Séances Vibe : Épisode 1 | Metis L2 sur Binance Square

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Séances Vibe : Épisode 1

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⏳One day left for the HyperHack Spotlight Campaign⏳ Final call for HyperHack teams to grab $500 in free marketing budget and a shot at $7500 in bonus rewards. Don’t leave help and money on the table. Apply now👇 https://f.mtr.cool/myqvrcbhqg

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💡Tek Made Simple💡 How to build low cost AI dApps with MetisVM’s gas optimization strategies? MetisVM is being developed for AI, high frequency trading, and realtime dApps. It keeps Ethereum compatibility while unlocking faster, cheaper, and smarter onchain execution. Gas optimization techniques: 🔵 Dynamic Opcode Repricing: Gas costs adapt to actual execution patterns, cutting waste without needing code changes 🔵 Speculative Execution: Transactions are processed ahead of confirmation and safely rolled back if needed, increasing throughput 🔵 Parallel Execution: Non-conflicting transactions run in parallel, allowing for much higher speed than traditional EVM 🔵 State Aware Caching: Contract state is cached during execution to avoid repeated storage reads and reduce gas Purpose-built for onchain AI: 🟣 Inference Precompiles: Special contract types support fast and efficient model execution onchain 🟣 Batched Inference Support: Multiple inference calls can be bundled into one transaction to save cost and improve responsiveness 🟣 zkVM Integration Ready: The architecture supports future integration with zero knowledge systems for verifiable AI Hyperion with MetisVM will bring Web2 level speed and responsiveness to the onchain world. Developers can start to build AI agents, trading bots, and realtime games that run fully onchain with low cost and high performance. 💡

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Private Data Inference using LazAI computing API

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🛠️ As we pass the midway point of the HyperHack, builders are showing what’s possible on Hyperion Testnet. From AI-native games to crypto-fluent agents and autonomous governance tools. Explore the latest community standouts: https://f.mtr.cool/webgdrifik

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ICYMI: Watch the full dev workshop on how to build an AI Agent using RAG with memory on the Hyperion Testnet. Watch the full session here: https://f.mtr.cool/ouilvqkftj

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