AI Monopoly Dilemma: Why Does Sahara AI Want to Decentralize?

Currently, the mainstream AI applications and large models on the market are mostly in the hands of tech giants. This centralized ownership structure has led to:

• Data privacy is difficult to guarantee.
• The barrier to entry for AI is high;
• Innovation mainly comes from a few players.

The purpose of Sahara AI is to break this situation. It introduces the concept of “AI assets”—whether it is models, data, or agents, users can possess their “ownership,” “access rights,” and “income rights,” and circulate and trade them on the platform.

Technical Architecture Analysis: Four Levels Supporting the Complete AI Lifecycle

The Sahara AI platform consists of the following four major technical layers:

1. Application Layer: Provides user operation interfaces, including AI marketplace, development tools, model building platforms, etc.
2. Transaction Layer: Based on the self-developed Sahara public chain, it handles ownership confirmation, contribution records, and profit distribution.
3. Data Layer: Achieves a hybrid storage solution that combines on-chain and off-chain storage, ensuring both performance and privacy.
4. Execution Layer: Performs AI training, inference, deployment, etc., with elastic scalability and high performance.

This layered design achieves a closed-loop process for the AI lifecycle from creation, distribution, invocation to incentivization.

The “certification” and profit distribution mechanism of AI assets

Sahara AI has proposed two key digital credentials:

• Receipt: Represents the ownership of AI assets by contributors, including information about the model creators, data providers, etc. It is non-transferable but can earn profit sharing.
• License: Represents the user’s access rights to a specific AI asset, which can take the form of a duration, full access, or API authorization.

For example: If you upload a set of data to train a model, the system will automatically give you a Receipt. The more the model is called, the more profit sharing you will receive. This mechanism gives value to every small contribution, breaking the old logic of “you feed the model with free data, they profit while you gain nothing.”

From developers to ordinary users: everyone can participate in Sahara AI

Whether you have programming skills or not, Sahara AI provides a path for participation:

• Technical developers: use SDK and API to develop agents and train models;
• Data contributors: Upload structured or unstructured data for model training;
• Enterprise users: purchase AI tools or API interfaces through the market to integrate into business processes;
• Ordinary users: Create personalized AI assistants using No-Code tools;
• Validators and governance participants: maintain the security of the public chain and participate in platform decision-making.

Sahara AI enhances ecological participation in breadth and depth through role division and incentive mechanisms.

Governance Mechanism: How do DAOs and Foundations Guide Platform Evolution?

In governance, Sahara AI has launched a “dual-track governance model”:

1. Sahara DAO: All contributors (holding receipts or tokens) can participate in proposals, voting, and resource allocation;
2. Sahara Foundation: Initially promoted the development of the key roadmap by the foundation, and gradually transferred it to DAO management to avoid centralization risks.

This governance model ensures the long-term sustainability of the platform and allows it to flexibly adjust its direction based on community consensus, freeing it from the constraints of traditional corporate structures.

Conclusion: Sahara AI is a key node in the integration of Web3 and AI.

What Sahara AI advocates is not just a technology platform, but a revolution of ideas.

• AI should not be controlled by a central authority, but rather belong to the whole society;
• Data is not a “sacrifice”, but an “asset”;
• Benefits should be shared by participants, rather than being centralized and deprived.

It is a landmark project that empowers AI through Web3 and may also become an important link in driving AI back to its original intention of “serving people.”