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NEW EPISODE - NEAR Just Turned Staking Yield Into AI Compute What if staking yield could keep an AI agent thinking? Illia (root.near) (🇺🇦, ⋈) joins David Hoffman to unpack NEAR Protocol’s new AI economy, where users can redirect staking yield toward private, verifiable inference. They dig into autonomous...

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Bankless

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113,516 次观看 • 7 天前 •via X (Twitter)

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INTERVIEW: AI, Surveillance, & the Fight for Digital Sovereignty | Near's Illia Polosukhin What happens when powerful AI requires an ID, governments can restrict access by country, and your most private data flows through centralized systems? NEAR Protocol co-founder Illia (root.near) (🇺🇦, ⋈) joins David Hoffman to explain why AI export controls could fracture the internet, how nationalized AI could become a surveillance layer, and why decentralized, user-owned AI may be the only real alternative. They also unpack Ironclaw, confidential inference, private agents, and NEAR’s push to make AI and assets fully sovereign. [TIMESTAMPS] 0:00 Intro 3:47 Pandora’s Box Opens 6:03 AI Meets Government 7:16 Decentralizing the Stack 8:51 Why Ban Fable? 11:18 Internet Balkanization 13:57 KYC for AI? 18:43 Nationalized Models 21:07 Building Private AI 26:30 Agent Marketplace 30:26 User-Owned Alignment 35:28 Winning Against Giants 40:19 Regulation Fuels Crypto 42:24 Global AI Adoption 45:05 Compute Is the Bottleneck 49:00 Enterprise Use Cases 51:39 Confidential TVL Explained 55:25 Full Sovereign Mode
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INTERVIEW: AI, Surveillance, & the Fight for Digital Sovereignty | Near's Illia Polosukhin What happens when powerful AI requires an ID, governments can restrict access by country, and your most private data flows through centralized systems? NEAR Protocol co-founder Illia (root.near) (🇺🇦, ⋈) joins David Hoffman to explain why AI export controls could fracture the internet, how nationalized AI could become a surveillance layer, and why decentralized, user-owned AI may be the only real alternative. They also unpack Ironclaw, confidential inference, private agents, and NEAR’s push to make AI and assets fully sovereign. [TIMESTAMPS] 0:00 Intro 3:47 Pandora’s Box Opens 6:03 AI Meets Government 7:16 Decentralizing the Stack 8:51 Why Ban Fable? 11:18 Internet Balkanization 13:57 KYC for AI? 18:43 Nationalized Models 21:07 Building Private AI 26:30 Agent Marketplace 30:26 User-Owned Alignment 35:28 Winning Against Giants 40:19 Regulation Fuels Crypto 42:24 Global AI Adoption 45:05 Compute Is the Bottleneck 49:00 Enterprise Use Cases 51:39 Confidential TVL Explained 55:25 Full Sovereign Mode

Bankless

59,588 次观看 • 1 个月前

LIVE NOW - Illia Polosukhin: Why AI Agents Are Still Useless (And What Fixes Them) AI agents still fall short. NEAR Protocol founder + Transformer co-author Illia (root.near) (🇺🇦, ⋈) breaks down what’s missing, why it matters, and how IronClaw could help unlock secure, private, autonomous AI. Illia’s bigger thesis: AI becomes the interface. Blockchains become the backend. -------------- TIMESTAMPS 0:00 Intro 0:43 Illia’s AI Journey 6:50 AI x Blockchain Operating Systems 13:11 Will Humans & AIs Use the Same Systems? 16:51 Why Are AI Agents Still Useless? 27:25 AI Agent Privacy Concerns 34:01 IronClaw Privacy 37:52 AI Agent Limitations 44:32 Context Constraints 51:14 Will Small Teams Win? 54:48 Autonomous Agents & Businesses 58:32 Digital Life Forms? 1:00:14 e/acc Vs d/acc 1:07:16 Why isn’t AI Crypto-Pilled 1:12:03 Advice for Builders 1:16:02 Closing & Disclaimers
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LIVE NOW - Illia Polosukhin: Why AI Agents Are Still Useless (And What Fixes Them) AI agents still fall short. NEAR Protocol founder + Transformer co-author Illia (root.near) (🇺🇦, ⋈) breaks down what’s missing, why it matters, and how IronClaw could help unlock secure, private, autonomous AI. Illia’s bigger thesis: AI becomes the interface. Blockchains become the backend. -------------- TIMESTAMPS 0:00 Intro 0:43 Illia’s AI Journey 6:50 AI x Blockchain Operating Systems 13:11 Will Humans & AIs Use the Same Systems? 16:51 Why Are AI Agents Still Useless? 27:25 AI Agent Privacy Concerns 34:01 IronClaw Privacy 37:52 AI Agent Limitations 44:32 Context Constraints 51:14 Will Small Teams Win? 54:48 Autonomous Agents & Businesses 58:32 Digital Life Forms? 1:00:14 e/acc Vs d/acc 1:07:16 Why isn’t AI Crypto-Pilled 1:12:03 Advice for Builders 1:16:02 Closing & Disclaimers

