades allocated by the human evaluators. In some cases, following fine-tuning, the learned evaluation model may be distilled into a student model.

Abstract: The disclosed subject matter relates to systems, methods, and media for media session concurrency management with recurring license renewals. More particularly, the disclosed subject matter relates to using recurring license renewals for concurrent playback detection and concurrency limit enforcement for video delivery services and managing server resources for handling such recurring license renewals.

Abstract: A system including a network of superconducting electrical cables configured to supply power to a plurality of server racks arranged within a space of a building, a first power source connection configured to connect a first power source to the network of superconducting electrical cables from a first side of the building and configured to supply power to a first section of the network of superconducting electrical cables, a second power source connection configured to connect a second power source to the network of superconducting electrical cables from a second side of the building different from the first side and configured to supply power to a second section of the network of superconducting electrical cables, and a plurality of bus ducts, each bus duct configured to connect the network of superconducting electrical cables to one or more of the plurality of server racks.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for transmitting/processing requests to control information stored at multiple content platforms/servers. In one aspect, a client device can send a request to verify the device's trustworthiness to a device trustworthiness server. The client device can receive, from the device trustworthiness server, data indicating that the client device is trustworthy, in response to which, the client device can send, to a relay server, a request to control user data stored at a plurality of servers. The client device can receive, via the relay server, a response from each of the plurality of servers. Based on the responses, the client device can determine that at least a subset of the plurality of servers that included the user data has performed the action specified in the request to control the user data.

Abstract: A first screen device establishes a pairing session between a first screen device and a second screen device. The first screen device presents, in a user interface on the first screen device, a video and one or more media features related to the video. The media features pertain to at least one of a presentation of the video or user feedback about the video. The video is cast from the first screen device onto the second screen device. The first screen device receives, via the user interface, user input indicating a user request to enable presentation of at least one of the media features on the second screen device in connection with the video. In response to the user input, the first screen device causes the at least one of the media features to be presented on the second screen device in connection with the video.

Abstract: A computing device obtains from a fingerprint sensor a first set of fingerprint data representative of a first portion of a finger positioned at the fingerprint sensor at a first time and a second set of fingerprint data representative of a second portion of a finger positioned at the fingerprint sensor at a second time. The computing device determines a first set of keypoints based on the first set of fingerprint data and second set of keypoints based on the second set of fingerprint data. The computing device determines for the first set of keypoints a first set of parameter values and for the second set of keypoints a second set of parameter values. The computing device generates an at least partial fingerprint based on the first set of fingerprint data, the second set of fingerprint data, the first set of parameter values, and the second set of parameter values.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Abstract: A computer-implemented method includes receiving at a computer server system, from a computing device that is remote from the server system, a string of text that comprises a search query. The method also includes identifying one or more search results that are responsive to the search query, parsing a document that is a target of one of the one or more results, identifying geographical address information from the parsing, generating a specific geographical indicator corresponding to the one search result, and transmitting for use by the computing device, data for automatically generating a navigational application having a destination at the specific geographical indicator.