Abstract: Methods and systems are described for generating memes and enhanced content in electronic communication. The communication is received, analyzed, and assessed for determining whether the enhanced content should be included in the communication. A content, context, intent, and/or mood of the communication is determined. For meme generation implementations, images and captions are generated based on the communication. Some candidate memes incorporate an image of one of the participants in the communication. Enhanced content candidates are generated and presented to the user for inclusion in the communication. Artificial intelligence systems, including neural networks, and models are utilized to improve the enhanced content generation. Related apparatuses, devices, techniques, and articles are also described.

Abstract: To facilitate efficient entity resolution, systems and methods include a first dataset is received from a first database associated with a first entity and a second dataset is received from a second database associated with a second entity. A geo-grid is mapped to a geographical area covering the first entity data records and the second entity data records. A grid matching area in the geo-grid is generated for each first entity data record based on latitude data and longitude data of each first entity data record. Candidate matching records are determined from the second entity data records based on respective grid matching areas. Actual matching records are determined from the candidate matching records based on a threshold for a trigram similarity between each candidate matching record and the respective first entity data record. The actual matching records are associated with the respective first entity data record in the first database.

Abstract: An interactive data object map system is disclosed in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. The interactive data object map system allows for rapid and deep analysis of various objects, features, and/or metadata by the user. A layer ontology may be displayed to the user. In various embodiments, when the user rolls a selection cursor over an object/feature an outline of the object/feature is displayed. Selection of an object/feature may cause display of metadata associated with that object/feature. The interactive data object map system may automatically generate feature/object lists and/or histograms based on selections made by the user. The user may perform geosearches, generate heatmaps, and/or perform keyword searches, among other actions.

Abstract: A filter multiplexer for variable bandwidth annealing selection is described. The filter multiplexer has multiple pathways, where each pathway comprises a switch and a filter. Each filter has a different cutoff frequency from the other filters. Switches may be cryogenic switches. Each pathway may be communicatively coupled to an external annealing line. Upon receiving a problem, an annealing bandwidth can be selected, set or configured via the multiplexer to operate a quantum processor with a desired annealing schedule. The multiplexer may be used for calibration of a quantum processor by performing a calibration with a large annealing bandwidth, then calibrating the quantum processor by iterating through all available annealing bandwidths from the multiplexer.

Abstract: A display apparatus includes a display; a communicator configured to communicate with a plurality of external apparatuses, which respectively provide a plurality of contents; and a processor. The processor is configured to: based on receiving information relating to contents among the plurality of contents from external apparatuses, respectively, through the communicator, identify the external apparatuses that transmitted the information, among the plurality of external apparatuses, control the display to display a UI including the contents respectively received from the identified external apparatuses, and control the display to display, on the UI, reproduction states of the contents to be visually distinguishable according to states of inputs of users of the received contents, the inputs being received through the identified external apparatuses, respectively.

Abstract: An electronic device displays a user interface including a slider control that represents a continuous range of values between a first value and a second value, the slider control includes a first end that corresponds to the first value and a second end that corresponds to the second value, and the slider control further includes a movable indicator configured to move along the slider control between the first and the second end. The device detects a contact on the slider control followed by a movement of the contact. In response to the movement detection, the device moves the moveable indicator along the slider control and generates a tactile output upon the moveable indicator reaching the first end of the slider control with a tactile output pattern configured based on a movement speed when the moveable indicator reaches the first end.

Abstract: According to one embodiment, a method, computer system, and computer program product for controlled screen sharing is provided. The embodiment may include detecting a user intention to begin a screen sharing session during a web conference. The embodiment may also include receiving a user selection of a first view to display during the screen sharing session. The embodiment may further include receiving a user selection of a first subset of web conference participants. The embodiment may also include displaying the first view to the first subset.

Abstract: An image forming apparatus includes a controller that displays a first screen on a touch screen. The screen has selectable regions including a first display area and a second display area. The first display area is in a selected state when the first screen is initially displayed. The controller outputs audio data indicating the first display area is in the selected state. The controller receives a first user operation on the touch screen displaying the first screen to change the second display area to the selected display state and then outputs audio data indicating the second display area is in the selected state. The controller receives a second user operation on the touch screen displaying the first screen with the second display area in the selected display state to change a setting value associated with the second display area, and then outputs audio data indicating the setting value.

Abstract: A method for providing an energy map may include defining group priorities, receiving indication of status for each of a plurality of individual entities with respect to corresponding priorities defined for each respective individual entity, correlating received indications of status to respective group priorities, providing a representation of group priorities, and mapping an amount of energy associated with the group priorities or individual priorities by providing a graphical representation of a respective amount of resources based on the received indications.

