A hospital trusted AI to recommend doctors.

It hallucinated a specialist who didn’t exist.
Here’s how one error delayed treatmentand how networks like miraprotocol.twitter are building the fix👇

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In 2022, a hospital in Brazil piloted an AI assistant for triaging patients.
The system was supposed to match cases with the right specialists.
One critical case needed an urgent neurologist referral.

The AI offered a name
Dr. Felipe Duarte. Based in São Paulo. Specialized in rare brain infections.
All seemed fine until the patient’s family tried to reach out.

No clinic. No registration. No medical license.
Turns out: the AI hallucinated the entire doctor.
Name, specialty, clinic all made up from fragments of unrelated data.

The patient’s treatment got delayed by 3 days.
That delay wasn’t just inconvenient. It caused permanent nerve damage.

No one saw it coming because the AI sounded confident.

With Mira, LLMs don’t just generate answers.
They prove them by routing through verified sources, and cross-checking with real data in real time.

It’s AI that doesn’t guess. It confirms.

So what’s the solution?
Enter miraprotocol.twitter building a verifiable AI infrastructure.
Think: intelligent query routing + real-time validation + a trust layer that catches fakes before they spread.

This isn’t a one-off glitch.
Hallucinations happen when models don’t verify what they generate.
They pull from patterns, not truth.

And in high-stakes fields like healthcare or finance, that’s a recipe for disaster.