Ai Based, Knowledge: AI-Powered Decentralized Staking System
Version 1.0 | Date of Issue: Q1 2025
AIK (Ai Based, Knowledge) aims to solve the inefficiency and low-yield problems of existing staking systems by combining the predictive power of Artificial Intelligence (AI) with the decentralized security of the blockchain.
Our vision is to provide every user with an optimal staking experience based on market Knowledge.
AIK provides the following solutions by building a **Knowledge Base** and utilizing trained Machine Learning models.
The AIK engine primarily uses Reinforcement Learning and time-series prediction models (LSTM, Transformer, etc.) to determine the optimal staking strategy.
AIK is a utility token used for project governance, staking rewards, and system fees within the ecosystem.
| Item | Ratio | Lock-up Period / Purpose |
|---|---|---|
| Staking Rewards | 40% | Distributed flexibly over the next 5 years |
| Operations & Development (Incl. AI Research) | 25% | Sequential release after team lock-up |
| Private/Public Sale | 15% | Initial liquidity and fundraising |
| Team & Advisors | 10% | 2-year lock-up, 2-year vesting |
| Ecosystem Growth & Marketing | 10% | Partnerships and community growth |
To incentivize long-term commitment and significant contribution to network security, AIK implements a **Loyalty Staking Bonus**. For every **20,000 AIK** staked in the AIK engine, the holder receives an additional **0.1% Daily Interest Bonus** on top of the base staking APY. This mechanism directly links the scale of contribution to the reward structure, fostering deep ecosystem loyalty. The daily interest rate (Daily Interest Rate) is calculated as: \($\text{Daily Interest Rate} = \text{Base Rate} + \left( \lfloor \frac{\text{Staked AIK}}{20,000} \rfloor \times 0.001 \right)$\) where $\lfloor x \rfloor$ is the floor function.
The AIK team consists of experienced blockchain developers, seasoned data scientists, and finance professionals who share a vision for the future of decentralized finance.
Harvard University (Computer Science), 15+ years in blockchain startups, serial entrepreneur in crypto and AI.
Moscow State University (AI & Robotics), Expert in AI/ML algorithms, led AI development at TechCorp.
Tsinghua University (Industrial Engineering), Operations expert, managed large-scale crypto exchanges.
Stanford University (Marketing), Marketing strategist with global crypto campaign experience.
MIT (Computer Science & AI), Specialized in reinforcement learning for blockchain-based applications.
Peking University (Computer Science), Expert in smart contract development, cross-chain integration and auditing.
Lomonosov Moscow State University (AI & UX), Leading product strategy for AIK platform, AI UX specialist.