Table of Contents

  1. Introduction 1.1 Context and Vision 1.2 Key Contributions

  2. System Architecture 2.1 Overview 2.2 Key Components and Microservices

  3. Data Ingestion from the Web and Social Media 3.1 Real-Time Twitter Streams and News Feeds 3.2 Global Web Crawling

  4. Message Orchestration and Interaction 4.1 Message Bus (Kafka/RabbitMQ) 4.2 Reactive Flow Example

  5. Hanna AI Engine: Satirical Logic and Debate 5.1 Transformer-Based Foundations 5.2 Exposing Truth Through Contextual Analysis 5.3 Reinforcement Learning from Human Feedback (RLHF)

  6. Data Storage and Updates 6.1 Hybrid SQL + NoSQL 6.2 Automatic Archival and Versioning

  7. On-Chain Governance and Logging 7.1 Immutable Interaction Logging 7.2 DAO Governance Model

  8. Public Interaction, Debate, and Feedback Loops 8.1 Social Engagement Layer 8.2 Advanced Auto-Learning Pipeline

  9. Tokenomics: $HANNA 9.1 Utility and Incentives 9.2 Deflationary Dynamics

  10. Complexities, Theoretical Underpinnings, and Future Outlook 10.1 Scalability Challenges and HPC Concurrency 10.2 Ethical and Cultural Considerations 10.3 Theoretical Foundations of AI Logic

  11. Conclusion

  12. References

PreviousAbstractNext1. Introduction

Last updated