Bankless

44,418 次观看 • 4 个月前

NEW EP: Inside NEAR Protocol 10+ Years Building Toward the Agent Economy with Illia Polosukhin (Illia (root.near) (🇺🇦, ⋈)) From pioneering the transformer architecture now used in every AI stack to building the rails for the agent economy, NEAR Co-Founder Illia Polosukhin connects the full arc in this inaugural episode of “Inside NEAR,” a new quarterly series on The Rollup. Illia breaks down NEAR’s early architectural bets that are now paying off, why privacy had to be a base-layer choice, and how it all culminates in NEAR becoming AI money: the unit of account for inference, compute, and every agent-to-agent transaction settling onchain. With $20 billion+ in Intents volume and a path to deflation, the thesis is simple: NEAR’s TAM isn't crypto, it's all of commerce. Timestamps: 00:00 Intro 01:38 State Of NEAR Quarterly 04:32 The Transformer's Origin Story 06:51 NEAR Started As AI 11:40 Post-Quantum Crypto Coming Soon 13:48 Root Of Trust Solved 19:36 Target Market All Commerce 20:41 AI Frontend Blockchain Backend 22:44 Confidential Intents TVL Rising 28:51 Fee Switch Turned On 34:04 NEAR Is AI Money 36:30 One Line Changes Reality Full episode links below.
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NEW EP: Inside NEAR Protocol 10+ Years Building Toward the Agent Economy with Illia Polosukhin (Illia (root.near) (🇺🇦, ⋈)) From pioneering the transformer architecture now used in every AI stack to building the rails for the agent economy, NEAR Co-Founder Illia Polosukhin connects the full arc in this inaugural episode of “Inside NEAR,” a new quarterly series on The Rollup. Illia breaks down NEAR’s early architectural bets that are now paying off, why privacy had to be a base-layer choice, and how it all culminates in NEAR becoming AI money: the unit of account for inference, compute, and every agent-to-agent transaction settling onchain. With $20 billion+ in Intents volume and a path to deflation, the thesis is simple: NEAR’s TAM isn't crypto, it's all of commerce. Timestamps: 00:00 Intro 01:38 State Of NEAR Quarterly 04:32 The Transformer's Origin Story 06:51 NEAR Started As AI 11:40 Post-Quantum Crypto Coming Soon 13:48 Root Of Trust Solved 19:36 Target Market All Commerce 20:41 AI Frontend Blockchain Backend 22:44 Confidential Intents TVL Rising 28:51 Fee Switch Turned On 34:04 NEAR Is AI Money 36:30 One Line Changes Reality Full episode links below.

The Rollup

25,631 次观看 • 2 个月前

INTERVIEW - Venice Is Here to Win: How Private AI Takes On OpenAI and Anthropic David Hoffman sits down with Jon Venice and Jesse Proudman to unpack how Venice is taking on OpenAI and Anthropic with private AI. They talk about: - why AI is becoming the biggest data honeypot ever - private Grok access through Venice - unrestricted AI as a consumer wedge - how non-crypto users still feed the $VVV economy - $DIEM, tokenized inference, and AI agents --- TIMESTAMPS 0:00 Intro 1:12 Why Private AI Matters 3:01 The AI Data Honeypot 6:07 Venice’s Consumer AI Ambition 8:01 Beating the Big AI Labs 10:19 Model Aggregation and Agentic Chat 12:29 Open Source, Closed Source, and Private Grok 17:14 Who Actually Needs Private AI? 21:58 Venice’s User Base 23:53 What Drove Venice’s Recent Growth 27:21 $VVV, $DIEM, and Tokenized Inference 29:00 Where Venice Gets Its Compute 32:17 Bonding Curves and DIEM Monetary Policy 39:14 Real Tokenomics, Not Just a Pie Chart 45:46 AI Agents Need Inference to Exist 52:54 ShapeShift DNA Inside Venice 55:53 Regulation, AI, and Individual Rights
58:52

