Abstract: The systems and methods of the present disclosure generally relate to a data processing system that can identify and surface alternative requests when presented with ambiguous, unclear, or other requests to which a data processing system may not be able to respond. The data processing system can improve the efficiency of network transmissions to reduce network bandwidth usage and processor utilization by selecting alternative requests that are responsive to the intent of the original request.

Abstract: Systems and methods for multi-attendee video conferencing are described. A system can convert from huddle video conference mode to spatial video conference mode. In particular, by assigning user roles, specific users can have greater control of the video conference as compared to other users. For instance, moderators may have a greater level of control of the video conferencing system. Thus, in example implementations of the present disclosure, specific users can affect transition between two or more video conferencing modes, such as between a huddle video conference mode and a spatial video conference mode.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting entity names. One method includes receiving texts and deriving a plurality of name-context pairs from the texts. The method further includes calculating a context consistency measure for each name-context pair and storing context-entity name data representing the name-context pairs. Another method includes identifying an entity name and one or more context terms from a query and generating candidate names for the entity name. The method further includes determining a score for each of the candidate names, selecting a number of top scoring candidate names, and using the selected candidate names to respond to the query.

Abstract: A plurality of pixel drive circuits form part of an array of emissive elements. The plurality of pixel drive circuits are disposed to form a plurality of rows and a plurality of columns. The plurality of pixel drive circuits are organized into sets of pixel drive circuits, and each set comprises at least one pixel drive circuit. A FET of a set of pixel drive circuits shares a common well with other FETs of similar function in the same set of pixel drive circuits positioned therein, such that the variance of the threshold voltages of those FETs is substantially reduced. Each of the pixel drive circuits comprises a circuit operative to deliver a current at a predetermined voltage to an emissive device and a memory circuit operative to receive modulation data and to use same to modulate the current output of the pixel drive circuit.

Abstract: Techniques of providing continual augmented reality navigation include combining first and second 6DoF poses from, respectively, a localization from a map in a vicinity of a location to an image and from predicted 6DoF poses based on IMU data.

Abstract: Artificial image generation may include obtaining a source image, identifying quantization information from the source image, wherein identifying the quantization information includes identifying multiresolution quantization interval information from the source image, generating a restoration filtered image by restoration filtering the source image, generating a constrained restoration filtered image by constraining the restoration filtered image based on the quantization information, obtaining an unconstrained artificial image based on the constrained restoration filtered image and a generative artificial neural network obtained using a generative adversarial network, obtaining the artificial image by constraining the unconstrained artificial image based on the quantization information, and outputting the artificial image.

Abstract: Implementations utilize deep reinforcement learning to train a policy neural network that parameterizes a policy for determining a robotic action based on a current state. Some of those implementations collect experience data from multiple robots that operate simultaneously. Each robot generates instances of experience data during iterative performance of episodes that are each explorations of performing a task, and that are each guided based on the policy network and the current policy parameters for the policy network during the episode. The collected experience data is generated during the episodes and is used to train the policy network by iteratively updating policy parameters of the policy network based on a batch of collected experience data. Further, prior to performance of each of a plurality of episodes performed by the robots, the current updated policy parameters can be provided (or retrieved) for utilization in performance of the episode.

Abstract: Implementations are provided for increasing realism of robot simulation by injecting noise into various aspects of the robot simulation. In various implementations, a three-dimensional (3D) environment may be simulated and may include a simulated robot controlled by an external robot controller. Joint command(s) issued by the robot controller and/or simulated sensor data passed to the robot controller may be intercepted. Noise may be injected into the joint command(s) to generate noisy commands. Additionally or alternatively, noise may be injected into the simulated sensor data to generate noisy sensor data. Joint(s) of the simulated robot may be operated in the simulated 3D environment based on the one or more noisy commands. Additionally or alternatively, the noisy sensor data may be provided to the robot controller to cause the robot controller to generate joint commands to control the simulated robot in the simulated 3D environment.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. A user of an initiating device is identified. Profile information for the identified user is located. The initiating device includes a display for presenting content to the user. An indication is received from an application running on the initiating device of an intent by the user to receive a first content item on a separate but co-located presentation device having enhanced presentation characteristics for presenting content. Additional content items are selected for delivery along with the first content item. The selection includes identifying a second different content item based on the profile information for the identified user and the enhanced presentation characteristics.

