➥ @Mira_Network Core Ethical Framework There’re 3 things I really appreciate about how they approach ethics ↓↓↓ ✦ Hallucination Mitigation ▸multi-model consensus raises factual accuracy from ~70% to 96% in production test ▸reducing first-pass hallucinations to ~5% ✦ Bias Reduction ▸model diversity w economic disincentives prevents systemic bias that would arise from single-model oracles or centralized curation ✦ Privacy Preservation ▸ Prompt sharding ensures no single node can reconstruct user data while maintaining verification integrity I’m still exploring all the implications

The fact that @Mira_Network got hallucinations down to ~5% and factual accuracy up to 96% is wild. If AI is gonna be trusted infra, this is the path forward.

this is how we can trust Mira model ngl