Abstract: A computer system receives a natural language input directed to a data source. In response to receiving the natural language input, and in accordance with a determination that the natural language input specifies an incomplete natural language command directed to the data source, the computer system presents a map widget for selecting geospatial data points from the data source. The map widget includes a map having a plurality of predetermined geographic regions. The computer system receives user specification of a user-defined region in the map included in the map widget. In accordance with receiving the user specification and based on a coverage metric computed for the plurality of geographic regions, the computer system selects one or more geographic regions. The computer system completes the natural language command with the selected geographic regions. The computer system generates and displays a map data visualization according to the completed natural language command.

Abstract: An asset management system that stores visual representation of an asset and its components, operational data of the components, and location of the components relative to the asset in a defined coordinate system. The system includes communication-enabled things disposed at the asset arranged to obtain component operational data and to communicate the operational data to data storage, and a user interface controllable by a user to display a visual representation of a selected portion of an asset, and to display visual representations of adjacent portions of the asset by receiving navigation instructions from the user. The user interface facilitates display of component information adjacent a component as the user navigates through the visual representation of the asset, the component information derived from the communication-enabled things. The stored data includes location of at least one actor disposed at the asset as the actor moves relative to the asset.

Abstract: In one embodiment, a method includes accessing a plurality of initial gradients associated with a machine-learning model from a data store associated with a first electronic device, selecting one or more of the plurality of initial gradients for perturbation, generating one or more perturbed gradients for the one or more selected initial gradients based on a gradient-perturbation model, respectively, wherein for each selected initial gradient: an input to the gradient-perturbation model comprises the selected initial gradient having a value x, the gradient-perturbation model changes x into a first continuous value with a first probability or a second continuous value with a second probability, and the first and second probabilities are determined based on x, and sending the one or more perturbed gradients from the first electronic device to a second electronic device.

Abstract: There are provided systems and methods for machine learning model verification for assessment pipeline deployment. A service provider may provide AI hosting platforms that allow for clients, customers, and other end users to upload AI models for execution, such as machine learning models. A user may utilize one or more user interfaces to provide model data and files, such as model artifacts, model requirements, and model test data. Thereafter, a model deployer may validate that the AI hosting platform has the required code packages and other model framework requirements for the AI model. The model test data may be used to ensure that the AI model is behaving correctly and providing the correct predictions based on input data and features. If so, the AI model may be deployed in a live production computing environment and used for predictive services.

Abstract: An electronic device for providing user experience based on a display extension profile and a method of controlling the same are disclosed. An electronic device according to an embodiment may include a housing, a flexible display disposed inside the housing, at least one driving motor disposed inside the housing and configured to extend a part of the flexible display from the housing, a memory storing a display extension profile related to control of the driving motor, and at least one processor. The at least one processor may be configured to identify occurrence of an event related to display of a preview screen showing a process of drawing out the flexible display, and display the preview screen showing the process of drawing out the flexible display through the flexible display, based on the display extension profile stored in the memory in response to the identification of the occurrence of the event.

Abstract: A secure inference over Deep Neural Networks (DNNs) using secure two-party computation to perform privacy-preserving machine learning. The secure inference uses a particular type of comparison that can be used as a building block for various layers in the DNN including, for example, ReLU activations and divisions. The comparison securely computes a Boolean share of a bit representing whether input value x is less than input value y, where x is held by a user of the DNN, and where y is held by a provider of the DNN. Each party computing system parses their input into leaf strings of multiple bits. This is much more efficient than if the leaf strings were individual bits. Accordingly, the secure inference described herein is more readily adapted for using in complex DNNs.

Abstract: A method for an artificial neural network includes receiving a set of input values to be convolved with multiple kernels via multiple computing units. One or more thermally-stressed computing units of the multiple computing units are determined. The multiple kernels are mapped to the multiple computing units of a system-on-chip (SOC) based on the one or more thermally-stressed computing units. A convolution is performed on the set of input values and a most sparse kernel of the multiple kernels on the most thermally-stressed computing unit.

Abstract: Described are methods, systems, and techniques to implement an improved map interface that displays updatable geographic information and that enables users to request one or more data products for a geospatial asset corresponding to a region of a geographic area. In some embodiments, a GIS application can be configured to interface with third party geospatial data suppliers that provide different types of data products displayable in the map interface. One or more of these data products can be requested by the user and may be associated with a recurring time interval to provide the user with expanded display views that are up to date and complete.

Abstract: Systems and methods for providing application management and navigation in a web-based environment are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: determine that a user has dragged-and-dropped a tab onto a launch bar of a web browser, parse a Uniform Resource Locator (URL) associated with the tab into a resource and a data source, and add a web app icon corresponding to the resource to the launch bar.

Abstract: System and method for completing knowledge graph. The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to: provide an incomplete knowledge graph comprising a plurality of nodes and a plurality of edges, each of the edges connecting two of the plurality of nodes; calculate an attention matrix of the incomplete knowledge graph based on one-hop attention between any two of the plurality of the nodes that are connected by one of the plurality of the edges; calculate multi-head diffusion attention for any two of the plurality of nodes from the attention matrix; obtain updated embedding of the incomplete knowledge graph using the multi-head diffusion attention; and update the incomplete knowledge graph to obtain updated knowledge graph based on the updated embedding.

