Lifecycle of a DAO

• Capital Allocation: Funds are directed toward projects and liquidity.

• AI-Guided Decisions: AI evaluates opportunities and advises on investments.

• Liquidity Management: Tokens are actively traded with AI balancing supply and demand.

Mathematical Model:

$$ROI = \frac{\sum_{k=1}^{M} R_k - I}{I} \times 100\%$$

$$ROI\text{: Return on investment} \newline R_k\text{: Revenue from investment } k \newline I\text{: Initial investment capital}$$

Phase 3: Governance and Asset Management

• Proposal Evaluation: AI scores proposals for token holders to review.

• Voting Mechanisms: Community votes with optional AI recommendations.

• Transparency: Dashboards display fund performance in real-time.

Mathematical Model:

$$V(p) = \sum_{j=1}^{Q} w_j \cdot s_j$$

$$V(p): \text{Weighted score of proposal } p \newline w_j: \text{Weight of criterion } j \newline s_j: \text{Score of proposal } p \text{ on criterion } j$$

Phase 4: Profit Distribution and Lifecycle Renewal

• Profit Sharing: Returns distributed proportionally to token holders.

• Reinvestment Options: Token holders can reinvest in new DAO cycles.

• AI Evaluation: Insights provided for improving future DAO performance.

Mathematical Model:

$$D_i = \frac{H_i}{\sum_{i=1}^{N} H_i} \cdot P$$

$$D_i: \text{ Distribution amount for holder } i \newline H_i: \text{ Holdings of holder }i \newline P: \text{ Total profit to be distributed}$$