Abstract: A method for displaying a user interface used to manage a storage device is provided. The method is performed by a management device managing the storage device, and the method includes: obtaining, by using configuration content displayed in a first user interface, configuration data of a storage device configured for a first user; and after the first user logs in to the management device, displaying a second user interface corresponding to the first user, where the second user interface displays display content determined based on the configuration data.

Abstract: A client device installed with a client application having a graphical user interface (GUI) may be configured to (i) at a given time during a runtime session of the client application, identify a set of GUI elements within the GUI of the client application that is to be represented in a generic visualization of the GUI, (ii) generate a dataset that encodes the generic visualization of the GUI, wherein the generated dataset comprises a respective data structure for each GUI element in the identified set that encodes information for rendering a generic representation of the GUI element, and (iii) after generating the dataset that encodes the generic visualization of the GUI, transmit the generated dataset that encodes the generic visualization of the GUI to a back-end platform associated with a provider of the client application.

Abstract: In implementations of systems for estimating terminal event likelihood, a computing device implements a termination system to receive observed data describing values of a treatment metric and indications of a terminal event. Values of the treatment metric are grouped into groups using a mixture model that represents the treatment metric as a mixture of distributions. Parameters of a distribution are estimated for each of the groups and mixing proportions are also estimated for each of the groups. In response to receiving a user input requesting an estimate of a likelihood of the terminal event for a particular value of the treatment metric, the termination system generates an indication of the estimate of the likelihood of the terminal event for the particular value based on a distribution density at the particular value for each of the groups and a probability of including the particular value in each of the groups.

Abstract: The present invention comprises a novel method for generating AI training data sets and evaluating the efficacy of AI algorithms against real data. The invention consists of both hardware and software devices. The described hardware devices are capable of providing known test object metadata and state information such that the appropriate attributes of a test object may be known a priori for use in AI algorithms. The described software devices are capable of performing the temporal association of the sensor and test object metadata and either building the training data set or statistically evaluating the accuracy of a pre-existing AI algorithm.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for collaboratively training an interaction prediction machine learning model using a plurality of user devices in a manner that respects user privacy. In one aspect, the machine learning model is configured to process an input comprising: (i) a search query, and (ii) a data element, to generate an output which characterizes a likelihood that a given user would interact with the data element if the data element were presented to the given user on a webpage identified by a search result responsive to the search query.

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating message composition, according to embodiments of the present invention. In one embodiment, message data associated with a message being composed is obtained. The message data is analyzed to determine a message type indicating a type of message and a message context representation representing a context provided within the message being composed. Context representations representing expected contexts associated with the message type of the message are identified. Thereafter, an absent context missing in the message being composed is determined based on a comparison of the message context representation with the set of context representations. A recommendation related to the absent context can be provided, for example, for display via a user interface.

Abstract: Methods and systems are provided for detecting and processing gestures, expressions (e.g., facial), tone and/or gestures of the user for the purpose of improving the quality and speed of interactions with computer-based systems. Such information may be detected by one or more sensors such as, for example, electromyography (EMG) sensors used to monitor and record electrical activity produced by muscles that are activated. Other sensor types may be used, such as optical, inertial measurement unit (IMU), or other types of bio-sensors. The system may use one or more sensors to detect speech alone or in combination with gestures, expressions (e.g., facial), tone and/or gestures of the user to provide input or control of the system.

Abstract: A computer-implemented method according to one embodiment includes identifying a natural language query; translating the natural language query into an intermediate representation; converting the intermediate representation into one or more query triples; and performing relation linking between each of the one or more query triples and a plurality of knowledge base triples.

Abstract: An apparatus for generating annotations for electronic records is disclosed. The apparatus includes a processor and a memory containing instructions configuring the processor to receive unstructured data for a plurality of electronic records and generate a plurality of machine learning models (MLMs), wherein each MLM of the plurality of MLMs is trained using a machine learning algorithm. The processor is further configured to generate at least one annotation for the unstructured data using each MLM of the plurality of MLM and structure the unstructured data as structured data as a function of the generated annotations.

Abstract: A computer-implemented method for training an augmented discriminator and a generator. The method includes: providing a training set comprising real training samples and artificial training samples for training of the augmented discriminator, wherein the artificial training samples are generated by the generator; assigning a data sequence to at least one data sample of the training set; wherein each pair of data sample and assigned data sequence is assigned to one of a plurality of classes such that, given the assigned one class and the assigned data sequence characterize whether the data sample is a real training sample or an artificial training sample; training the augmented discriminator to compute from pairs of data sample and assigned data sequence the respective class to which the corresponding pair is assigned; training the generator to generate artificial training samples such that the augmented discriminator is not able to correctly compute the aforementioned one class.