Abstract: A system can determine a group of input data, comprising score data, text data, and interaction data. The system can further categorize respective text data of the text data based on an intent of respective intents of the respective accounts of the respective experiences, to produce a group of categorized text data. The system can further generate respective binary sparse matrices that represent the respective interaction data of the interaction data. The system can further identify a binary sparse matrix of the binary sparse matrices that corresponds to score data of the score data that satisfies a defined score criterion, to produce an identified binary sparse matrix. The system can further store an indication of the identified binary sparse matrix, with categorized text data of the group of categorized text data corresponding to the identified binary sparse matrix.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for perform predictive data analysis operations. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations by using a cross-temporal encoding machine learning model, such as a cross-temporal encoding machine learning model that is generated by using a target intervention classification machine learning model to map outputs of the cross-temporal encoding machine learning model to historical target intervention labels, thus enabling supervised training of the cross-temporal encoding machine learning without the need for ground-truth data corresponding to the output of the cross-temporal encoding machine learning model.

Abstract: In general, embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for pipelined machine learning. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform pipelined machine learning using at least one of error correction machine learning models and output augmentation machine learning models, for example using a pipelined implementation of error correction machine learning models followed by output augmentation machine learning models.

Abstract: The present invention discloses a method for simulating stochastic oscillation in an individual-granularity long-distance expressway traffic volume using a quantum harmonic oscillator, which includes: firstly, describing the speed and position of a vehicle by a quantum superposition state, and constructing an energy eigenequation of the quantum harmonic oscillator to represent movement of the vehicle; secondly, constructing an n-order Hermite polynomial based on the energy eigenequation, constructing a quantum harmonic oscillator model for simulating the stochastic oscillation in the long-distance traffic flow in a mode featuring aliasing of multiple strategies, and optimizing a solution model; and finally, constructing a mapping mechanism between the probability and the traffic volume to simulate the traffic volume.

Abstract: Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

Abstract: The present invention provides techniques for learning Mahalanobis distance similarity metrics from data for individually fair machine learning models. In one aspect, a method for learning a fair Mahalanobis distance similarity metric includes: obtaining data with similarity annotations; selecting, based on the data obtained, a model for learning a Mahalanobis covariance matrix ?; and learning the Mahalanobis covariance matrix ? from the data using the model selected, wherein the Mahalanobis covariance matrix ? fully defines the fair Mahalanobis distance similarity metric.

Abstract: In one general aspect, a method can include displaying, on a display device included in a computing device, content in an application executing on the computing device. The method can further include displaying, in a user interface on the display device, at least one identifier, receiving a selection of the at least one identifier, and initiating casting in response to receiving the selection of the at least one identifier.

Abstract: Provided is a base mutation detection method, which includes: determining an initial frequency of sequencing data of samples being a specific base at an interested locus; calculating, based on the initial frequency, an expected value of each sample being the specific base at the interested locus; updating the initial frequency of the sequencing data of the samples being the specific base at the interested locus; further calculating the expected value of each sample being the specific base at the interested locus, further updating the initial frequency of the sequencing data of the samples being the specific base at the interested locus, and repeating the foregoing iteration until the expected value of each sample being the specific base at the interested locus converges; and determining, based on each converging expected value, a base mutation type and a mutation confidence at the interested locus of each sample.

Abstract: A computer-implemented method for reinforcement learning with Logical Neural Networks (LNNs) is provided including receiving a plurality of observation text sentences from a target environment, extracting one or more propositional logic values from the plurality of observation text sentences, finding a class for each propositional logic value by using external knowledge, converting each propositional logic value into a first-order logic by replacing a part in the propositional logic value with a variable word, the part indicating the class, selecting a LNN based on the class among LNNs prepared in advance for each class, each LNN receiving the one or more propositional logic values as a status input and outputting an action with a score indicating a degree of preference for taking the action, and performing a highest score action to the target environment to obtain a next state of the target environment and a reward for the highest score action.

Abstract: Aspects of the present disclosure describe systems and methods that enable a user of a computing device (e.g., a smartphone, tablet, etc.) to interact with a wearable device worn by the user. In one embodiment, the computing device provides a touchscreen-based graphical user interface (GUI). The GUI displays a three-quarter view of a plurality of icons arranged in a ring, where each of the icons is associated with a respective health/fitness parameter (e.g., heart rate, blood oxygen saturation, etc.). The GUI enables the user to interact with the wearable device through the computing device, via swiping gestures, presses of icons, and press-and-holds of the icons.

Abstract: The disclosure relates to a method of training an artificial neural network so that a first artificial neural network is trained based on a plurality of training data including a first feature and a second feature that has a correlation with the first feature and depends on the first feature.