TROY AI Docs
  • Executive Summary
  • Introduction
    • Market Opportunity and Potential Impact
  • TROY AI Ecosystem
    • TROY Play
    • TROY DAO
    • TROY TRADE
  • Technology Framework
    • Core AI Technologies
    • Data Privacy and Security
  • TROY AI’s Approach to AI-Native Development
    • Gaming
    • Social Interactions
    • Other Domains
  • $10 Million AI Grant Program
    • Purpose and Objectives
    • Eligibility Criteria and Selection Process
    • Funding Allocation and Project Support
  • Token Economics and Governance
    • TROY Token Utility and Distribution
    • Lifetime Membership for Passive Income
    • DAO Governance Model
    • Staking and Rewards Mechanisms
  • Data Ownership and Value Redistribution
    • User Data Control and Monetization
    • TROY ID (ERC721 NFT)
    • Value Creation and Distribution to Data Contributors
  • Security and Privacy Considerations
    • Data Protection Measures
    • Ethical AI Development Guidelines
    • User Privacy Safeguards
  • Legal and Regulatory Compliance
    • Regulatory Landscape
    • Compliance Strategy
    • Risk Management
  • Roadmap and Future Outlook
    • Short-term Milestones (6-12 months)
    • Medium-term Goals (1-3 years)
    • Long-term Vision (3+ years)
  • Conclusion
    • Recap of TROY AI’s Vision and Objectives
    • Call to Action for Developers, Users, and Investors
    • The Future of Data Ownership and AI Integration
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  1. Technology Framework

Core AI Technologies

TROY AI utilizes a state-of-the-art tech stack that integrates decentralized blockchain technology with the latest advancements in generative AI, AI agents, and multi-modal capabilities to enhance the development and operation of TROY Play and TROY TRADE.

Key Components of the TROY AI Tech Stack:

● Natural Language Processing (NLP): Enables sophisticated, context-aware interactions between AI agents and users, improving communication.

● Computer Vision: Facilitates visual understanding across various applications, enhancing user interfaces and experiences.

● Emotion Recognition: Empowers AI agents to interpret and respond to users' emotional states, fostering more empathetic interactions.

● Reinforcement Learning: Allows AI agents to adapt and improve their behavior based on user interactions and feedback, ensuring continuous performance enhancement.

● Retrieval-Augmented Generation (RAG): Combines the strengths of retrieval and generation, allowing agents to access external knowledge bases for more accurate and contextually relevant responses.

● Agentic Workflow: Supports the creation of complex workflows for individual or multi-agent systems, enabling seamless integration and interaction among agents.

This integrated approach not only streamlines the development of AI agents but also enriches user experiences, positioning TROY AI as a leader in the consumer AI landscape.

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Last updated 10 months ago