Alerta

Intelligent Orchestration Systems for Energy and Power Management of Edge Devices

Resumen de: US2025377647A1

Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a machine learning system is trained on a set of energy intelligence data and deployed on an edge device, wherein the machine learning system is configured to receive additional training by the edge device to improve energy management. In some embodiments, the energy management includes management of generation of energy by a set of distributed energy generation resources, management of storage of energy by a set of distributed energy storage resources management of delivery of energy by a set of distributed energy delivery resources, management of delivery of energy by a set of distributed energy delivery resources, and/or management of consumption of energy by a set of distributed energy consumption resources.

Method for Filtering User Feedback and/or Output of a Machine Learning Model

Resumen de: US2025378309A1

A computer implemented method for filtering user feedback and/or output of a machine learning model, comprising: providing a filter for filtering user feedback and/or output of a machine learning model; receiving user feedback and/or output of the machine learning model; filtering the user feedback and/or the output with the filter and determining a filtering result, wherein the filtering result comprises at least a detected error; providing the filtering result for further processing.

MACHINE LEARNING IN AGRICULTURAL PLANTING, GROWING, AND HARVESTING CONTEXTS

Resumen de: US2025378507A1

A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

SYSTEMS AND METHODS FOR MANAGING OIL AND GAS PRODUCTION

Resumen de: US2025378508A1

Implementations claimed and described herein provide systems and methods for managing natural resource production. The systems and methods use a machine learning model to generate categorizations associated with communication data. The machine learning model is built from historical data.

SYSTEM AND METHOD FOR TEACHING MACHINE LEARNING MODELS TO RECOGNIZE CONCEPTS IN MULTIMEDIA DOCUMENTS THROUGH NATURAL LANGUAGE INTERACTION AND MIXED-INITIATIVE LEARNING

Resumen de: AU2024274930A1

A method and system for training machine learning models using natural language interactions as well as techniques utilizing machine learning models trained using natural language interactions. A method includes applying a language model to text of a set of natural language interactions in order to output a set of domain-specific language (DSL) data, wherein the set of natural language interactions is between a user and at least one other entity, wherein the set of natural language interactions indicates at least one user-defined concept; querying a knowledge base based on the set of DSL data in order to obtain at least one DSL query result; integrating the at least one DSL query result with a structured representation of the natural language interactions in order to create at least one contextualized DSL query result; and training the language model using the at least one contextualized DSL query result.

Spectrum vacancy and occupancy forecasting

Resumen de: GB2641642A

A spectrum forecasting system, including a spectrum receiver to monitor a radio spectrum and collect live signal data; a spectrum forecasting deep learning model communicatively coupled to the spectrum receiver to receive the live signal data as input data, infer future vacancies, and chart a path through the future vacancies for assignment. A spectrum forecasting method, including receiving live signal data from a radio spectrum; inputting the live signal data into a spectrum forecasting deep learning model; inferring, using the spectrum forecasting deep learning model, future vacancies; and charting, using the spectrum forecasting deep learning model, a path through the future vacancies for assignment.

MACHINE LEARNING ARCHITECTURE FOR DETECTING MALICIOUS FILES USING STREAM OF DATA

Resumen de: CN120660086A

The invention discloses a method, a system and a computer system for classifying streaming data at an edge device. The method includes obtaining streaming data of a file at the edge device, processing a set of chunks associated with the streaming data of the file using a machine learning model, and classifying the file at the edge device prior to processing all content of the file.

MODEL GENERATION DEVICE, MACHINE LEARNING SYSTEM, MODEL GENERATION METHOD, AND PROGRAM

Resumen de: EP4660892A1

A model generation apparatus includes a parameter identification unit that identifies a parameter affecting misclassification of misclassification data incorrectly classified by a trained classification model, among parameters of the classification model for each type of the misclassification, based on the misclassification data incorrectly classified by the trained classification model; a parameter correction unit that generates a correction parameter obtained by correcting the parameter identified by the parameter identification unit for each type of the misclassification; and a parameter integration unit that generates an integrated model including an integrated parameter obtained by integrating the correction parameters for each type of the misclassification.

METHOD FOR FILTERING USER FEEDBACK AND/OR OUTPUT OF A MACHINE LEARNING MODEL

Nº publicación: EP4660880A1 10/12/2025

Solicitante:

ABB SCHWEIZ AG [CH]
ABB SCHWEIZ AG

Resumen de: EP4660880A1

Computer implemented method for filtering user feedback and/or output of a machine learning model, comprising: providing a filter for filtering user feedback and/or output of a machine learning model; receiving user feedback and/or output of the machine learning model; filtering the user feedback and/or the output with the filter and determining a filtering result, wherein the filtering result comprises at least a detected error; providing the filtering result for further processing.