[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  Milad đ [@0xMiladx0](/creator/twitter/0xMiladx0) on x 4510 followers Created: 2025-07-26 03:15:10 UTC If you want AI systems to be truly trustworthy, algorithms arenât enough. You need to make honesty economically rational. Hereâs how Mira redefines verification through a cryptoeconomic blend of PoS and PoW. A deep dive @Mira_Network doesnât use classical PoW (i.e. energy-intensive hashing). Here, work = AI verification: answering structured questions like Is this claim supported by the source text? But the tasks are multiple choice which means random guessing is statistically viable. Thatâs where PoS and slashing come in. To participate, nodes must stake value. If they submit low quality or deviant answers, theyâre slashed. Random guessing becomes an economically irrational strategy. Only consistent, evidence based verification survives. Miraâs rollout progresses in X security phases: 1ď¸âŁ Curated nodes with manual vetting 2ď¸âŁ Redundant verification same task, different nodes 3ď¸âŁ Random sharding unpredictable assignment across the network Together, these resist collusion and scale trust. But #mira doesnât stop at defense. It optimizes for efficiency. Nodes running smaller, cheaper models if accurate earn proportionally higher rewards. This incentivizes precision + cost efficiency, not brute force. As adoption grows: ⢠Reward flows increase ⢠Stake thresholds rise ⢠Verification diversity expands ⢠Attack surfaces fragment ⢠Anomaly detection improves All reinforcing a singular goal: a scalable trust layer for AI inference. Miraâs insight is clear: Trust in AI doesnât emerge from architecture alone. It comes from economic structures that reward truth and penalize manipulation by design, not policy. #Mira is trust engineered into consensus.  XXX engagements  **Related Topics** [$raade](/topic/$raade) [coins ai](/topic/coins-ai) [if you](/topic/if-you) [Post Link](https://x.com/0xMiladx0/status/1948945158784815410)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
Milad đ @0xMiladx0 on x 4510 followers
Created: 2025-07-26 03:15:10 UTC
If you want AI systems to be truly trustworthy, algorithms arenât enough. You need to make honesty economically rational. Hereâs how Mira redefines verification through a cryptoeconomic blend of PoS and PoW. A deep dive
@Mira_Network doesnât use classical PoW (i.e. energy-intensive hashing). Here, work = AI verification: answering structured questions like Is this claim supported by the source text?
But the tasks are multiple choice which means random guessing is statistically viable.
Thatâs where PoS and slashing come in.
To participate, nodes must stake value. If they submit low quality or deviant answers, theyâre slashed. Random guessing becomes an economically irrational strategy.
Only consistent, evidence based verification survives.
Miraâs rollout progresses in X security phases: 1ď¸âŁ Curated nodes with manual vetting 2ď¸âŁ Redundant verification same task, different nodes 3ď¸âŁ Random sharding unpredictable assignment across the network
Together, these resist collusion and scale trust.
But #mira doesnât stop at defense. It optimizes for efficiency.
Nodes running smaller, cheaper models if accurate earn proportionally higher rewards. This incentivizes precision + cost efficiency, not brute force.
As adoption grows: ⢠Reward flows increase ⢠Stake thresholds rise ⢠Verification diversity expands ⢠Attack surfaces fragment ⢠Anomaly detection improves
All reinforcing a singular goal: a scalable trust layer for AI inference.
Miraâs insight is clear: Trust in AI doesnât emerge from architecture alone. It comes from economic structures that reward truth and penalize manipulation by design, not policy.
#Mira is trust engineered into consensus.
XXX engagements
