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When it comes to high-stakes AI (medical, finance, etc), what would help you trust it the most?
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🚀 ARPA Network Spring Progress Highlights are here! This season, we: • Expanded our ecosystem with integrations across @carv_official, @SonicSVM, @awenetwork_ai, @soon_svm, @SoloDePIN, @GPTWars & more • Launched @eigenlayer AVS Restaking Season 4 • Drove new partnerships and community milestones in Turkey & Dubai • Advanced thought leadership in verifiable AI, privacy, and cryptography Read the full report for all the details and what’s next👇
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Why does verifiable machine learning matter in today's AI-driven world? 🔐 In our latest article, we break down how zkML is solving AI's growing trust problem and why it’s essential for Web3, policy, and beyond. 🧠 Read now: https://arpa.medium.com/why-verifiable-machine-learning-matters-in-todays-ai-landscape-ac521c66164e
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Here’s what we’re optimizing for in verifiable AI: ✅ Prover time < model run time ✅ Verifier time = instant ✅ Model remains private ✅ Output is provably valid The end game: trustless AI that performs and proves.
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In Web3, trustworthy trustlessness is king 👑
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ZK for AI doesn’t mean running the model in ZK You don’t need to prove the entire model execution You just need to prove the result came from the correct model That’s a huge difference, and where the speedup comes from 🧠⚡
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