A human-computer collaborative intelligent ecosystem and method based on cultural gene engineering

Abstract

The application discloses a kind of human-computer collaborative intelligent ecosystem and method based on culture gene engineering.The system is driven by "meaning-use intention" dual-core architecture, establishes global language, knowledge, software positioning system, realizes the accuracy and traceability of intelligent behavior.The system can automatically identify and record the language points, knowledge points and algorithm innovation in the process of collaborative innovation, and realize real-time right protection and incentive through the contribution point mechanism.The application expands the specific application scenarios such as knowledge experience venue, intelligent resident vehicle and double-character chessboard, solves the technical problems such as semantic ambiguity of existing AI system, untraceable innovation and difficulty in interest allocation, and provides a complete solution for productivity, production relations and intellectual property protection in the new era of human-computer interaction.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of artificial intelligence, natural language processing and intellectual property management. Specifically, it relates to a general artificial intelligence (AGI) ecosystem that is built based on the principles of fusion intelligence and cultural gene systems engineering and can automatically record and incentivize innovative contributions. Background Technology

[0002] Current artificial intelligence systems have the following inherent flaws: Semantic ambiguity: Large language models generate content based on statistical probability, lacking a precise understanding of the essence (sense) and intent (purpose) of language; Innovation is untraceable: the system cannot automatically identify and record micro-innovations generated during the collaboration between humans and machines; The challenge of rights allocation: The traditional intellectual property protection system cannot adapt to the real-time innovation rights confirmation needs in human-machine collaboration scenarios; Significant waste of computing power: Every calculation starts from scratch, making it impossible to effectively reuse verified intelligent paths; Lack of educational applications: There is a lack of intelligent facilities that can deeply integrate knowledge modules with experiential learning; Limitations of human-computer interaction: Existing interactive devices cannot be dynamically reconfigured according to the scenario, and lack the support of cultural gene engineering. Summary of the Invention

[0003] Core Inventive Concept This invention constructs a cultural gene engineering system driven by a dual core of "meaning-intention," establishes three major global positioning systems for language, knowledge, and software, and achieves: precise and traceable intelligent behavior, automated confirmation and incentive of innovative contributions, optimization and reuse of computational paths, scenario-based and personalized educational experiences, and adaptive and reconfigurable interactive devices.

[0004] Technical solution architecture Attached Figure Description Figure 1 It is the structural principle and flowchart of the technical solution system architecture. graph TB A[Input Layer] Multimodal information] --> B [Processing layer] [Definition - Intended Dual-core Engine] B --> C ["Storage Layer"] The three major global positioning systems C --> C1 [Global Positioning System] C --> C2 [Global Knowledge Location System] C --> C3 [Global Positioning System] B -->D[“Innovation Layer”] [IP contribution automatically recorded] D -->D1 [Language point innovation] D --> D2 [Knowledge Point Innovation] D --> D3 [Algorithm Innovation] C1&C2&C3 -->E["Output Layer"] Optimal Intelligent Path”] D1&D2&D3 -->F[“Incentive Layer”] Contribution Points System”] E --> G[“Application Layer” Five major implementation scenarios F -->H[“Rights Protection Layer” Automatic property rights confirmation assistance] G --> G1 [Intelligent Writing Assistance] G --> G2 [Interdisciplinary Research] G -->G3 [Knowledge Experience Hall] G -->G4 [Intelligent Parking Vehicle] G -->G5 [Intelligent Double-Character Chessboard] G -->I [Continuous Optimization Feedback] H -->I I --> B Key technical features The semantic set construction module adopts three types of bilingual (Chinese and English, Chinese language and mathematics, and terminology and colloquialism) for dual formal representation. It achieves accurate disambiguation and anchoring of semantics through a twin Turing machine, establishes a character group recording system at all levels from character to discourse, and realizes the accurate division and management of two-level information units of element-group.

[0005] Intent set generation module: Based on the synonym parallel correspondence transformation law, it achieves accurate intent matching, performs targeted intent invocation under the premise of order relation conservation, records the user's intent selection pattern to form an intelligent strategy library, and verifies the validity of intent through the intersubjective agreement law.

[0006] The three positioning system modules are: Global Language Positioning System A Library, which records the statistical patterns of semantic reuse and constructs a language gene map; Global Knowledge Positioning System B Library, which records the optimized paths of intention reuse and constructs a knowledge gene map; and Global Software Positioning System C Library, which records the complete workflow of semantic-intention coordination and constructs a software gene map.

[0007] The IP contribution auto-recording module captures innovations in language points, knowledge points, and software / hardware matching points in real time, automatically generates tamper-proof contribution chain evidence, automatically allocates rights points based on contribution values, and establishes an automatic conversion mechanism of contribution level - points - rights.

[0008] Intelligent facility adaptation module: Supports educational venues to dynamically configure workshop scale according to the number of knowledge modules, realize the autonomous combination of interactive devices according to the density of people, and provide learning tools to adaptively adjust difficulty according to cognitive level. Detailed Implementation

[0009] Example 1: Intelligent Writing Assistance System. Users input their creative needs, and the system accurately identifies core concepts from the set of meanings, matches the most suitable expression strategies and knowledge frameworks from the set of intentions, automatically records innovative expressions and knowledge connections generated during this collaboration, generates contribution points and stores them in a blockchain-based ownership confirmation system, and the optimized creative path is entered into a global software positioning system for reuse.

