Abstract: In one implementation, a computer-implemented method includes receiving, at a computing device and from a computer server system, digital content that is for sale and that is received without having yet been purchased by a user of the computing device; storing the digital content locally on the computing device in a manner that prohibits user access to the digital content; after storing the digital content: receiving user input that indicates the user is purchasing at least a portion of the stored digital content; and in response to the received user input, storing information that indicates the user purchased the portion of the digital content and providing the user with access to the purchased portion of the digital content; and in response to detecting that the computing device is communicatively connected to the computer server system over a network, providing the stored information to the computer server system.

Abstract: Systems and methods are described to notify an author that suggested content is available. An author-assistance tool is instantiated with a document processor to perform research to suggest content for a document being edited at the document processor. A user interaction relating to a document is received via the document processor, and the author-assistance tool generates suggested content for the document when the author has intent for content suggestion or the document has a document type that is on a list of document types for which a content suggestion should be made. The author-assistance tool then determines that the suggested content meets a pre-determined quality threshold, and generates, via the user interface of the document processor, a notification to the author that the suggested content is available.

Abstract: A computing device receives a response comprising one or more data sets corresponding to an identifier. The computing device identifies a first data set identifier in the response that signals the beginning of a first data set and edits the first data set to comprise a first keyboard stroke entry prefix understood by a second computing device as defining the first data set as a first particular type of data and a keyboard stroke entry suffix understood by the second computing device as defining an end of the first data set. The computing device identifies and edits a second data set. The edited first and second data sets are transmitted to the second computing device, where it processes the data sets based on the keyboard stroke entry prefixes and recognizes the end of the data sets based on the keyboard stroke entry suffix.

Abstract: In a general aspect, an apparatus can include image processing logic (IPL) configured to perform an image processing operation on pixel data corresponding with an image having a width of W pixels and a height of H pixels to produce output pixel data in vertical slices of K pixels using K vertically overlapping stencils of S×S pixels, K being greater than 1 and less than H, S being greater than or equal to 2, and W being greater than S. The apparatus can also include a linebuffer operationally coupled with the IPL, the linebuffer configured to buffer the pixel data for the IPL. The linebuffer can include a full-size buffer having a width of W and a height of (S?1). The linebuffer can also include a sliding buffer having a width of SB and a height of K, SB being greater than or equal to S and less than W.

Abstract: A method is described. The method includes configuring a first instance of object code to execute on a processor. The processor has multiple cores and an internal network. The internal network is configured in a first configuration that enables a first number of the cores to be communicatively coupled. The method also includes configuring a second instance of the object code to execute on a second instance of the processor. A respective internal network of the second instance of the processor is configured in a second configuration that enables a different number of cores to be communicatively coupled, wherein, same positioned cores on the processor and the second instance of the processor have same network addresses for the first and second configurations. A processor is also described having an internal network designed to enable the above method.

Abstract: An encoder and/or a computer implemented encoding method includes a texture module configured to determine texture data associated with texture of an image, a noise module configured to determine noise data based on the texture data, a synthesis module configured to generate spatial spectral characteristics of the noise, and combine at least one of the noise data, the texture data, and the spatial spectral characteristics of the noise based on at least one border between adjacent textures, and an encoding module configured to compress the image using an image compression codec.

Abstract: This document describes methods, devices, systems, and means for a wireless mesh access point with user-space tunneling. A first wireless mesh network access point (WMAP) determines that a frame from a first device is destined for a second device associated with a second WMAP. The first WMAP encapsulates the frame to produce an encapsulated frame that includes an Internet Protocol (IP) header and a payload, the Internet Protocol (IP) header including an IP destination address of the second WMAP and an IP source address of the first WMAP, and the payload including a header and payload data from the frame. The first WMAP sends the encapsulated frame to the second WMAP using a station mode interface of the first WMAP, which causes the second WMAP to forward the frame to the second device.

Abstract: Implementations relate to providing information items for display during a communication session. In some implementations, a computer-implemented method includes receiving, during a communication session between a first computing device and a second computing device, first media content from the communication session. The method further includes determining a first information item for display in the communication session based at least in part on the first media content. The method further includes sending a first command to at least one of the first computing device and the second computing device to display the first information item.

Abstract: A method includes receiving a build request containing build step instructions from a user. The build step instructions specify a usage of containers within memory hardware for building an output container. The containers include at least one private container having private contents and/or at least one public container having public contents. The method also includes authenticating the user initiating the build request and determining whether the user is authorized to access the private containers. When the user is authenticated and authorized to access the private containers, the method includes obtaining the containers specified by the build step instructions from the memory hardware, executing the build step instructions to build the output container while using the received containers, and outputting the built output container.