INTERVIEW - Venice Is Here to Win: How Private AI Takes On OpenAI and Anthropic David Hoffman sits down with Jon Venice and Jesse Proudman to unpack how Venice is taking on OpenAI and Anthropic with private AI. They talk about: - why AI is becoming the biggest data honeypot ever - private Grok access through Venice - unrestricted AI as a consumer wedge - how non-crypto users still feed the $VVV economy - $DIEM, tokenized inference, and AI agents --- TIMESTAMPS 0:00 Intro 1:12 Why Private AI Matters 3:01 The AI Data Honeypot 6:07 Venice’s Consumer AI Ambition 8:01 Beating the Big AI Labs 10:19 Model Aggregation and Agentic Chat 12:29 Open Source, Closed Source, and Private Grok 17:14 Who Actually Needs Private AI? 21:58 Venice’s User Base 23:53 What Drove Venice’s Recent Growth 27:21 $VVV, $DIEM, and Tokenized Inference 29:00 Where Venice Gets Its Compute 32:17 Bonding Curves and DIEM Monetary Policy 39:14 Real Tokenomics, Not Just a Pie Chart 45:46 AI Agents Need Inference to Exist 52:54 ShapeShift DNA Inside Venice 55:53 Regulation, AI, and Individual Rights

Bankless

59,389 次观看 • 2 个月前

INTERVIEW: Why $NEAR is Growing: The AI-Native Money Thesis - Intents, Privacy, & Tokenomics | Sal Ternullo NEAR Protocol is showing up more and more - Integrated in Zodl, right before the $ZEC explosion - Used in Venice to create private AI inferece - Infinex uses Near Intents for creating a unified wallet What's going on over at NEAR Protocol, and how does Near adoption impact $NEAR? Sal Ternullo, CEO of SVRN, joins us to explain why he thinks the original NEAR thesis finally coming into focus. They dig into NEAR Intents, AI money, tokenomics, privacy, fee capture, agentic commerce, and why SVRN is trying to commercialize the NEAR ecosystem rather than simply hold the asset. [TIMESTAMPS] 0:00 Intro 2:23 Why NEAR is Everywhere Lately 3:58 Pivot or Return to Roots? 7:41 The “AI Money” Thesis 9:54 Intents, Zashi, and Real Product Market Fit 11:38 Tokenomics, Buybacks, and Value Accrual 14:45 NEAR’s Different Approach From Ethereum 18:00 Fees, Scaling, and First-Party Apps 23:04 Cross-Chain Liquidity as NEAR’s Moat 28:27 The Contrarian Investor Case for NEAR 31:43 Privacy, Enterprises, and AI Agents 39:38 What SVRN Is Building for NEAR 46:00 Investor Sentiment and Final Thoughts
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INTERVIEW: Why $NEAR is Growing: The AI-Native Money Thesis - Intents, Privacy, & Tokenomics | Sal Ternullo NEAR Protocol is showing up more and more - Integrated in Zodl, right before the $ZEC explosion - Used in Venice to create private AI inferece - Infinex uses Near Intents for creating a unified wallet What's going on over at NEAR Protocol, and how does Near adoption impact $NEAR? Sal Ternullo, CEO of SVRN, joins us to explain why he thinks the original NEAR thesis finally coming into focus. They dig into NEAR Intents, AI money, tokenomics, privacy, fee capture, agentic commerce, and why SVRN is trying to commercialize the NEAR ecosystem rather than simply hold the asset. [TIMESTAMPS] 0:00 Intro 2:23 Why NEAR is Everywhere Lately 3:58 Pivot or Return to Roots? 7:41 The “AI Money” Thesis 9:54 Intents, Zashi, and Real Product Market Fit 11:38 Tokenomics, Buybacks, and Value Accrual 14:45 NEAR’s Different Approach From Ethereum 18:00 Fees, Scaling, and First-Party Apps 23:04 Cross-Chain Liquidity as NEAR’s Moat 28:27 The Contrarian Investor Case for NEAR 31:43 Privacy, Enterprises, and AI Agents 39:38 What SVRN Is Building for NEAR 46:00 Investor Sentiment and Final Thoughts

Bankless

50,511 次观看 • 2 个月前

A new episode of Hivemind is out now! This week we discuss the market rebound, DeFi exploit fallout, Crypto AI resurgence, and more. Timestamps: 0:00 Intro + market sentiment shift 08:55 The Aave/KelpDAO exploit explained 17:00 Why DeFi lending models may need to change 37:30 Where DeFi yield still makes sense 38:00 USDAI and real-world AI infrastructure yield 48:20 Venice, Bittensor, and AI token narratives 54:00 How AI agents are changing productivity 1:00:50 What the team is watching next
1:07:53

