Abstract: Various hardware and software configurations are described herein which provide improved security and control over protected data. In some embodiments, a computer includes a main motherboard card coupled to all input/output devices connected to the computer, and a trusted operating system operates on the main motherboard which includes an access control module for controlling access to the protected data in accordance with rules. The trusted operating system stores the protected data in an unprotected form only on the memory devices on the main motherboard. The computer may also have a computer card coupled to the main motherboard via a PCI bus, on which is operating a guest operating system session for handling requests for data from software applications on the computer.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: A spatio-temporal profilometer performs time-resolved spatial profilometry and includes a substrate, a tapered optical collimator waveguide, a fluid channel, and a light-fluid interaction volume. The tapered optical collimator waveguide receives diverging light, internally reflects it, and collimates it. The fluid channel receives a fluid comprising microparticles and communicates the microparticles into the fluid channel. The light-fluid interaction volume is disposed in the fluid channel and provided by an overlap within the fluid channel of the collimated light from the tapered optical collimator waveguide and the fluid. The spatio-temporal profilometer produces product light from the collimated light in response to the microparticles interacting with the collimated light in the light-fluid interaction volume from which is determined a spatial and temporal profile of microparticles in the fluid channel.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: The present concepts relate to a differentiable user-item co-clustering (“DUICC”) model for recommendation and co-clustering. Users' interaction with items (e.g., content) may be centered around information co-clusters—groups of items and users that exhibit common consumption behavior. The DUICC model may learn fine-grained co-cluster structures of items and users based on their interaction data. The DUICC model can then leverage the learned latent co-cluster structures to calculate preference stores of the items for a user. The top scoring items may be presented to the user as recommendations.

Abstract: Disclosed are techniques for extracting, identifying, and consuming imprecise temporal elements (“ITEs”). A user input may be received from a client device. A prediction may be generated of one or more time intervals to which the user input refers based upon an ITE model. The user input may be associated with the prediction, and provided to the client device.

Abstract: Disclosed are systems and methods for trusted and secure application deployment via collective signature verification of the application artifacts. The trusted and secure application deployment may include receiving multiple application artifacts, decoding verifications from at least one cryptographic signature associated with each received artifact, comparing the verifications to a first set of requirements specified in an admission control list, comparing the verifications from a first received artifact to a second set of requirements specified in the verifications of a second received artifact, halting the deployment of the artifacts in response to the decoded verifications not satisfying one or more requirements from the first set of requirements or the second set of requirements, and deploying the artifacts to a set of compute nodes in response to the verifications decoded from the received artifacts satisfying the first set of requirements and the second set of requirements.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.

Abstract: Disclosed are systems and methods for trusted and secure application deployment via collective signature verification of the application artifacts. The trusted and secure application deployment may include receiving multiple application artifacts, decoding verifications from at least one cryptographic signature associated with each received artifact, comparing the verifications to a first set of requirements specified in an admission control list, comparing the verifications from a first received artifact to a second set of requirements specified in the verifications of a second received artifact, halting the deployment of the artifacts in response to the decoded verifications not satisfying one or more requirements from the first set of requirements or the second set of requirements, and deploying the artifacts to a set of compute nodes in response to the verifications decoded from the received artifacts satisfying the first set of requirements and the second set of requirements.

Abstract: The present concepts relate to a differentiable user-item co-clustering (“DUICC”) model for recommendation and co-clustering. Users' interaction with items (e.g., content) may be centered around information co-clusters—groups of items and users that exhibit common consumption behavior. The DUICC model may learn fine-grained co-cluster structures of items and users based on their interaction data. The DUICC model can then leverage the learned latent co-cluster structures to calculate preference stores of the items for a user. The top scoring items may be presented to the user as recommendations.

