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Velvet isn’t simply another DeFi tool it’s an execution layer designed for humans and AI. → DCA orders that help minimize price impact on low liquidity assets → Intent-driven swaps across multiple chains → Non-custodial, real time analytics to identify strong performers early I’ve been using Velvet | Onchain...

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Damian

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27,502 Aufrufe • vor 5 Monaten •via X (Twitter)

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I find it fascinating how Opulous is using AI to quietly reshape how music is created, marketed, and monetized. It’s not just one tool , it’s an ecosystem where each layer compounds the next. Take Wippit AI, for example. Instead of artists guessing what to post or how to grow, Wippit analyzes past content, audience behavior, and engagement patterns to guide smarter promotion decisions. That adaptability is a huge shift from static marketing tools that don’t learn or evolve. Then there’s Opulous music-first DeFi layer. By connecting on-chain infrastructure to real-world streaming data, Opulous enables transparent royalty tracking and automated payouts. This bridge between static music rights and live performance data is what makes the model sustainable, not speculative. On the creator side, MFTs (Music Fungible Tokens) unlock a new financing model entirely. Artists can raise capital without labels or debt, while fans gain exposure to real revenue streams. It’s a system designed around alignment , creators grow, supporters earn, and the platform scales organically. What really stands out is how AI, DeFi, and music IP converge into a single workflow: • AI helps artists grow • DeFi helps artists fund • Blockchain ensures trust and transparency Each component alone is powerful. Together, they’re disruptive. Of course, building systems like this isn’t trivial. It requires deep understanding of music rights, data pipelines, AI modeling, and financial infrastructure. That’s why Opulous isn’t moving fast for hype , it’s moving deliberately for longevity. And the real-world impact is already visible. Artists gain control. Fans gain access. Royalties become programmable, not opaque. Whether you’re an artist looking for independence, a fan seeking real utility, or someone exploring how AI can power real-world assets, Opulous offers a blueprint that goes beyond theory. This is what happens when technology is built for creators, not platforms. And we’re still early. $OPUL #opulous

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💡 Whats the upgrade that our game-changing Trading 🐦 is going to get: Our upgraded trading tools will be built on a foundation of advanced AI technologies and blockchain integrations to deliver a seamless, smarter trading experience. Here’s a glimpse of the tech behind this upgraded trading agent: 1️⃣ Multi-Layer Attention (MLA) - This is the backbone of our AI system, enabling multiple AI agents to work in sync. - It allows the agents to collaborate on tasks like analyzing market trends, identifying token opportunities, and optimizing strategies in real time. - MLA ensures parallel processing of data for better decision-making and faster 2️⃣ Learning and Evolution System - Our AI agents are powered by a self-learning framework that constantly evolves based on market conditions and user behavior. - With every interaction, the system adapts and gets smarter, improving the accuracy of its predictions and strategies. 3️⃣ On-Chain Data Analysis - The AI bots pull data directly from Ethereum and other blockchain networks, giving them real-time access to liquidity pools, token prices, and market activity. - This deep integration ensures precise and timely execution of tasks like token purchases, profit analysis, and cross-chain swaps. 4️⃣ Natural Language Processing (NLP) - NLP models power the bot’s ability to understand your tweets and translate them into complex trading actions. - This ensures an easy-to-use, human-friendly interface that connects your social interactions to advanced trading strategies. 5️⃣ Cloud-Hosted Infrastructure - The AI operates on scalable cloud infrastructure, ensuring 24/7 uptime, fast processing, and the ability to handle large volumes of trades simultaneously.
0:51

💡 Whats the upgrade that our game-changing Trading 🐦 is going to get: Our upgraded trading tools will be built on a foundation of advanced AI technologies and blockchain integrations to deliver a seamless, smarter trading experience. Here’s a glimpse of the tech behind this upgraded trading agent: 1️⃣ Multi-Layer Attention (MLA) - This is the backbone of our AI system, enabling multiple AI agents to work in sync. - It allows the agents to collaborate on tasks like analyzing market trends, identifying token opportunities, and optimizing strategies in real time. - MLA ensures parallel processing of data for better decision-making and faster 2️⃣ Learning and Evolution System - Our AI agents are powered by a self-learning framework that constantly evolves based on market conditions and user behavior. - With every interaction, the system adapts and gets smarter, improving the accuracy of its predictions and strategies. 3️⃣ On-Chain Data Analysis - The AI bots pull data directly from Ethereum and other blockchain networks, giving them real-time access to liquidity pools, token prices, and market activity. - This deep integration ensures precise and timely execution of tasks like token purchases, profit analysis, and cross-chain swaps. 4️⃣ Natural Language Processing (NLP) - NLP models power the bot’s ability to understand your tweets and translate them into complex trading actions. - This ensures an easy-to-use, human-friendly interface that connects your social interactions to advanced trading strategies. 5️⃣ Cloud-Hosted Infrastructure - The AI operates on scalable cloud infrastructure, ensuring 24/7 uptime, fast processing, and the ability to handle large volumes of trades simultaneously.

