CAN I GET A GM ? Bullish on @OpenledgerHQ @JoinSapien | zeliscalls on Binance Square

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CAN I GET A GM ?
Bullish on @OpenledgerHQ @JoinSapien

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AI revolution is not won just by big models; it is won by the people who train them @JoinSapien It's a Web3 crowdsourcing infrastructure ➡️ a protocol that works for humanity, not AI. Real human input, trained on real data. Global Players ➡️ 1M+ Countries ➡️ 110+ Tasks Completed ➡️ 110M+ Those contributing now are building the foundation for tomorrow's most valuable AI.

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Friends, The integration of artificial intelligence into Web3 is still on the surface. @recallnet gets to the core of the game: Let's examine this revolution in detail: 👇 Recall is building a decentralized memory layer for AI agents. What does this mean? A network of AI agents that access on chain data -prove their contribution on chain - and earn rewards based on their contribution What is in the infrastructure? ✅ Recall Coprocessor → Provides on chain evaluation of agents. ✅ Recall SDK → Tools to quickly develop and deploy AI agents. ✅ Agent Arena (AlphaWave) → Evaluation arena where agents compete on a task basis. The main problems that Recall is trying to solve: • Off chain data and AI models are unverifiable • Not rewarding AI contributions • AI processes revolve around centralized structures The solution: A modular, open, points based network. Testnet is currently active, I will share information about it, I would be happy if you support me. 🧡

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Friends, The integration of artificial intelligence into Web3 is still on the surface. @recallnet gets to the core of the game: Let's examine this revolution in detail: 👇 Recall is building a decentralized memory layer for AI agents. What does this mean? A network of AI agents that access on chain data -prove their contribution on chain - and earn rewards based on their contribution What is in the infrastructure? ✅ Recall Coprocessor → Provides on chain evaluation of agents. ✅ Recall SDK → Tools to quickly develop and deploy AI agents. ✅ Agent Arena (AlphaWave) → Evaluation arena where agents compete on a task basis. The main problems that Recall is trying to solve: • Off chain data and AI models are unverifiable • Not rewarding AI contributions • AI processes revolve around centralized structures The solution: A modular, open, points based network. Testnet is currently active, I will share information about it, I would be happy if you support me. 🧡

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Friends, The integration of artificial intelligence into Web3 is still on the surface. @recallnetwork gets to the core of the game: Let's examine this revolution in detail: 👇 Recall is building a decentralized memory layer for AI agents. What does this mean? A network of AI agents that access on chain data -prove their contribution on chain - and earn rewards based on their contribution What is in the infrastructure? ✅ Recall Coprocessor → Provides on chain evaluation of agents. ✅ Recall SDK → Tools to quickly develop and deploy AI agents. ✅ Agent Arena (AlphaWave) → Evaluation arena where agents compete on a task basis. The main problems that Recall is trying to solve: • Off chain data and AI models are unverifiable • Not rewarding AI contributions • AI processes revolve around centralized structures The solution: A modular, open, points based network. Testnet is currently active, I will share information about it, I would be happy if you support me. 🧡

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Good night friends Sapien Snap Update @cookiedotfun 🔸 Mindshare: 1.1% 🔸 Sentiment score: +7.03K 🔸 Total distributed Snaps: 3.9K+ 🔸 My Snaps: 6.85 🔸I'm ranked 72 👀➡️ top 50 Total 10K User ➡️ Total supply 0.5 @JoinSapien

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