Roadmap

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1. 2025 Q1-Q2: Initial Phase

• Complete platform architecture design and integration with Solana blockchain.

• Complete integration of decentralized storage (IPFS).

• Develop data upload and reward mechanisms.

• Launch community building and token airdrops.

2. 2025 Q3-Q4: Platform Launch and Testing

• Release initial version, conduct platform testing and optimization.

• Complete preliminary development of AI agents, supporting basic research experiment design and question answering.

3. 2026 Q1-Q2: AI Agent Optimization and Feature Expansion

• Optimize AI algorithms to enhance capabilities in autonomous research and experiment design.

• Complete integration of deep learning and natural language processing functions for AI agents, supporting more complex research question answering.

• Launch commercialization of research data within the platform, allowing transactions between data uploaders and users.

• Complete initial implementation of decentralized governance (DAO), enabling token holders to participate in platform governance.

4. 2026 Q3-Q4: Expanding Platform Ecosystem and Internationalization

• Expand coverage to more research fields, supporting interdisciplinary data sharing and intelligent analysis.

• Add trading markets for research tools and algorithms, pushing the platform to become a core tool for global researchers.

• Enhance the decentralized data verification mechanism, involving more experts and community members in data quality reviews.

• Launch an international version of the platform, supporting multiple languages and international research collaboration.

5. 2027 Q1-Q2: Perfecting Ecosystem and Technical Iteration

• Complete comprehensive optimization of the platform, including user experience, AI agent accuracy, and data processing capabilities.

• Promote cooperation with global research institutions, ensuring the platform becomes one of the main international scientific data sharing platforms.

• Perfect the token incentive mechanism to further increase the participation of researchers and institutions.

• Strengthen platform security and privacy protection to ensure user data safety.

Through the above optimizations, the DataNovaAI White Paper has been significantly enhanced in technical detail and AI agent implementation, providing a more solid foundation for the project's practical advancement and application.