Abstract: Implementations set forth herein relate to an automated assistant capable of bypassing soliciting a user for supplemental data for completing an action when a previously-queried application is capable of providing the supplemental data. For instance, when a user invokes the automated assistant to complete a first action with a first application, the user may provide many pertinent details. Those details may be useful to a second application that the user may subsequently invoke via the automated assistant for completing a second action. In order to save the user from having to repeat the details to the automated assistant, the automated assistant can interact with the first application in order to obtain any information that may be essential for the second application to complete the second action. The automated assistant can then provide the information to the second application, without soliciting the user for the information.

Abstract: Systems, methods, and computer readable media related to: training an encoder model that can be utilized to determine semantic similarity of a natural language textual string to each of one or more additional natural language textual strings (directly and/or indirectly); and/or using a trained encoder model to determine one or more responsive actions to perform in response to a natural language query. The encoder model is a machine learning model, such as a neural network model. In some implementations of training the encoder model, the encoder model is trained as part of a larger network architecture trained based on one or more tasks that are distinct from a “semantic textual similarity” task for which the encoder model can be used.

Abstract: Methods, systems, and media for presenting contextually relevant information are provided. In some implementations, the method includes: receiving information associated with a user of a user device from multiple data sources, where the user device comprises a display; identifying, without user intervention, a relevant document based on the received information associated with the user of the user device; determining that a new browser window or a new browser tab has been opened by a browser application being executed by the user device; and causing, without user intervention, the relevant document to be presented using the new browser window or new browser tab.

Abstract: Systems and methods of enforcing policies in a computer environment for content distribution using pointwise mutual information (PMI) based clustering are provided. The system can maintain a network of nodes representing a plurality of assets. Upon detecting that an asset is associated with a policy label, the system can identify attributes of the asset and compute a PMI score indicating whether nodes of the network sharing the attributes belong to a single content source. Upon determining that the PMI score exceeds a predefined threshold value, the system can identify a cluster of nodes including the nodes sharing the attributes. The system can tag the cluster, for example, as being associated with a content source that is associated with the policy label.

Abstract: A response to a first query related to a geographic area, and search results responsive to a second query related to the geographic area, are received from a server system. A digital map of the geographic is provided via a user interface. A focus is provided to the first query to illustrate the response on the digital map, where the response defines a geographic context. A subset of the search results is identified based on a relationship to the geographic context. The search results in the identified subset are visually emphasized on the digital map relative to the rest of the search results.

Abstract: Systems and methods for delivering cross-site auto-play media are described herein. The server can receive, from a client device, a request for media content at a first domain embedded in a content element from a second domain. The request can include an identifier indicating that the client device is configured to restrict cross-domain redirection. The server can determine, responsive to identifying the identifier indicating that the client device is configured to restrict cross-domain redirection, that the request comprises a content type header having a first predetermined value. The server can generate, responsive to the determination, a response comprising the media content element in a body of the response. The server can transmit the response to the client device. Receipt of the response can cause the client device to extract the media content element from the body of the response and to render the media content element.

Abstract: Implementations are directed to utilizing an assistant to automatically navigate an interactive voice response (IVR) tree to arrive at a target state during an assisted telephone call. The assistant can receive input to initiate the assisted telephone call, identify an entity to engage with, on behalf of the user, and during the assisted telephone call, based on the input, and identify an IVR tree stored in association with the entity. In various implementations, navigation of the IVR tree can be modified based on interaction(s) detected at a client device subsequent to initiating the assisted telephone call. In various implementations, the assisted telephone call can be initiated from a search interface, and the target state can be associated with a given search result. In various implementations, the IVR tree can be dynamic in that only a subset of candidate state(s) of the IVR tree may be available as the target state.

Abstract: Techniques are described herein for translating source code in one programming language to source code in another programming language using machine learning. In various implementations, one or more components of one or more generative adversarial networks, such as a generator machine learning model, may be trained to generate “synthetically-naturalistic” source code that can be used as a translation of source code in an unfamiliar language. In some implementations, a discriminator machine learning model may be employed to aid in training the generator machine learning model, e.g., by being trained to discriminate between human-generated (“genuine”) and machine-generated (“synthetic”) source code.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.