Abstract: An industrial technical support system acts as an interactive assistant that leverages generative artificial intelligence (AI) techniques to suggest solutions to industrial alarm conditions or other performance problems based on earlier documented solutions, thereby expediting the process of finding alarm resolutions. The system enhances a user's prompt with relevant contextual data retrieved from stored documentation as well as relevant past chat histories to assist the system's generative AI model in recommending accurate resolutions to alarm conditions or performance issues described by the user's prompt.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

Abstract: Techniques for caching in a machine learning model (ML) hosting service are described. ML model usage data is aggregated from host usage data provided from each host of a first set of hosts, the ML model usage data including, for a particular ML model, a number of inference requests to the particular ML model. A priority order of hosts in a second set of hosts to service an inference request for the particular ML model is calculated. Based on the ML model usage data and the priority order, a set of ML models to load to a particular host in the second set of hosts is determined. The particular host is caused to load the set of ML models. A router is updated to direct ML model inference requests amongst the second set of hosts.

Abstract: A power system includes a power source configured to output electrical power, a power converter configured to convert the electrical power into a converted power, and a power bus configured to deliver the converted power to a power load connected to the power bus. The power system further includes a controller that implements a neural network (NN) trained to perform a NN-based model predictive control (NNMPC). The controller utilizes the NNMPC to obtain at least one learned control input for power regulation for a current system state and power load measurement of the power load in real-time, and to perform an output action that regulates the power system based on the at least one learned control input obtained by the NNMPC.

Abstract: Self-consumable portions generation techniques from a digital document are described. The self-consumable portions are generated based on a determination of an amount of resources available at a receiver device that is to receive the digital document. Examples of the resources include an amount of memory resources, processing resources, and/or network resources associated with the receiver device. The self-consumable portions, once generated, are separately renderable at the receiver device.

Abstract: A method for a HEP system includes obtaining, for each of a plurality of mission profiles, a respective first power splitting profile to be used throughout one or more flights described by the mission profile to achieve a fuel consumption objective for the one or more flights. Each power splitting profile indicates a series of power splits between a gas turbine and an electric motor of the HEP system. A neural network is trained to mimic the first power splitting profiles for the plurality of mission profiles. During one or more actual flights corresponding to a particular mission profile of an aircraft that includes a particular HEP system, the neural network is utilized to obtain a second power splitting profile for the particular HEP system for the one or more actual flights, and an output action for the particular HEP system is performed based on the second power splitting profile.

Abstract: The present invention may include a computing device that receives root data, where the root data comprises a plurality of datasets. The computing device determines a context of each dataset within the plurality of datasets. The computing device identifies one or more users based on monitoring behavior of the one or more users related to each dataset. The computing device appends metadata associated with each dataset within the plurality of datasets with the determined context and the one or more identified users and setts access restrictions to each dataset in the metadata based on the context and the one or more identified users.

Abstract: A method for a hybrid electric propulsion (HEP) system includes utilizing a soft actor-critic agent, which includes at least one neural network, and a control barrier function (CBF) filter to obtain a power splitting profile for an HEP system. The power splitting profile includes an electric motor power for an electric motor of the HEP system and a gas turbine power for a gas turbine of the HEP system. The electric motor power and gas turbine power collectively provide a combined HEP output power. The method also includes, during a flight of an aircraft that includes the HEP system, performing an output action for the HEP system based on the power splitting profile. The utilizing is performed based on a predefined fuel consumption objective and a state of charge of at least one battery that powers the electric motor. A system for a HEP system is also disclosed.

Abstract: Methods, systems, and computer-readable media are disclosed herein for improved state identification and prediction in computerized queries. In an aspects, a neural network model is trained via word embedding, using a plurality of workflows having a plurality of steps as input training data. The model may be searched using a string to locate and identify semantic matches as potential results, where the potential results correspond to a specific step and/or a particular workflow. Markov chaining may also be performed, using the potential results, in order to predict one or more additional results, where the additional results correspond to a specific succeeding step within a particular workflow, in some aspects. The results and predicted steps may be displayed.

Abstract: Self-consumable portions generation techniques from a digital document are described. The self-consumable portions are generated based on a determination of an amount of resources available at a receiver device that is to receive the digital document. Examples of the resources include an amount of memory resources, processing resources, and/or network resources associated with the receiver device. The self-consumable portions, once generated, are separately renderable at the receiver device.

Abstract: Certain aspects of the present disclosure provide techniques for predicting activity within a software application using a machine learning model. An example method generally includes generating a multidimensional time-series data set from time-series data associated with activity within a software application. The multidimensional time-series data set generally includes the time-series data organized based on a plurality of time granularities. Using a machine learning model and the generated multidimensional time-series data set, activity within the software application is predicted for one or more time granularities of the plurality of time granularities. Computing resources are allocated to execute operations using the software application based on the predicted activity within the software application.

Abstract: Methods, systems, and computer-readable media are disclosed herein for improved state identification and prediction in computerized queries. In an aspects, a neural network model is trained via word embedding, using a plurality of workflows having a plurality of steps as input training data. The model may be searched using a string to locate and identify semantic matches as potential results, where the potential results correspond to a specific step and/or a particular workflow. Markov chaining may also be performed, using the potential results, in order to predict one or more additional results, where the additional results correspond to a specific succeeding step within a particular workflow, in some aspects. The results and predicted steps may be displayed.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

Abstract: The present invention may include a computing device that receives root data, where the root data comprises a plurality of datasets. The computing device determines a context of each dataset within the plurality of datasets. The computing device identifies one or more users based on monitoring behavior of the one or more users related to each dataset. The computing device appends metadata associated with each dataset within the plurality of datasets with the determined context and the one or more identified users and setts access restrictions to each dataset in the metadata based on the context and the one or more identified users.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

Abstract: One embodiment provides a method, including: utilizing at least one processor to execute computer code that performs the steps of: providing, on a display device, a communications window, wherein the communications window comprises a request for user input to start a conversation with an online assistant; receiving a user input identifying a request by the user to be completed by the online assistant; updating, based upon the request, the communications window, wherein the updated communications window comprises a summary of the conversation including prepopulated variable terms and allows user interaction to adjust the summary including adjustment of the prepopulated variable terms; and iteratively updating the communications windows based upon user input adjusting the summary. Other aspects are described and claimed.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.

Abstract: A recreational and/or sports type transport (board) having an object detection and proximity warning system. The board uses sensors and calculates the distance from object, and then warns the user of the proximity of same through tactile and/or audio feedback.

Abstract: Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.