A new episode of Hivemind is out now! This week we discuss the market rebound, DeFi exploit fallout, Crypto AI resurgence, and more. Timestamps: 0:00 Intro + market sentiment shift 08:55 The Aave/KelpDAO exploit explained 17:00 Why DeFi lending models may need to change 37:30 Where DeFi yield still makes sense 38:00 USDAI and real-world AI infrastructure yield 48:20 Venice, Bittensor, and AI token narratives 54:00 How AI agents are changing productivity 1:00:50 What the team is watching next

Delphi Digital

12,596 次观看 • 3 个月前

Interview with Nebius Co-Founder Roman Chernin Please like & share this video so that all $NBIS investors on X will see it! :) If you prefer watching on YouTube: Timestamps: 00:00 - Why AI Infrastructure Is So Hard to Understand 00:24 - Market Fragmentation and What Actually Differentiates Providers 01:30 - Consolidation, Segmentation, and the Future AI Cloud Landscape 02:56 - What Analysts and VCs Still Get Wrong About AI Infrastructure 05:34 - Nebius Cloud: Product Readiness and Customer Proof Points 07:42 - Why Inference Workloads Are Exploding 09:11 - Training vs. Inference: How AI Models Actually Reach Production 10:10 - Why Inference Market Share May Concentrate Around a Few Winners 12:36 - Customer Use Cases: Coding, Enterprise AI, and Real-World Adoption 14:01 - Why Integrated Training and Inference Matter Strategically 16:01 - Building Scalable AI Infrastructure With High Utilization 18:24 - Token Factory: Inference as a Managed Service 20:24 - Revolut Case Study: AI-Driven Product Enhancements 22:56 - Token Factory Performance Optimization and Competitive Advantage 25:07 - Scale, Capacity, and Efficiency as Growth Drivers 28:36 - Why Inference Capacity Could Become the Next Major Bottleneck 30:10 - How Nebius Benchmarks Performance Across Providers 33:14 - The Future Size and Shape of the Inference Market 36:38 - Value-Based Pricing: Moving Beyond Cost per GPU Hour 40:55 - How Nebius Wins Deals: Quality, Performance, and Customer Experience 44:53 - Autonomous AI Platforms and the Rise of Agent-Based Models 47:28 - Tavily, Agentic Applications, and the Next Layer of the AI Stack 50:45 - Strategic Trade-Offs: Scaling, Product Roadmap, and Customer Relevance 55:40 - Final Thoughts: Adapting to the Next Shift in AI Workloads Nebius Roman Chernin
56:22

Interview with Nebius Co-Founder Roman Chernin Please like & share this video so that all $NBIS investors on X will see it! :) If you prefer watching on YouTube: Timestamps: 00:00 - Why AI Infrastructure Is So Hard to Understand 00:24 - Market Fragmentation and What Actually Differentiates Providers 01:30 - Consolidation, Segmentation, and the Future AI Cloud Landscape 02:56 - What Analysts and VCs Still Get Wrong About AI Infrastructure 05:34 - Nebius Cloud: Product Readiness and Customer Proof Points 07:42 - Why Inference Workloads Are Exploding 09:11 - Training vs. Inference: How AI Models Actually Reach Production 10:10 - Why Inference Market Share May Concentrate Around a Few Winners 12:36 - Customer Use Cases: Coding, Enterprise AI, and Real-World Adoption 14:01 - Why Integrated Training and Inference Matter Strategically 16:01 - Building Scalable AI Infrastructure With High Utilization 18:24 - Token Factory: Inference as a Managed Service 20:24 - Revolut Case Study: AI-Driven Product Enhancements 22:56 - Token Factory Performance Optimization and Competitive Advantage 25:07 - Scale, Capacity, and Efficiency as Growth Drivers 28:36 - Why Inference Capacity Could Become the Next Major Bottleneck 30:10 - How Nebius Benchmarks Performance Across Providers 33:14 - The Future Size and Shape of the Inference Market 36:38 - Value-Based Pricing: Moving Beyond Cost per GPU Hour 40:55 - How Nebius Wins Deals: Quality, Performance, and Customer Experience 44:53 - Autonomous AI Platforms and the Rise of Agent-Based Models 47:28 - Tavily, Agentic Applications, and the Next Layer of the AI Stack 50:45 - Strategic Trade-Offs: Scaling, Product Roadmap, and Customer Relevance 55:40 - Final Thoughts: Adapting to the Next Shift in AI Workloads Nebius Roman Chernin