Abstract: A reinforcement learning-based sensor data management system includes a processor configured to: manage virtualized objects that correspond to sensors included in a sensor network to update data received from each sensor and queries representing a data quality requested by an application; calculate an abstracted action that abstracts a size of an action space of the sensor network based on present state information of the virtualized objects and the queries; calculate scores for virtualized objects based on position relationships between the calculated abstracted action the virtualized objects; and assign priorities to the virtualized objects based on the calculated scores to update data received from the sensors to the virtualized objects according to the priorities.

Abstract: A method including extracting data from disparate data sources. The data includes data pairs including a corresponding data point and a corresponding time associated with the corresponding data point. The method also includes extracting insights from the data at least by identifying a trend in the data pairs. The method also includes forming a model vector including the insights and an additional attribute to the insights. The additional attribute characterizes the insights. The additional attribute includes at least user feedback including a user ranking of a ranked subset of the insights from a user. The method also includes inputting the model vector into a trained insight machine learning model to obtain a predicted ranking of the insights. The method also includes selecting, based on the predicted user ranking, a pre-determined number of insights to form predicted relevant insights. The method also includes reporting the predicted relevant insights.

Abstract: A table including a record can be displayed within a graphical user interface display space. The record can include an attribute. Data characterizing a user input can be received. The user input can specify an input parameter of an entry associated with the attribute of the record. A predefined syntactical rule set can be used to parse the user input. The parsing can include determining one or more simulation attributes associated with executing a simulation. The one or more simulation attributes can be provided. The result of the executed simulation can be processed. The result of the executed simulation can be displayed within a graphical user interface display space. Related apparatus, systems, techniques, and articles are also described.

Abstract: A control method for an electronic device is disclosed. The control method comprises the steps of during a call with a user of another electronic device by means of an electronic device, acquiring at least one keyword from a content of the call with the user of the another electronic device displaying the at least one keyword during the call and providing a search result for a keyword selected by a user from among the displayed at least one keyword. Particularly, at least a part of the control method of the present disclosure may use an artificial intelligence model learned according to at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: A method includes receiving first input values for a first parameter of a physical system, calculating first modeled values for a second parameter using a model that represents the physical system, based on the first input values, receiving measured values for the second parameter, training a machine learning model to adjust modeled values generated by the model based on a difference between the first modeled values and the measured values, receiving second input values for the first parameter, calculating second modeled values for the second parameter using the model, generating adjusted values for the second parameter by adjusting the second modeled values using the trained machine learning model, and visualizing the adjusted values for the second parameter as representing operation of the physical system.

Abstract: Disclosed is an accelerator and a method of operating the accelerator including determining whether any group shares weights of a first group from among groups, determining a presence of an idle processing element (PE) array, in response to no group sharing the weights of the first group, and selecting a second group having a memory time overlapping a computation time of the first group from among the groups, in response to the idle PE array being present.

Abstract: Discussed herein are devices, systems, and methods for classification using a clustering autoencoder. A method can include receiving, by an encoder of an autoencoder, content, the autoencoder trained using other content and corresponding labels, providing, by the encoder, a latent feature representation of the content to a decoder of the autoencoder, providing, by a clustering layer situated between the encoder and the decoder, a probability that the content belongs to a class of classes represented by respective clusters in a latent feature representation space based on a distance between the feature representation and the cluster, and providing, by the decoder, reconstructed content that is a construction of the content based on the latent feature representation.

Abstract: According to embodiments, a method of neural network optimized matrix-matrix multiplication (NNMM) is performed by at least one processor and includes determining a first matrix of input coefficients, and determining a second matrix of weight coefficients of a neural network that is trained so that the second matrix has a predetermined uniform pattern, the predetermined uniform pattern having at least two of the weight coefficients that have a same value. The method further includes performing multiplication of the determined first matrix and the determined second matrix to determine output coefficients.

Abstract: A software system operates to store information about a plurality of products in a common data management system that serves as a single source of truth for product information. Multiple different computing systems can access and edit item records. As information in the item records is updated, other computing systems can access the updated information immediately. The overall system is a multi-use tool for assortment planning that allows for flexible data sharing across the lifecycle of an item for item definition, budget definition, and vendor negotiation.

Abstract: An arithmetic part of an arithmetic processing device includes: a filter processing part that has a multiplier and a first adder and performs filter processing; a second adder that performs cumulative addition processing that cumulatively adds all of the results of the filter processing as executed in N parallel; a non-linear conversion part that performs non-linear arithmetic processing on the result of the cumulative addition processing; a pooling processing part that performs pooling processing on the result of the non-linear arithmetic processing; and an arithmetic control part that controls the filter processing part, the second adder, the non-linear conversion part, and the pooling processing part.