[0010] Example 2: Interdisciplinary Research Platform. Researchers propose complex scientific questions. The system quickly locates relevant concepts, methods, and research paradigms through three positioning systems, automatically combines the optimal research path, records innovative interdisciplinary intersections, and incentivizes interdisciplinary innovative contributions in real time, forming a reusable interdisciplinary research "recipe."

[0011] Example 3: Knowledge Module Refinement Experience Venue. Venue Structure Design: Experience workshops of appropriate scale are set up according to the number of knowledge modules at each stage of education, from K-12 to higher education (associate degree, bachelor's degree, master's degree, doctoral degree); Workshop Configuration: Each workshop corresponds to a core knowledge module and is equipped with a dedicated meaning-purpose database; Experience Process: Students enter the workshop corresponding to the knowledge module. The system retrieves the corresponding set of meanings based on the student's cognitive level, presents the three-dimensional structure of knowledge through AR / VR technology, and records the student's innovative understanding and expression during the experience; Refinement Mechanism: The system automatically identifies the student's unique perspective on the knowledge points, transforms high-quality understandings into new meaning-purpose combinations, and promotes knowledge re-creation through point incentives; Effectiveness Evaluation: The teaching effectiveness is evaluated based on the quantity and quality of the innovative contributions generated by students during the experience.

[0012] Example 4: Intelligent Mobility Vehicle. Equipment Architecture: Modular design supports flexible combination for various indoor and outdoor scenarios; Crowd Sensing: Real-time monitoring of crowd size automatically adjusts vehicle form and functional configuration; Intelligent Adaptation: Small groups (1-10 people): Provides personalized interactive terminals; Medium groups (10-50 people): Creates collaborative work pods; Large groups (50+ people): Constructs immersive experience spaces; Cultural Integration: The vehicle incorporates three positioning systems: language, knowledge, and software. It automatically retrieves relevant semantic-intention databases based on usage scenarios, recording users' innovative contributions during movement; Application Scenarios: Museum tours, campus learning, corporate training, community education, etc.

[0013] Example 5: Intelligent Two-Character Chessboard. Chessboard Design: A variable chessboard system based on the cultural genes of Chinese characters; Hierarchical Mechanism: Beginner Chessboard: 500 high-frequency Chinese characters, categorized by radical; Intermediate Chessboard: 2000 commonly used Chinese characters, grouped by meaning; Advanced Chessboard: 5000 universal Chinese characters, clustered by cultural genes; Intelligent Transformation: Automatically adjusts the chessboard difficulty according to the user's literacy level, dynamically reorganizes the arrangement of Chinese characters according to the learning progress, and recommends the best learning path based on meaning association; Learning Functions: Masters the meanings and usages of Chinese characters through chessboard games, records learners' creative word formation and sentence construction, automatically includes high-quality creations in the intention set, and provides point incentives: Rewards points for innovative use of Chinese characters.

[0014] The beneficial effects of this invention are as follows: Technical benefits include: improving semantic understanding accuracy by over 50%, reducing computing power consumption by 70% through intelligent path reuse, increasing innovation discovery efficiency by 3-5 times, enhancing personalized education by 60%, and improving equipment utilization efficiency by 40%; Economic benefits include: establishing a new contribution-based rights distribution mechanism, significantly reducing intellectual property rights protection costs, creating a new type of human-machine collaborative production relationship, improving the utilization rate and added value of educational equipment, and building a new industrial ecosystem integrating culture and technology; Social benefits include: constructing a continuously evolving open innovation ecosystem, providing a trustworthy governance framework for the AGI era, promoting the deep integration of human wisdom and machine intelligence, driving fundamental changes in education models, and accelerating the digital inheritance of outstanding Chinese culture.

Claims

1. A human-machine collaborative intelligent ecosystem, characterized in that... include: The module includes a definition set construction module, a purpose set generation module, a global positioning system module, and an automatic IP contribution recording module.

2. The system as described in claim 1, characterized in that... The semantic set construction module adopts three types of bilingual dual formal representation methods.

3. The system as described in claim 1, characterized in that... The intent set generation module achieves intent matching based on the theorem of synonymous parallel correspondence transformation.

4. The system as described in claim 1, characterized in that... The Global Positioning System module comprises three subsystems: language, knowledge, and software.

5. The system as described in claim 1, characterized in that... The IP contribution automatic recording module can automatically generate contribution chain evidence and allocate equity points.

6. The system as described in claim 1, characterized in that... It also includes a smart facility adaptation module, which supports the intelligent configuration of experience venues, parking vehicles, and dual-character chessboards.

7. A knowledge module refinement experience venue, characterized in that... The scale of experiential workshops can be set according to the number of educational knowledge modules in schools at all levels and of all types, and an integrated meaning-purpose database can be used to support personalized learning experiences.

8. An intelligent parking carrier, characterized in that... It can be freely combined in form according to the number of people gathered indoors and outdoors, and has a built-in cultural gene engineering system to record innovative contributions.

9. An intelligent two-character chessboard, characterized in that... It can be freely combined and transformed according to the number of characters one knows, and provides a progressive learning path based on the Chinese character semantic database.

10. A method for realizing a human-machine collaborative intelligent ecosystem, characterized in that... Includes the following steps: Precise anchoring of meanings, intelligent matching of intent, optimized reuse of paths, automatic confirmation of contribution rights, and adaptive configuration of facilities.

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