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George Zeng explains NEAR’s approach to user-owned AI. Confidential inference keeps your data yours. IronClaw runs agents where secrets never reach the model. NEAR Intents settles across chains. Intelligence, execution, settlement. The full stack, and it answers to you.

148,625 просмотров • 5 дней назад •via X (Twitter)

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Ep. 20 | Free The Money | How NEAR Intents Fix DeFi UX In this episode, I sit down with Harshit Tiwari (chronear), Head of Ecosystem Strategy at the NEAR Foundation, to break down NEAR Intents, one of the fastest-growing cross-chain protocols. At its core, NEAR Intents allows users to seamlessly move assets across chains without needing to think about bridges, liquidity, or execution. Instead of manually swapping tokens, users simply express what they want (an “intent”), and a network of competing solvers executes the trade, optimizing for the best price and fastest settlement. A major innovation discussed is confidential intents, which bring privacy to on chain trading, something historically missing in crypto. This is especially critical for institutional adoption, where large players require discretion similar to traditional finance (e.g. dark pools). Looking ahead, Harshit predicts a major shift toward AI-driven economies, where autonomous agents transact on behalf of users. Within 12–18 months, AI agents could dominate on-chain activity, executing trades, payments, and real-world tasks through intent-based systems. NEAR is building toward: • Tokenized equities • An open-source AI stack — NEAR AI is already live today • A world where users own their data, not centralized platforms • And a model where ecosystem activity ultimately feeds back into value accrual for NEAR holders Sign up for ITrustCapitol with this link for $100 funding bonus. See why people are opening a tax-advantaged Crypto, Gold & Silver IRA for their future: If you’re being moved onto a platform you didn’t choose, with higher fees, there are better options. iTrustCapital gives you more control, better pricing, and now a limited time 2% match to make the move even more compelling. 00:00 Intro: NEAR = Universal Transaction Layer for AI Economy 01:00 What Are NEAR Intents? (Fixing Cross-Chain Fragmentation) 02:26 Confidential Intents: Bringing Privacy to On-Chain Trading 04:50 Institutional Adoption Is Already Here (What Changes Next) 05:38 Chain Abstraction + User-First UX (Why This Wins) 06:32 Competing with Coinbase & Binance UX (DeFi’s Big Unlock) 06:58 iTrustCapital Ad (Gold, Crypto, IRA Strategy) 08:00 Why CEX UX Still Dominates (and How NEAR Fixes It) 09:35 One Interface for Everything: The NEAR “Super App” Vision 10:13 Intents = Decentralized Fiverr (Solvers Compete for Best Price) 11:24 AI Agents Will Transact More Than Humans (12–18 Months?) 13:10 Decentralized AI vs Big Tech (Who Controls Your Data?) 14:24 NEAR AI: User-Owned, Open-Source, Verifiable AI 15:54 NEAR Tokenomics: Value Accrual + Buybacks Explained 17:37 Deflationary Token Model (Why Supply Could Shrink) 18:19 Stocks & Commodities Coming to NEAR Intents 20:29 “Trillions of AI Agents” Thesis Explained 22:43 Regulation, AI, and Working With Governments

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Perplexity CEO Aravind Srinivas on the biggest threat to the data center industry: It's not competition. It's not regulation. It's decentralisation. "The biggest threat to a data center is if the intelligence can be packed locally on a chip that's running on the device and then there's no need to inference all of it on like one centralized data center." He outlines how this could work in practice. Personalisation doesn't necessarily require on-device model training. Retrieval augmented generation, tool calls, and local data can already tailor AI to individual users. But the real unlock? Test time training. Aravind Srinivas describes a future where AI lives on your device, watches how you work and gradually automates your repetitive tasks. "Imagine we crack test time training where the AI watches tasks you repeatedly do on your local system, adapts to you over time and starts automating a lot of the things you do." The key insight: in this model, the intelligence belongs to you. It's your data, your device, your personalised AI brain. And if that future arrives, the economics of centralised infrastructure start to collapse. "That really disrupts the whole data center industry. It doesn't make sense to spend all this money, 500 billion, 5 trillion, whatever on building all the centralized data centers across the world that do a lot of the intelligence workloads for people." The companies spending trillions on centralised infrastructure may want to rethink where intelligence actually needs to live.

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