Processing

Please wait...

Settings

Settings

Goto Application

1. WO2022115198 - ROBOTIC PROCESS AUTOMATION ARCHITECTURES AND PROCESSES FOR HOSTING, MONITORING, AND RETRAINING MACHINE LEARNING MODELS

Publication Number WO/2022/115198
Publication Date 02.06.2022
International Application No. PCT/US2021/056924
International Filing Date 28.10.2021
IPC
G05B 19/04 2006.1
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
19Programme-control systems
02electric
04Programme control other than numerical control, i.e. in sequence controllers or logic controllers
G06N 3/08 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
G06F 9/44 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
44Arrangements for executing specific programs
CPC
G06F 21/602
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
21Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
60Protecting data
602Providing cryptographic facilities or services
G06F 21/6218
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
21Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
60Protecting data
62Protecting access to data via a platform, e.g. using keys or access control rules
6218to a system of files or objects, e.g. local or distributed file system or database
G06F 8/61
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
8Arrangements for software engineering
60Software deployment
61Installation
G06F 9/451
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
44Arrangements for executing specific programs
451Execution arrangements for user interfaces
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06N 20/20
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
20Ensemble learning
Applicants
  • UIPATH, INC. [US]/[US]
Inventors
  • SHRIVASTAVA, Shashank
Agents
  • LEONARD, Michael, Aristol, II
  • PATEL, Sheetal, S.
Priority Data
17/143,39207.01.2021US
20201105123625.11.2020IN
20201105123725.11.2020IN
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) ROBOTIC PROCESS AUTOMATION ARCHITECTURES AND PROCESSES FOR HOSTING, MONITORING, AND RETRAINING MACHINE LEARNING MODELS
(FR) ARCHITECTURES D'AUTOMATISATION DE PROCESSUS ROBOTIQUES ET PROCESSUS D'HÉBERGEMENT, DE SURVEILLANCE ET DE NOUVELLE FORMATION DE MODÈLES D'APPRENTISSAGE AUTOMATIQUE
Abstract
(EN) Robotic process automation (RPA) architectures and processes for hosting, monitoring, and retraining ML machine learning (ML) models are disclosed. Retraining is an important part of the ML model lifecycle. The retraining may depend on the type of the ML model and the data on which the ML model will be trained. A secure storage layer may be used to store data from RPA robots for retraining. This retraining may be performed automatically, remotely, and without user involvement.
(FR) Des architectures d'automatisation de processus robotiques (RPA) et des processus d'hébergement, de surveillance et de nouvelle formation de modèles d'apprentissage automatique (ML) sont divulgués. La nouvelle formation est une partie importante du cycle de vie de modèle ML. La nouvelle formation peut dépendre du type du modèle ML et des données sur lesquelles le modèle ML sera formé. Une couche de stockage sécurisée peut être utilisée pour stocker des données provenant de robots RPA pour une nouvelle formation. Cette nouvelle formation peut être effectuée automatiquement, à distance et sans implication de l'utilisateur.
Related patent documents
Latest bibliographic data on file with the International Bureau