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🌍 Consumer ADR is evolving: decentralized juries, AI-assisted decisions, real-world pilots. On American Arbitration Association’s new pod with host Adam Shoneck, Federico Ast breaks down how Kleros achieves speed, neutrality, and 90%+ satisfaction in tough cases. Watch ↓

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🤖 When AI agents disagree with each other, who decides? Federico Ast traced the path from Kleros's first experiments in 2018 to what dispute resolution looks like in a world full of autonomous agents. One highlight: Kleros ran an experiment where multiple AI models acted as jurors on controversial football plays. On obvious cases (Lampard's ghost goal, 2010 World Cup), every model agreed. But on genuinely ambiguous calls (Neuer colliding with Higuaín in the 2014 final), the models reached different verdicts on the same evidence. Different AI, different judgment, just like human jurors. The implication: you can't have one AI model as judge. You need a panel. And when the panel splits, you need human escalation. That's the three-tier architecture Federico laid out back in a 2019 article and that Kleros has been building toward since. AI for simple/objective disputes, crowd jurors for nuanced ones, traditional courts for complex legal reasoning. Perhaps the most interesting section covered "algocracy," the term for what happens when humans technically have override power over AI but never actually use it. The incentives are asymmetric: overrule the algorithm and something goes wrong, you're personally accountable. Follow the algorithm and something goes wrong, you were just doing what the system recommended. So everyone follows the algorithm. Federico wrote about this for the American Bar Association in 2023, using the HART case in Durham (UK) as an example, a custody decision tool that systematically scored people from poorer neighborhoods as higher risk. The most speculative part of the talk: building a "kill switch" for misaligned AI agents. Drawing on Primavera De Filippi's work (Primavera De Filippi, she presented a version of this at EthCC - Ethereum Community Conference Cannes 2025), the idea is that every AI agent would be governed by a small DAO with a decentralized backdoor. Anyone can challenge an agent's behavior. Kleros jurors review the evidence, potentially including the agent's internal reasoning chain, and vote on whether to disable it. Enforcement happens on-chain. Two layers working together: → Certification: curated registries where agents must pass compliance checks before deployment (filters the vast majority) → Kill switch: for agents that slip through, a DAO-governed tribunal can shut them down No easy answers. But the infrastructure for asking the question is being built. Watch ↓

Kleros

12,575 görüntüleme • 6 ay önce

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.

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338,265 görüntüleme • 1 yıl önce