3.3 Self-earning Capability

• Tokenized Computational Power Market Agentora tokenizes the computing power required for AI training, transforming it into a tradable economic asset. Through the assetization of computing power, the platform achieves an endogenous capital cycle, providing a solid economic foundation for the ecosystem's continuous development.

• AI Training Tax Mechanism During each AI model update and training process, the system levies a training tax at a certain percentage. This tax serves as a funding source for ecosystem maintenance, platform upgrades, and ecosystem expansion. This mechanism ensures that the entire system has a stable cash flow during continuous evolution, guaranteeing long-term operation and self-sustenance.

• Revenue Reinvestment and Ecosystem Incentives Agentora has designed a revenue distribution and reinvestment mechanism. A portion of the earnings obtained by players and participants is automatically channeled back into the ecosystem. This is used to further enhance AI Agents, expand the scale of the computational power market, and drive continuous upgrades of cross-chain and ecosystem functions.

• Self-sustaining Economic Cycle Through the above mechanisms, Agentora has built a self-sustaining, closed-loop economic system. Every transaction within the platform and each AI training session infuse new vitality into the entire ecosystem, endowing the Web3 AI economy with a high degree of self-maintenance and value appreciation capabilities.