An increasingly important perspective is that the true value of AI on the chain does not depend on the size of the model parameters, but on whether the data is trustworthy and whether the results are verifiable.

@bluwhaleai provides its answer to this critical question. Bluwhale focuses on combining real data, AI inference, and on-chain verification, so that AI is not just about outputting conclusions, but can be traced back, evaluated, and incentivized.

By integrating data contributors, model executors, and users into a unified mechanism, the platform aims to establish a sustainable collaborative network rather than a one-way consumption of computing power or data.

In the longer term, $BLUAI carries not only payment or governance functions but also acts as the core incentive for the entire network collaboration.

It creates a closed loop of data provision, model operation, and result verification, giving AI behavior economic constraints and on-chain transparency.

This design does not pursue short-term popularity but lays the foundation for the long-term application of AI in Web3 scenarios.

If AI on the chain is to truly enter high-trust scenarios such as finance, content, and decision-making in the future, paths like Bluwhale that emphasize real data and verifiable reasoning may become particularly important.

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@Bantr_fun @easydotfunX