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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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Kleros

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120,418 просмотров • 10 месяцев назад •via X (Twitter)

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🤖 What happens when you hand the same legal case to five different AIs? They disagree. at almost exactly the same rate human jurors do. That's one the findings in the new chapter Federico Ast, William George, and Robert Dean just published in AI and Arbitration (Wolters Kluwer, 2026), "When Decentralised Justice Meets Artificial Intelligence." 63 real Kleros disputes, judged by five frontier LLMs from: ChatGPT, Claude, Gemini, DeepSeek, Mistral. The takeaway isn't which model judges best. It's that you shouldn't trust a monolith AI. Round 2 of the experiment is already in flight: the team is re-running the test on real-world consumer cases from Argentina's Junín pilot and Lemon, where early evidence suggests the AIs and human jurors come to different conclusions on the same cases. Book details below ↓
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🤖 What happens when you hand the same legal case to five different AIs? They disagree. at almost exactly the same rate human jurors do. That's one the findings in the new chapter Federico Ast, William George, and Robert Dean just published in AI and Arbitration (Wolters Kluwer, 2026), "When Decentralised Justice Meets Artificial Intelligence." 63 real Kleros disputes, judged by five frontier LLMs from: ChatGPT, Claude, Gemini, DeepSeek, Mistral. The takeaway isn't which model judges best. It's that you shouldn't trust a monolith AI. Round 2 of the experiment is already in flight: the team is re-running the test on real-world consumer cases from Argentina's Junín pilot and Lemon, where early evidence suggests the AIs and human jurors come to different conclusions on the same cases. Book details below ↓

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27,288 просмотров • 2 месяцев назад

⚖️ Kleros Community Call Recap | April 30, 2025 ⚖️ ⚙️ Mechanism Design Conference in London ▸ William George and Federico Ast presented at a one-day conference with academic researchers and practitioners ▸ Conference focused on mechanism design and decentralized justice ▸ Key panels included: ▸▸ Social choice theory (optimizing voting systems for non-binary options) ▸▸ AI's role in centralized justice ▸▸ SBT blockchain identity tools integration with decentralized justice ▸ Video of the conference expected to be shared soon 🇬🇧 Legal Tech Workshop at King's College ▸ Workshop for legal tech founders on using frontier technologies ▸ Focused on AI and blockchain applications for dispute resolution ▸ Similar to workshops Federico conducted in Central America earlier this year 💻 Technical Updates & Development ▸ Scout Incentive Program Updates, updates by Fortunato A. Cinquepalmi ▸ Two rewardable chains added back: Arbitrum 1 and optimism.eth ▸ Partnership with MetaMask.eth 🦊 and etherscan.eth for sharing contract metadata ▸ New website field added for tokens at Etherscan's request ▸ Policy changes are not retroactive for previously submitted entries ▸ Submission and challenge deposit amounts remain unchanged ▸ Work ongoing on new version of Kleros Curate with permanent deposits for vaults ▸ Audits for proxies to enable cross-network dispute resolution 🔐 Escrow Solutions ▸ Multiple solutions in development: Kleros Escrow V2 using Kleros V2 beta on Arbitrum ▸ Escrowly interface for escrow on V1 ▸ Lockler: new solution by Guangmian Kung using SafeSnap ▸ Partner integrations including Smart Invoice (used by DAOs) and paydeceP2P (P2P platform more active in Latin America) 🌎 Real-world Use Cases & Partnerships Argentina Initiatives ▸ Major insurance company integration: First dispute resolved 2-3 weeks ago with positive feedback ▸ Second case in progress, on Arbitrum ▸ Potential for high volume of cases in the future ▸ Confirms Kleros can solve real-world disputes ▸ Lemon (Argentinian fintech) cases: 15-16 cases being prepared with evidence and justifications ▸ Cases to be created before end of next week ▸ Ombudsman Recognition: Advanced discussions with [redacted] ▸ Would allow Kleros to resolve consumer disputes ▸ Potential for implementation in other jurisdictions 👥 Team Updates ▸ New Dev Rel joined the team to handle documentation, dev relations and updates ▸ First Developers Office Hours next week! Listen to the call below 👇
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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 ↓

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1/ BREAKING – DePIN's Biggest New Deal: Valeo x NATIX Network with Alireza Ghods Host: Connor Lovely 🎬 We discuss: - Why a $3B, Fortune 500 company wants Natix data - What is a World Foundational Model? - Why autonomous driving needs synthetic data Timestamps: 00:00 - Introduction 01:14 - Updates on VX360 and Data Sales 02:09 - Vision Language Model and Its Applications 04:39 - Importance of Diverse Data for World Models 06:20 - Details on the Valeo Deal 08:15 - Use Cases and Future Plans for World Models 10:45 - Synthetic Data and Real-World Applications 19:37 - Future of Physical AI and Autonomous Driving 23:51 - Conclusion Watch on other platforms below ⬇️
25:05

1/ BREAKING – DePIN's Biggest New Deal: Valeo x NATIX Network with Alireza Ghods Host: Connor Lovely 🎬 We discuss: - Why a $3B, Fortune 500 company wants Natix data - What is a World Foundational Model? - Why autonomous driving needs synthetic data Timestamps: 00:00 - Introduction 01:14 - Updates on VX360 and Data Sales 02:09 - Vision Language Model and Its Applications 04:39 - Importance of Diverse Data for World Models 06:20 - Details on the Valeo Deal 08:15 - Use Cases and Future Plans for World Models 10:45 - Synthetic Data and Real-World Applications 19:37 - Future of Physical AI and Autonomous Driving 23:51 - Conclusion Watch on other platforms below ⬇️

Proof of Coverage | Tech’s Creative Agency

11,869 просмотров • 6 месяцев назад

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.
49:12

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.

Mario Nawfal

338,265 просмотров • 1 год назад

🚨AI IS MORE DANGEROUS THAN NUKES AND NO ONE IS IN CONTROL Most people compare AI to nuclear weapons. Roman Yampolskiy says that comparison misses the real danger. Nukes still require human decisions. Someone has to launch them. Someone can stop them. Advanced AI does not work that way. Once powerful systems are deployed, they make decisions on their own. And the people who build them do not truly control what happens next. He says we did the opposite of what safety demanded. Instead of slowing down, we connected AI to the internet, open sourced it, and pushed it forward in an arms race with no serious oversight. Governments talk about regulation, but most of it never materialized. In some cases, rules were blocked before they even started. Yampolskiy’s warning is simple. With nukes, the world tried to limit the damage. With AI, we are accelerating toward something we may not be able to stop. Full conversation with Dr. Roman Yampolskiy below
2:41

🚨AI IS MORE DANGEROUS THAN NUKES AND NO ONE IS IN CONTROL Most people compare AI to nuclear weapons. Roman Yampolskiy says that comparison misses the real danger. Nukes still require human decisions. Someone has to launch them. Someone can stop them. Advanced AI does not work that way. Once powerful systems are deployed, they make decisions on their own. And the people who build them do not truly control what happens next. He says we did the opposite of what safety demanded. Instead of slowing down, we connected AI to the internet, open sourced it, and pushed it forward in an arms race with no serious oversight. Governments talk about regulation, but most of it never materialized. In some cases, rules were blocked before they even started. Yampolskiy’s warning is simple. With nukes, the world tried to limit the damage. With AI, we are accelerating toward something we may not be able to stop. Full conversation with Dr. Roman Yampolskiy below

Mario Nawfal

24,888 просмотров • 6 месяцев назад