Do you know what's the scariest thing? It's not that AI doesn't understand, but that it can use a 100% certainty tone to make something that doesn't exist at all sound like it's real. Now that AI agents driven by large language models are starting to get involved in financial trading and asset management, this "illusion" problem is no longer just a funny quirk of chat software—it can directly eat up your money.

Traditional oracles only verify where the data comes from, but the new generation of oracles go even further. They need to verify the logic of the content itself. For example, if an AI agent needs to analyze a real estate valuation report, the new oracle won't just trust the output of a single model. It will take the key data extracted by AI—such as property valuation, audit time—and compare it with public databases and historical prices.

Imagine this: AI says a property is worth 500 million, but historical data and surrounding property prices show it's actually only 5 million? The oracle network will immediately raise an alert and directly reject this result.

This multi-model consensus mechanism combined with external data cross-verification effectively equips AI agents with a "reality check" system. It forces AI to pass through node network validation before every decision. This way, financial decisions are insured.