Daniel Koss

203,706 次观看 • 3 个月前

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute
1:59:48

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute

Joseph Noel Walker

29,267 次观看 • 2 天前

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering
27:58

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

Madison Kanna

119,268 次观看 • 4 个月前

NEAR AI Ecosystem - "What Did You Ship This Week?" Ep. 3 🚢 The third NEAR AI shipstream brought more proof that this ecosystem isn’t slowing down. Teams are shipping, agents are evolving, and the pieces of a truly open AI stack are coming together. Timestamps & Highlights: 00:00 - Welcome & Introduction 00:07 - elizaOS w. robertyan (NEAR x ElizaOS, Open Source Plugins for Agents) 00:15 - Cyrnux w. 0xaaaaaron Δ∇ (Deploying EVM contracts on NEAR and Multichain OP Stack) 00:22 - Intellex AI Protocol w. Omar Saadoun (Activators Management for AI Protocols) 00:29 - Jutsu | Get a 24/7 SOC without hiring analysts. w. Zahidul Islam (NEAR AI TypeScript SDK update and demo) 00:36 - StrawberryAI w. intern.🍓 (Berry-Chat-r3 & BerrySwap for AI-based trading) 00:43 - MIZU w. shu@mysta (Curifi App for creating AI workflows from Telegram messages) 00:51 - Pond (Hiring Growth) w. dylan (AI models trained on on-chain data for crypto-native agents) 00:55 - NEAR AI w. Eric Winer (Agent for Autonomous Shopping Demo) 01:02 - Closing Remarks by Cameron.near NEAR Protocol is the blockchain for AI, and the stack speaks for itself. Don't fade anon. Tap into the full recording and see what’s next.
1:08:48

NEAR AI Ecosystem - "What Did You Ship This Week?" Ep. 3 🚢 The third NEAR AI shipstream brought more proof that this ecosystem isn’t slowing down. Teams are shipping, agents are evolving, and the pieces of a truly open AI stack are coming together. Timestamps & Highlights: 00:00 - Welcome & Introduction 00:07 - elizaOS w. robertyan (NEAR x ElizaOS, Open Source Plugins for Agents) 00:15 - Cyrnux w. 0xaaaaaron Δ∇ (Deploying EVM contracts on NEAR and Multichain OP Stack) 00:22 - Intellex AI Protocol w. Omar Saadoun (Activators Management for AI Protocols) 00:29 - Jutsu | Get a 24/7 SOC without hiring analysts. w. Zahidul Islam (NEAR AI TypeScript SDK update and demo) 00:36 - StrawberryAI w. intern.🍓 (Berry-Chat-r3 & BerrySwap for AI-based trading) 00:43 - MIZU w. shu@mysta (Curifi App for creating AI workflows from Telegram messages) 00:51 - Pond (Hiring Growth) w. dylan (AI models trained on on-chain data for crypto-native agents) 00:55 - NEAR AI w. Eric Winer (Agent for Autonomous Shopping Demo) 01:02 - Closing Remarks by Cameron.near NEAR Protocol is the blockchain for AI, and the stack speaks for itself. Don't fade anon. Tap into the full recording and see what’s next.

NEARWEEK

25,584 次观看 • 1 年前

LIVE NOW - AI Is Destroying Every Moat, Except Bitcoin Bitcoin may be the clearest winner in an AI economy. Jordi Visser joins Bankless to make the case for BTC as the core scarcity trade: An asset built for a world where AI compresses software, weakens old moats, and pushes investors toward what stays truly scarce. --- TIMESTAMPS 0:00 Intro 2:07 Jordi’s bold Bitcoin call 4:18 The AI endgame lands at Bitcoin 9:26 Bitcoin as the purest AI trade 12:49 SaaSpocalypse, quantum fear, and the private credit risk 20:49 AI is the new QE 26:55 Inflation, deflation, and the scarcity squeeze 34:28 What happens to stocks from here 44:24 Is AI a bubble? 48:17 The Bitcoin IPO and muted cycles 1:01:01 Has Bitcoin already bottomed? 1:09:03 The broken social pact 1:13:21 The rest of crypto, from ETH to stablecoins 1:17:29 Inside the scarcity portfolio 1:20:42 Jensen vs. Dwarkesh, China, and the chip war 1:27:42 Jordi’s AI stack and where to follow his work
1:31:19

