Methods, systems, and non-temporary computer-readable media for customizing community user robots.
The method and system enable community users to customize robots using a cloud server, allowing them to train and deploy AI robots that autonomously engage in community activities, reflecting user characteristics and providing personalized services.
JP2026121343APending Publication Date: 2026-07-24PLACY INC
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Patent Information
- Application Number
- JP2025234671
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-01-13
- Filing Date
- 2025-12-05
- Publication Date
- 2026-07-24
AI Technical Summary
Technical Problem
Existing community robots lack the ability for community users to train and customize them for personalized activities within their communities, limiting their functionality and interaction capabilities.
Method used
A method and system utilizing a cloud server to receive and preprocess user data, train a community robot using machine learning, and deploy it under the user's personal account, enabling it to perform community activities and interact with users through natural language processing and generative artificial intelligence.
Benefits of technology
Community robots can autonomously engage in community activities, reflect user characteristics, and provide personalized services, enhancing user interaction and community engagement.
✦ Generated by Eureka AI based on patent content.
Abstract
This provides methods, systems, and non-temporary computer-readable media for customizing community user robots. [Solution] The system provides a cloud server, and community users can upload data via the user interface provided by the cloud server to set the attributes of the community robot (including prompts for various attributes). Subsequently, a training dataset is formed after processing the data by a language model, and a machine learning method operating within that dataset is trained to learn the attributes of community users from the training dataset. Based on the prompts, the robot is trained to become a community robot dedicated to the community user, deployed to the community, and allowed to operate under the community user's personal account within the community.
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