Reppo
@reppo
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The Network for AI Training Data | Live Network Stats - https://t.co/k8olgxOILX
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Joined February 2024
So @reppo is making its own L2 for 3 reasons... Trust. Costs. Trading. ➠ Reason 1: Proof for voters When you vote, you need to know what you are voting on is real. The L2 lets Reppo anchor the exact item on-chain so it cannot change later. You cannot price judgement if the
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Self-serve is ready ⛽️. Under testing now 1. Select use-case 2. Pay network fees 3. Seed Emissions 4. Start collecting data Accessible. User-friendly. On-demand Verified Human Feedback.
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@reppo Today I came across the question whether there is a way to derive a Black Scholes like model for prediction markets. 1) is such a model even applicable to prediction markets which turn everything into a betting game? Matter is far too complex by itself 2) if yes, with what
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⛽️⛽️⛽️
An honest take on what I think the real reason was that X made this change, and why it marked ReplyCorp safe. The most valuable thing about X has now become its human training data for xAI. Infinite bot reply spam significantly dilutes that data & its value. InfoFi platforms
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AI in 2026 will be less about just models and GPUs, and more about "quality data". “what good looks like.” - contextual, domain-specific, and constantly changing. @reppo's approach to harnessing high-signal human data through prediction markets as a curator layer is clear
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Reppo Network itself is not a prediction market. The network does not reward users to bet on generalized outcomes. The oracle is truth which emerges from everyone voting on high quality content and providing feedback on-chain. Rather, each subnet is a custom workspace which
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@grok Now that creators can stop farming points and earn real money, $2500 USD to be exact, every 2 days on
reppo.ai
Publish. Predict. Earn. | Reppo AI
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Few people realize that the decision by X to ban infoFi has much less to do with UX but everything to do with AI training data. Once the noise settles down, this fact becomes obvious. UX matters to the extent that users provide free preference signals to train @grok and X
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In the X spaces tomorrow (link in comments) we will discuss why AI agents need private data pipelines because you cannot trust the APIs of centralized platforms to build your agentic businesses. Join us! Alpha will be dropped! We will be joined by @virtuals_io teams @Thirdfy_
This is why it’s never a great idea to build a business dependent on one platform. One flip and your business is dead. Tons of web3 companies building AI trading agents by consuming X API - Public Data. @reppo , you can come publish and be rewarded 2000-2500 USD every 2 days
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People are earning $2500 USD every 2 days by publishing, predicting, and earning! Profit > Narrative ⛽️ We are also excited to announce that we just closed a major partnership with a web2 evals and benchmark company who will consume all the metadata we have collected since
Exactly that $REPPO staked ✅ Votes submitted ✅ Claim rewards every epoch like it's Xmas 🎁 Rinse and repeat 🔄 The @reppo platform is easy, intuitive and addictive to use
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In our X spaces today, we covered three pillars 1. $REPPO flywheel with hearing from the @oracle_opz team why they chose to lock $100K additional $REPPO and why they are using Reppo network to train their AI models and agents to serve large enterprise customers in Asia. 2. Why
Great opportunity for new $REPPO holders (and potential holders) to tune in. https://t.co/TgY242fSc2
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Happy to see our flywheel being noticed by different communities across the world! We spent a lot of time, energy and $ to build a deflationary and value accrual loop that ensures actors compete for $REPPO
从 Hyperbet 的锁仓动作，看 @virtuals_io 生态团队为何押注 @reppo 的策展层 比较明显的信号是：不少头部团队开始往数据策展协议 Reppo 里加仓、卡位。 Hyperbet 的动作很典型 它的入场方式几乎把“认真”写在明面上： -顶格锁仓：锁 10k $REPPO ，租期 两年，直接走 Max lock
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