I spent 3 hours last weekend fact-checking an AI "research report" for a trade. Turns out half the sources were hallucinated. We laugh about AI mistakes, but when you're putting real capital on the line? Not funny.
That's why I've been tracking @Mira - Trust Layer of AI closely.
Most people think AI verification means "run it through another AI." Mira does something smarter they break claims into atomic pieces and force consensus across independent models with economic stakes. Blockchain isn't just the ledger here; it's the enforcement mechanism. Wrong answers cost you money. Right answers earn trust.
The $MIRA tokenomics actually make sense: validators stake to participate, get slashed for bad verification, rewarded for catching errors. It's prediction markets meets AI auditing.
What hooked me was realizing this isn't just about "safer ChatGPT." Autonomous agents handling real transactions insurance claims, supply chain proofs, on-chain oracles need this layer. Without cryptographic verification, we're trusting black boxes with treasury functions.
I've seen three "AI x Crypto" projects this month. Most slap a token on inference costs and call it decentralized. Mira's approach consensus through verification, not just distribution feels like actual infrastructure.
Still early. Mainnet gaps exist. But the direction is right: don't trust the model, trust the math.