⚖️Governance & Incentive

The sustainable development of the AI ecosystem requires equitable contributions of data, models, and computing resources from participants. However, traditional centralized platforms often lack transparency and fair revenue distribution mechanisms, which weakens motivation for collaboration.

Shortcomings of Existing Technology:

• Uneven Revenue Distribution: On traditional platforms, it is often difficult to transparently measure the contributions of data providers, model developers, and infrastructure operators. This typically results in revenue distribution favoring the platform itself, discouraging multi-party participation.

• Centralized Governance Models: Governance on traditional AI platforms is usually controlled by a single entity, lacking transparency and user participation. This can lead to unfair decision-making and oversimplified ecological development.

• Inefficient Collaboration Models: Task allocation and resource utilization lack automation and standardization, particularly in multi-agent collaborations. Existing systems struggle to achieve dynamic collaboration for complex tasks.

LazAI adopts a decentralized governance model to ensure that contributions of data, computing power, and models are rewarded fairly and transparently. Through community-driven data governance and incentive mechanisms, the platform addresses data sovereignty issues inherent in traditional platforms. LazAI also removes harmful or biased data while encouraging broader user participation, driving the platform’s sustainable development.