LIVE NOW - AI Is Destroying Every Moat, Except Bitcoin Bitcoin may be the clearest winner in an AI economy. Jordi Visser joins Bankless to make the case for BTC as the core scarcity trade: An asset built for a world where AI compresses software, weakens old moats, and pushes investors toward what stays truly scarce. --- TIMESTAMPS 0:00 Intro 2:07 Jordi’s bold Bitcoin call 4:18 The AI endgame lands at Bitcoin 9:26 Bitcoin as the purest AI trade 12:49 SaaSpocalypse, quantum fear, and the private credit risk 20:49 AI is the new QE 26:55 Inflation, deflation, and the scarcity squeeze 34:28 What happens to stocks from here 44:24 Is AI a bubble? 48:17 The Bitcoin IPO and muted cycles 1:01:01 Has Bitcoin already bottomed? 1:09:03 The broken social pact 1:13:21 The rest of crypto, from ETH to stablecoins 1:17:29 Inside the scarcity portfolio 1:20:42 Jensen vs. Dwarkesh, China, and the chip war 1:27:42 Jordi’s AI stack and where to follow his work

Bankless

16,225 次观看 • 3 个月前

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!
1:13:04

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!

Logan Jastremski

62,508 次观看 • 7 天前

LIVE NOW -- The Rise of AI Crypto Agents The collision between crypto and AI agents has officially begun. Joining us today is Matthew Stephensen, Research Partner Pantera Capital and author of “Crypto: Picks and Shovels for the AI Gold Rush”. We dive into the world of autonomous AI agents on blockchains, discuss the evolving role of agents, AI-driven market changes, and whether blockchain is the natural substrate for AI. Matt Stephenson sheds light on topics from agent liability and regulatory challenges to infrastructure value capture and the "picks and shovels" approach to investing in AI-driven crypto tech. Are AI agents on blockchains the obvious future? And how do scarcity and abundance interact in this new era? Join us as we tackle these questions and more, exploring what the future might hold at the intersection of AI, autonomy, and blockchain. ------------------------------------------------------------ Chapters: 0:00 Intro 5:34 Crypto x AI Narrative Shift 6:39 AI & Economic Agents Explained 11:50 $GOAT Memecoin Summary 23:15 Were AI Crypto Agents Obvious? 25:18 Luna AI Token & Terminal 29:41 Consequences? Is This Life? 33:27 Exciting Use Cases 40:27 Sam Altman Quote Importance 42:33 Wealth Generation Process & Blockspace 48:15 Programmable Money & Agent MEV 56:14 The #AI Agent & Memecoin Thesis 1:03:03 Government & Society Reaction Predictions 1:11:09 No Off Buttons?... 1:13:40 #DePin & AI 1:16:45 AI Agent Blockspace Demand 1:19:15 Closing & Disclaimers
1:21:01

LIVE NOW -- The Rise of AI Crypto Agents The collision between crypto and AI agents has officially begun. Joining us today is Matthew Stephensen, Research Partner Pantera Capital and author of “Crypto: Picks and Shovels for the AI Gold Rush”. We dive into the world of autonomous AI agents on blockchains, discuss the evolving role of agents, AI-driven market changes, and whether blockchain is the natural substrate for AI. Matt Stephenson sheds light on topics from agent liability and regulatory challenges to infrastructure value capture and the "picks and shovels" approach to investing in AI-driven crypto tech. Are AI agents on blockchains the obvious future? And how do scarcity and abundance interact in this new era? Join us as we tackle these questions and more, exploring what the future might hold at the intersection of AI, autonomy, and blockchain. ------------------------------------------------------------ Chapters: 0:00 Intro 5:34 Crypto x AI Narrative Shift 6:39 AI & Economic Agents Explained 11:50 $GOAT Memecoin Summary 23:15 Were AI Crypto Agents Obvious? 25:18 Luna AI Token & Terminal 29:41 Consequences? Is This Life? 33:27 Exciting Use Cases 40:27 Sam Altman Quote Importance 42:33 Wealth Generation Process & Blockspace 48:15 Programmable Money & Agent MEV 56:14 The #AI Agent & Memecoin Thesis 1:03:03 Government & Society Reaction Predictions 1:11:09 No Off Buttons?... 1:13:40 #DePin & AI 1:16:45 AI Agent Blockspace Demand 1:19:15 Closing & Disclaimers