Abstract: Embodiments of the present invention relate to a system and method for determining quantity of target nucleic acid sequence in a sample. During a PCR-based amplification reaction, fluorescence intensity signals are acquired that form an amplification profile from which an exponential amplification region is desirably identified. In determining the exponential region, embodiments of the present invention determine a fluorescence threshold by background subtraction, test the feasibility of matching a signal to a reference curve and, in the event the feasibility test is successful, determine the matching parameters that quantify the initial amplicon number, and signal detection that reduces systematic errors in the measurements and increase the sensitivity of the measurement by decreasing the apparent noise-floor.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: A computer-implemented technique receives an input expression that a user submits with an intent to accomplish some objective. The technique then uses a machine-trained intent encoder component to map the input expression into an input expression intent vector (IEIV). The IEIV corresponds to a distributed representation of the intent associated with the input expression, within a vector intent vector space. The technique then leverages the intent vector to facilitate some downstream application task, such as the retrieval of information. Some application tasks also use a neighbor search component to find expressions that express an intent similar to that of the input expression. A training system trains the intent encoder component based on the nexus between queries and user clicks, as recorded in a search engine's search log.

Abstract: Embodiments of the present invention described herein provide a device that can measure a single particle in flow several times along a microchannel with integrated waveguides that carry optical signals (e.g. excitation, emission, transmission, and scattered light) to and from measurement regions. Embodiments of the present invention used to perform multiple measurements of particles, such as microspheres or cells, traveling in a sample fluid through a microfluidic channel achieve lower uncertainties, discriminate complex samples, and account for sources of uncertainty that might be related to the shape, deformability, stability, or activity of objects in a liquid sample.

Abstract: A digital task document can include instructions for performing a task, and a task state data structure can indicate a state of completion of the task. A first update of the data structure can be performed in response to visual user input received from a user profile via a first computer application/device. A second update of the data structure can be performed in response to natural language input received from the user profile via the second computer application/device. A first set of task guidance can be provided to the user profile via the first application/device in a visual format by displaying the task document on a computer display. A second set of task guidance can be provided to the user profile via the second application/device in a natural language format. The first and second sets of task guidance can be provided using the task document and the data structure.

Abstract: The present disclosure relates to systems and methods for discovering relatedness between entities from a corpora of information by automatically extracting attributes from the plurality of heterogeneous entities in a graph. A standardized representation of the extracted attributes from the plurality of heterogeneous entities are propagated across the graph and these propagated attributes are used to find a degree to which the plurality of heterogeneous entities are associated with the extracted attributes. The degree to which the plurality of heterogeneous entities are associated with the extracted attributes is used to create a representation space illustrating a level of relatedness of an entity to another entity of the plurality of heterogeneous entities.

Abstract: Systems and methods for collaborative illumination estimation for mobile mixed-reality devices are provided. Embodiments described herein compose an illumination estimate using video data capturing an environment which includes a reflective object, such as a light probe. Radiance samples are computed from light reflections from the reflective object, which are then interpolated to compose a realistic estimation of physical lighting of the environment. Robust illumination estimation is provided in a computationally efficient manner, supplying real-time updates to facilitate integration with augmented reality (AR) systems and other image processing applications. The computational efficiency of this approach allows for implementation in lower-resource environments, such as mobile devices. In some examples, multiple devices can collaborate to capture the environment from different viewpoints and enhance realism and fidelity in their illumination estimates.

Abstract: An optical flow meter includes a substrate; a microchannel with a fluid receiver; a fluid transmitter; a fluid member with an optical interaction region; a photo interaction region; an analytical light path, such that analytical light interacts with an analyte in a photo interaction region subsequent to an interaction of a pre-analyte with activation light in an optical interaction region to produce analyte; and a detection light path disposed in the substrate, arranged at an oblique angle or right angle to the fluid member proximate to the photo interaction region, and that: receives the photoanalyte light from the photo interaction region; and communicates the photoanalyte light from the microchannel to a photodetector, the optical flow meter determines a flow rate of the analyte.

Abstract: This document relates to natural language processing using a framework such as a neural network. One example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. The example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. The contextualized semantic representations can provide a basis for performing one or more natural language processing operations.