𝕋𝕎𝔼𝔼𝕋

20,357 Aufrufe • vor 1 Jahr

Prediction Markets Are Broken by Low Liquidity, Pots Market Fixes It! Prediction markets promise smarter trading, but most fall short due to low liquidity, making trades execution slow and poor pricing. Pots Market solves this by integrating with Polymarket’s deep liquidity, delivering smoother and more reliable trades. It even goes further with sub-accounts for risk control, AI agents for better insights, and a Skill Hub where users can earn from their models. With built-in DeFi lending and Pots Money, capital doesn’t stay idle even while trades are active. All of this runs under Pots Core, powered by $POTS. Pots is turning prediction markets into more efficient tools for smarter decisions in Web3. If you’re paying attention, you’ll see where this is going. Follow Pots Market and Pots Money money to stay ahead.
1:01

Prediction Markets Are Broken by Low Liquidity, Pots Market Fixes It! Prediction markets promise smarter trading, but most fall short due to low liquidity, making trades execution slow and poor pricing. Pots Market solves this by integrating with Polymarket’s deep liquidity, delivering smoother and more reliable trades. It even goes further with sub-accounts for risk control, AI agents for better insights, and a Skill Hub where users can earn from their models. With built-in DeFi lending and Pots Money, capital doesn’t stay idle even while trades are active. All of this runs under Pots Core, powered by $POTS. Pots is turning prediction markets into more efficient tools for smarter decisions in Web3. If you’re paying attention, you’ll see where this is going. Follow Pots Market and Pots Money money to stay ahead.

web3prof

27,178 Aufrufe • vor 2 Monaten

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
25:59

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

Bri Teresi

29,602 Aufrufe • vor 3 Monaten

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch
56:43

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

83,806 Aufrufe • vor 1 Monat

AI just launched a memecoin… but the idea goes deeper. $GGIVE (Giggle Give) — fully built by Binance AI Pro From concept → name → ticker → branding → execution. The token isn’t the interesting part… it’s how it was built. Tokenomics: 3% tax → 2% goes directly to Giggle Academy → 1% is permanently burned But here’s what stands out ↓ Binance AI Pro didn’t just analyze markets… it designed the value flow from scratch and turned it into an executable on-chain system. This isn’t “AI assisting trading”… this is AI building digital economies end-to-end. If this direction continues, exchanges won’t just be execution layers… they become infrastructure for AI-native systems. That shift might be bigger than the feature itself. 👀 CZ 🔶 BNB BNB Chain
0:51

AI just launched a memecoin… but the idea goes deeper. $GGIVE (Giggle Give) — fully built by Binance AI Pro From concept → name → ticker → branding → execution. The token isn’t the interesting part… it’s how it was built. Tokenomics: 3% tax → 2% goes directly to Giggle Academy → 1% is permanently burned But here’s what stands out ↓ Binance AI Pro didn’t just analyze markets… it designed the value flow from scratch and turned it into an executable on-chain system. This isn’t “AI assisting trading”… this is AI building digital economies end-to-end. If this direction continues, exchanges won’t just be execution layers… they become infrastructure for AI-native systems. That shift might be bigger than the feature itself. 👀 CZ 🔶 BNB BNB Chain

Narcos 🔸

118,846 Aufrufe • vor 3 Monaten

Infrastructure defines what scales. Electricity enabled industry. The internet enabled software. Now AI is moving toward systems that run continuously, across data, execution, and feedback. 💡At OptimAI, we’re building that infrastructure. A decentralized search layer for real-time data. A network of nodes powering continuous retrieval and validation. Agents that execute tasks directly on your device. This is not theoretical - we’re already seeing it in production, with millions of nodes and growing usage across the network. We’re putting together a short documentary to show how this shift is happening, and where it leads next. If you’re building, exploring, or just getting started - this is the layer to pay attention to. Welcome to OptimAI.
2:02

Infrastructure defines what scales. Electricity enabled industry. The internet enabled software. Now AI is moving toward systems that run continuously, across data, execution, and feedback. 💡At OptimAI, we’re building that infrastructure. A decentralized search layer for real-time data. A network of nodes powering continuous retrieval and validation. Agents that execute tasks directly on your device. This is not theoretical - we’re already seeing it in production, with millions of nodes and growing usage across the network. We’re putting together a short documentary to show how this shift is happening, and where it leads next. If you’re building, exploring, or just getting started - this is the layer to pay attention to. Welcome to OptimAI.

OptimAI Network

17,439 Aufrufe • vor 3 Monaten