Ai implementation method, cloud server, computer device and storage medium
By generating a unified desktop and analyzing natural voice commands through a neutral cloud server, and simulating user operations, the problem of recommendation algorithm bias between different brand ecosystems is solved, realizing a unified AI assistant service across brand ecosystems and providing a variety of value-added services.
CN122293657APending Publication Date: 2026-06-26XIAN WANXIANG ELECTRONICS TECH CO LTD
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Patent Information
- Application Number
- CN202610246376.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-02
- Publication Date
- 2026-06-26
AI Technical Summary
Technical Problem
The recommendation algorithms of existing AI smartphones exhibit bias and exclusivity among different brand ecosystems, resulting in limited user experience.
Method used
By using a neutral cloud server for unified scheduling, a fusion desktop image is generated and natural voice commands are analyzed to simulate user operations and control target applications, breaking the limitations of different ecosystems.
Benefits of technology
It enables a unified AI assistant service across brand ecosystems, allowing users to freely choose their agent, avoiding brand bias, and providing services such as AI analysis, intelligent routing, privacy management, and compliance supervision.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122293657A_ABST
Abstract
This disclosure provides an AI implementation method, a cloud server, a computer device, and a storage medium. The method includes: generating a front-end display desktop and sending the front-end display desktop to a zero-terminal display, enabling a user to install a target application on an application server within the corresponding ecosystem via the front-end display desktop; receiving natural voice commands initiated by the zero-terminal for the target application, and analyzing the natural voice commands and the front-end display image corresponding to the current user; outputting operation commands based on the analysis results, and simulating user operations based on the operation commands to control the target application. The AI implementation method of this disclosure avoids the bias and exclusivity issues inherent in the recommendation algorithms of different brand-specific large-models used in existing agents across different brand ecosystems.
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