Bankless

43,849 次观看 • 1 年前

Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History
1:04:51

Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History

Raoul Pal

326,827 次观看 • 1 年前

INTERVIEW: Why Every Chain, Wallet & App Is Integrating NEAR Intents | Kendall Cole NEAR Protocol wants users to stop thinking about blockchains altogether. Proximity Labs co-founder Kendall Cole joins David Hoffman to explain how NEAR Intents connects 35 chains, powers products like Infinex, brings tokenized assets and confidential transactions into one seamless experience, and turns fragmented crypto markets into a single account where users see assets, not infrastructure. [TIMESTAMPS] 0:00 Intro 2:29 Chains Need Neutrality 4:20 Near’s Chain Abstraction Vision 6:03 Wallets to Retail Expansion 9:30 Bootstrapping Liquidity and Partners 11:23 RWA Asset Explosion 15:00 Tokenized Stocks on Near 15:57 One App Across Chains 19:01 Near as Chain Abstraction 21:35 Trading Bots and Payments 24:54 MiCA’s Market Shock 28:16 Noncustodial Compliance Strategy 29:17 Euro Onramps into Near 31:38 Regulation Meets On-Chain Freedom 38:09 Confidential Intents Launch 41:15 Privacy for Users and Firms 43:36 Private zcash:native Routing 46:50 Privacy for AI Models 49:52 near:native’s Fee Capture Model 52:19 Crypto as Exchange Infrastructure
56:18

INTERVIEW: Why Every Chain, Wallet & App Is Integrating NEAR Intents | Kendall Cole NEAR Protocol wants users to stop thinking about blockchains altogether. Proximity Labs co-founder Kendall Cole joins David Hoffman to explain how NEAR Intents connects 35 chains, powers products like Infinex, brings tokenized assets and confidential transactions into one seamless experience, and turns fragmented crypto markets into a single account where users see assets, not infrastructure. [TIMESTAMPS] 0:00 Intro 2:29 Chains Need Neutrality 4:20 Near’s Chain Abstraction Vision 6:03 Wallets to Retail Expansion 9:30 Bootstrapping Liquidity and Partners 11:23 RWA Asset Explosion 15:00 Tokenized Stocks on Near 15:57 One App Across Chains 19:01 Near as Chain Abstraction 21:35 Trading Bots and Payments 24:54 MiCA’s Market Shock 28:16 Noncustodial Compliance Strategy 29:17 Euro Onramps into Near 31:38 Regulation Meets On-Chain Freedom 38:09 Confidential Intents Launch 41:15 Privacy for Users and Firms 43:36 Private zcash:native Routing 46:50 Privacy for AI Models 49:52 near:native’s Fee Capture Model 52:19 Crypto as Exchange Infrastructure

Bankless

37,003 次观看 • 1 个月前

Andy asked why wouldn't AI agents create their own currency? An AI-generated unit of account all the LLMs agree on? Illia (root.near) (🇺🇦, ⋈), Co-Founder of NEAR Protocol: "They can create tokens. But agents need reputation and reputation needs history. You can't manufacture that." "You still need to pay for compute. That maps to energy. Those economic pieces need to map into something people value. Existing infrastructure already has ins and outs into the real world. That matters."
1:30

Andy asked why wouldn't AI agents create their own currency? An AI-generated unit of account all the LLMs agree on? Illia (root.near) (🇺🇦, ⋈), Co-Founder of NEAR Protocol: "They can create tokens. But agents need reputation and reputation needs history. You can't manufacture that." "You still need to pay for compute. That maps to energy. Those economic pieces need to map into something people value. Existing infrastructure already has ins and outs into the real world. That matters."

The Rollup

34,140 次观看 • 2 个月前

INTERVIEW: Arthur Hayes - The AI Crash That Could Send bitcoin:native to $1M Arthur thinks the AI trade is sucking the oxygen out of crypto, and the real opportunity may come after the AI bubble cracks. Inside the episode: - AI CapEx mania - Why ethereum:native looks cheap - Oil as the macro bear case - “The Fed can’t print Moore’s Law” - How an AI credit event could send money back into crypto - Why Hyperliquid can challenge Binance - Why the inventor of perps says not to use leverage --- TIMESTAMPS 0:00 Why Arthur Sold HYPE, NEAR and ZEC 4:26 The AI Trade Starts to Look Crowded 6:25 How Arthur Is Positioned Now 7:15 Crypto’s Strange Market Dispersion 11:09 Oil, Iran and the Fake-Out Risk 14:16 Why the Iran Deal May Not Be Durable 17:29 Can AI Survive Higher Oil? 21:20 The AI Bubble Thesis 26:11 China’s Cheap AI Threat 30:38 The Credit Event Arthur Is Watching 35:51 The 2028 Perfect Storm 39:45 Why AI Is Draining Crypto’s Bull Market 44:28 Arthur on Inventing Perps 48:11 Why Perps Could Eat Wall Street 51:18 Socialized Loss Explained 53:21 Onshore vs Offshore Perps 55:50 Why Hyperliquid Can Flip Binance 56:30 The Perp Inventor Does Not Use Leverage
58:16

