
Fortunato A. Cinquepalmi
263 posts

Fortunato A. Cinquepalmi
@fortuvp
Product M. @Kleros_io @KlerosCurate . Making world safer with decentralized justice.









Binance Alpha will be the first platform to feature R2 Protocol (R2) on March 30. Eligible users can claim their airdrop using Binance Alpha Points on the Alpha Events page once trading opens. Further details will be announced soon. Please stay tuned to Binance’s official channels for the latest updates.

We are still seeking clarity on the path forward for RLP from @ResolvLabs - The Resolv Collateral Pool was not impacted by the exploit - Any use of this collateral must align with the stated Terms and be fair to RLP holders - DeFi markets are not covered by the Terms Therefore, it is unclear to us why RLP redemptions have not yet reopened. We remain optimistic that the collateral pool will not be repurposed to support third parties in a manner contrary to the Terms.

Yearly repost and reminder that an unspecified government agency proactively takes this video down from Youtube all the time




🤖 ERC-8004 is here! Who's coming to the launch event? We have lots of ideas to share with @KlerosCurate ↓






Proud to present our new release! github.com/openscan-explo… Introduces proxy contract detection, @Kleros_io verified tags, @etherscan as a parallel verification source, auto RPC sync by latency, skeleton loaders, breadcrumb navigation, and a range of accessibility and UX improvements. Already in production!

🍿 Can you scale a movie critic? That's the question behind Kleros Foresight's first experiment. 16 movies, 1 judge: Kleros CTO @clesaege. Judge Dredd, Mamma Mia, 12 Angry Men, Barbie... all in the same pool. For each film: "If Clément watches this, what percentile score will he give it?" Slide a prediction higher or lower than the crowd. Closer to reality, you profit. Off, you lose. The twist: Clément won't watch all 16. Only 5 get evaluated. The top 3 by market estimate (the crowd literally decides what's worth watching), plus 1 random and 1 Clément's choice. The other 11 redeem at neutral. No profit, no loss. This is "distilled human judgement" in action. One person's taste is the ground truth, but invoking it (watching + rating a film) is slow and expensive. So the market predicts across all 16, only 5 get verified, and accurate predictions earn. The result: a recommendation signal that scales without the critic needing to watch everything. Movies are session 1. The same architecture works anywhere expert judgement exists but doesn't scale: property appraisals, grant allocation, content curation. Built on @SeerPM and @GnosisChain.
