The strength of a smart contract depends on how truthful the data it consumes is. This is a harsh reality facing the entire blockchain industry.

Imagine this: no matter how perfect the transaction logic is, if it encounters tampered price sources, false event results, or delayed market data, it can instantly become the source of disastrous decisions. Traditional oracle design is like single-point communication—once that line is compromised, all connected applications fall apart.

Now, some projects are approaching this problem from a different angle. Instead of relying on a single information source to make decisions, they build a "Data Parliament" architecture: multiple independent data sources compete in real-time, node networks cross-verify each other, and finally, the data must pass AI risk control checks. Only data that passes all three layers of filtering is integrated into the blockchain. The logic behind this approach is pure—it’s not just about transmitting data, but about filtering out information that can withstand scrutiny.

On a technical level, two key aspects of this solution are worth noting. One is AI acting as the "gatekeeper"—identifying market manipulation techniques in real-time, detecting abnormal fluctuations, and automatically switching data channels when attacks occur. This shifts attacks on or against oracles from "low risk, high reward" to "high risk, difficult to execute."

The other is fully on-chain verifiable random numbers. Whether for NFT generation, blockchain game draws, or DAO voting, the entire randomness process runs on-chain, making the results tamper-proof and traceable, with every participant able to verify the process clearly.

From this perspective, whether the next phase of blockchain applications can truly run stably may hinge on this data channel.