INTERVIEW: Arthur Hayes - The AI Crash That Could Send bitcoin:native to $1M Arthur thinks the AI trade is sucking the oxygen out of crypto, and the real opportunity may come after the AI bubble cracks. Inside the episode: - AI CapEx mania - Why ethereum:native looks cheap - Oil as the macro bear case - “The Fed can’t print Moore’s Law” - How an AI credit event could send money back into crypto - Why Hyperliquid can challenge Binance - Why the inventor of perps says not to use leverage --- TIMESTAMPS 0:00 Why Arthur Sold HYPE, NEAR and ZEC 4:26 The AI Trade Starts to Look Crowded 6:25 How Arthur Is Positioned Now 7:15 Crypto’s Strange Market Dispersion 11:09 Oil, Iran and the Fake-Out Risk 14:16 Why the Iran Deal May Not Be Durable 17:29 Can AI Survive Higher Oil? 21:20 The AI Bubble Thesis 26:11 China’s Cheap AI Threat 30:38 The Credit Event Arthur Is Watching 35:51 The 2028 Perfect Storm 39:45 Why AI Is Draining Crypto’s Bull Market 44:28 Arthur on Inventing Perps 48:11 Why Perps Could Eat Wall Street 51:18 Socialized Loss Explained 53:21 Onshore vs Offshore Perps 55:50 Why Hyperliquid Can Flip Binance 56:30 The Perp Inventor Does Not Use Leverage

Bankless

303,740 次观看 • 1 个月前

In this episode, we’re diving deep into AI and crypto. To help us unpack it, we’re joined by Illia (root.near) (🇺🇦, ⋈) — co-founder of the crypto protocol NEAR Protocol and co-author of the groundbreaking 2017 “transformers” paper that kicked off the current AI boom. Ilia has been early to some of the biggest recent tech trends, and today he brings us a rare, panoramic view of the tech industry’s cutting edge. Together we explore what the phrase “user-owned AI” really means; why the so-called agentic internet — that is, a world where your AI assistant talks directly to services on your behalf — might replace the very notion of websites and apps as we know them; and much more. Timestamps: 0:00 - Introduction 3:40 - Centralization and Challenges of AI 6:17 - “User-Owned” AI 12:14 - Confidential Computing and AI 17:51 - The Birth of Transformers 22:33 - NEAR AI and Crowdsourcing 27:56 - AI Agents and Future Applications 31:04 - The End of Websites and Applications 34:08 - Dead Internet Theory & Distinguishing Humans 41:49 - Open Source vs. Open Weight Models 43:48 - Geopolitical Implications of AI 46:55 - NEAR Protocol and Blockchain Scaling 59:29 - The Role of Humans in an AI World
1:02:18

In this episode, we’re diving deep into AI and crypto. To help us unpack it, we’re joined by Illia (root.near) (🇺🇦, ⋈) — co-founder of the crypto protocol NEAR Protocol and co-author of the groundbreaking 2017 “transformers” paper that kicked off the current AI boom. Ilia has been early to some of the biggest recent tech trends, and today he brings us a rare, panoramic view of the tech industry’s cutting edge. Together we explore what the phrase “user-owned AI” really means; why the so-called agentic internet — that is, a world where your AI assistant talks directly to services on your behalf — might replace the very notion of websites and apps as we know them; and much more. Timestamps: 0:00 - Introduction 3:40 - Centralization and Challenges of AI 6:17 - “User-Owned” AI 12:14 - Confidential Computing and AI 17:51 - The Birth of Transformers 22:33 - NEAR AI and Crowdsourcing 27:56 - AI Agents and Future Applications 31:04 - The End of Websites and Applications 34:08 - Dead Internet Theory & Distinguishing Humans 41:49 - Open Source vs. Open Weight Models 43:48 - Geopolitical Implications of AI 46:55 - NEAR Protocol and Blockchain Scaling 59:29 - The Role of Humans in an AI World

a16z crypto

47,069 次观看 • 1 年前