Abstract: Systems and methods are disclosed for a first application associated with a first media sharing platform to incorporate context of a post from a second application associated with a second media sharing platform into a first user interface (UI) of the first application associated with the first media sharing platform. The method includes receiving, based on a post from a second UI of the second application, a user request pertaining to a media content item referenced in the post in the second UI of the second application, the second UI comprising post content associated with the media content item and a first plurality of UI elements. The method further includes presenting, within the first UI of the first application, the post content from the second UI of the second application and at least one control corresponding to at least one control from the second UI of the second application, the first UI to present a second plurality of UI elements and the post content separately from the media player.

Abstract: Technology embodied in a computer-implemented method for receiving a multi-modal input representing a query associated with a physical object, processing the multi-modal input to identify the physical object, and determining, based in part on an identification of the physical object and by accessing a language processing model, at least one response to the query associated with the physical object. The method also includes determining a sequence of actions associated with the at least one response, the sequence including at least one action that involves an interaction with at least one portion of the physical object. The method further includes generating a digital representation of the at least one action, and providing the digital representation to a user-device for presentation on a display. The digital representation includes a gesture-icon representing the action, the gesture-icon being overlaid on a digital twin of the physical object.

Abstract: A computer-implemented method for automatically determining data relationships includes generating a graphical user interface (GUI) that allows a user to intuitively form a customized model of data from different data sources. The GUI includes icons that represent data sources, data variable selection, data modeling, and data prediction. The icons can be logically arranged to form a customized model without any additional user input or knowledge of data modeling. A prediction GUI allows the user to set customized weights of data variables in the model to form predictive controls for data prediction such as in what-if scenarios.

Abstract: A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the hot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the hot generation server generates a bot to automate some or all of the process step.

Abstract: A chat-based persistent messaging platform that can seamlessly convert messages from different modalities (e.g., email clients and text message clients) into persistent messages and vice versa is described herein. The platform can include a parsing processor to convert messages into standard format data. A message classifier can process the standard format data into different subcomponents. These subcomponents can be translated into persistent messaging content via one or more content processing engines. The persistent messaging content can be converted into a persistent message via the parsing processor. The message classifier can also add messages into a persistent thread so that message history between two or more users can be maintained in perpetuity.

Abstract: A universal deep probabilistic decision-making framework for dynamic process modeling and control, referred to as Deep Probabilistic Decision Machines (DPDM), is presented. A predictive model enables the generative simulations of likely future observation sequences for future or counterfactual conditions and action sequences given the process state. Then, the action policy controller, also referred to as decision-making controller, is optimized based on predictive simulations. The optimal action policy controller is designed to maximize the relevant key performance indicators (KPIs) relying on the predicted experiences of sensor and target observations for different actions over the near future.

Abstract: Various aspects involve a monotonic recurrent neural network (MRNN) trained for risk assessment or other purposes. For instance, the MRNN is trained to compute a risk indicator from a predictor variable. Training the MRNN includes adjusting weights of nodes of the MRNN subject to a set of monotonicity constraints, wherein the set of monotonicity constraints causes output risk indicators computed by the RNN to be a monotonic function of input predictor variables. The trained monotonic RNN can be used to generate an output risk indicator for a target entity.

Abstract: An example method of monitoring computing resources in a cloud computing environment may include receiving a request to subscribe to a monitoring service with respect to computing resources associated with a user account, the request specifying access information for a cloud computing system comprising a plurality of virtual machines associated with the computing resources. The method may further include monitoring, using the access information, the plurality of virtual machines. The method may further include identifying, in view of the monitoring, a virus-infected application running on a virtual machine of the plurality of virtual machines. The method may further include terminating the virus-infected application. The method may further include receiving, in view of the monitoring, resource usage data reflecting types and duration of usage of the computing resources. The method may further include generating, in view of the usage data, a report reflecting usage of the computing resources.

Abstract: In the present disclosure, a method for compressing a feature map is provided, where the feature map is generated by passing a first input through a deep neural network (DNN). A respective optimal index order and a respective optimal unifying method are determined for each of super-blocks that are partitioned from the feature map. A selective structured unification (SSU) layer is subsequently determined based on the respective optimal index order and the respective optimal unifying method for each of the super-blocks. The SSU layer is added to the DNN to form an updated DNN, and is configured to perform unification operations on the feature map. Further, a first estimated output is determined, where the first estimated output is generated by passing the first input through the updated DNN.