Abstract: In some implementations, a computer-implemented method includes analyzing first data from a first data source to determine a first schema of the first data source, and analyzing second data from a second data source to determine a second schema of the second data source. The method can further include generating a first two-dimensional aggregation of a first time data series having a time dimension and a dimension corresponding to aggregated values of a first metric, and generating a second two-dimensional aggregation of a second time data series having a time dimension and a dimension corresponding to aggregated values of a second metric. The method can also include computing a correlation value between the first two-dimensional aggregation and the second two-dimensional aggregation, and providing an indication of duplicated data between the first data source and the second data source if the correlation value meets a threshold.

Abstract: A method includes receiving a speech input from a user and obtaining context metadata associated with the speech input. The method also includes generating a raw speech recognition result corresponding to the speech input and selecting a list of one or more denormalizers to apply to the generated raw speech recognition result based on the context metadata associated with the speech input. The generated raw speech recognition result includes normalized text. The method also includes denormalizing the generated raw speech recognition result into denormalized text by applying the list of the one or more denormalizers in sequence to the generated raw speech recognition result.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using dynamic minibatch sizes during neural network training. One of the methods includes receiving, by each of a plurality of host computer, a respective batch of training examples, each training example having zero or more features, computing, by each host computer, a minimum number of minibatches into which the host computer can divide the respective batch of training examples so that the host computer can process each minibatch using an embedding layer of the neural network without exceeding available computing resources, determining a largest minimum number of minibatches (N) into which any host computer can divide its respective batch of training examples, generating, by each host computer, N minibatches from the respective batch of training examples received by the host computer, and processing, by each host computer, the N minibatches using the embedding layer.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for constructing and programming quantum hardware for quantum annealing processes.

Abstract: This document describes techniques and systems that enable a smartphone-based radar system for determining user intention in a lower-power mode. The techniques and systems use a radar field to enable the smartphone to accurately determine the presence or absence of a user and further determine the intention of the user to interact with the smartphone. Using these techniques, the smartphone can account for the user's nonverbal communication cues to determine and maintain an awareness of users in its environment, and only respond to direct interactions once a user has demonstrated an intention to interact, which preserves battery power. The smartphone may determine the user's intention by recognizing various cues from the user, such as a change in position relative to the smartphone, a change in posture, or by an explicit action, such as a gesture.

Abstract: Methods, systems, and computer program products for cloud-based adaptive configuration and control of a network device include, detecting an access by a user through the network device to a cloud-based service; and responsive to the detected access, configuring the network device to be controlled by the user via a cloud-based configuration controller. Further implementations include, receiving a configuration request from the network device, wherein the configuration request includes access information pertaining to an access made by a user to a cloud-based service; determining a cloud-based identity of the user based upon the received access information; associating the cloud-based identity with an ownership identifier; forming one or more instructions to configure the network device with the ownership identifier as an owner of the network device; and transmitting the one or more instructions to the network device.

Abstract: Systems and methods for predicting content performance with interest data include receiving a content selection request that includes a client identifier. One or more topical interest categories associated with the client identifier may be used as inputs to a prediction model to predict the likelihood of an online action occurring as a result of third-party content being selected. The predicted likelihood may be used to select third-party content.

Abstract: This document describes methods, devices, systems, and means for controlling wireless devices using aggregated data from cross-network access points. An access point (AP) provides operational information from a plurality of different types of client devices communicating with the AP to a cloud service and obtains per-client-device-type policy data from the cloud service that is based on aggregated operational information from a plurality of different types of client devices from different AP networks. The AP controls, using a wireless transceiver, a wireless client device that is of a first type, using the per-client-device-type policy data for the first type based on aggregated operational information from a plurality of different types of client devices from different AP networks.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimized graph traversal are disclosed. In one aspect, a method includes the actions of receiving a given phrase that is input through a user interface by a digital component provider. The actions further include determining an entity that is being referred to by the given phrase. The actions further include identifying properties of the entity. The actions further include selecting a subset of the properties that were identified for the entity. The actions further include identifying additional phrases. The actions further include updating the user interface to present at least some of the additional phrases with programmatic controls that assign one or more of the additional phrase as distribution criteria for digital components of the digital component provider in response to activation of the programmatic controls.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for training a machine learning model to perform multiple machine learning tasks from multiple machine learning domains. One system includes a machine learning model that includes multiple input modality neural networks corresponding to respective different modalities and being configured to map received data inputs of the corresponding modality to mapped data inputs from a unified representation space; an encoder neural network configured to process mapped data inputs from the unified representation space to generate respective encoder data outputs; a decoder neural network configured to process encoder data outputs to generate respective decoder data outputs from the unified representation space; and multiple output modality neural networks corresponding to respective different modalities and being configured to map decoder data outputs to data outputs of the corresponding modality.