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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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113,984 次观看 • 1 个月前 •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 • 3 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 • 6 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

25,758 次观看 • 3 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 - 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

59,687 次观看 • 4 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
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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 • 5 个月前

Compute is emerging as a new asset class, and Ornn is building markets for it. We sat down with wayne nelms, co-founder and CTO of Ornn, to chat about pricing, hedging, and trading compute. Timestamps 👇 0:00 Intro 0:49 Meet Wayne 2:15 GPU pricing & Ornn's compute marketplace 4:27 Why compute differs from oil 5:47 Compute pricing and market neutrality 10:07 Bloomberg and compute exchange partnerships 12:40 AI infrastructure's financing gap 16:42 Compute forward curves and price risk 21:58 AI token pricing and inference costs 24:26 Compute markets and blockchain 28:36 Financial engineering and institutional adoption
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Compute is emerging as a new asset class, and Ornn is building markets for it. We sat down with wayne nelms, co-founder and CTO of Ornn, to chat about pricing, hedging, and trading compute. Timestamps 👇 0:00 Intro 0:49 Meet Wayne 2:15 GPU pricing & Ornn's compute marketplace 4:27 Why compute differs from oil 5:47 Compute pricing and market neutrality 10:07 Bloomberg and compute exchange partnerships 12:40 AI infrastructure's financing gap 16:42 Compute forward curves and price risk 21:58 AI token pricing and inference costs 24:26 Compute markets and blockchain 28:36 Financial engineering and institutional adoption

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60,855 次观看 • 8 天前

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Why $10 Million Bitcoin Isn’t As Crazy As It Sounds | Avichal Garg - Electric ϟ Capital 00:00 Bitcoin to $5–10M? The Digital Gold Thesis 03:11 How AI Agents Could Expand Bitcoin’s Market 05:18 Autonomous AI Agents, Money & Jurisdiction 09:09 How Electric Capital Is Already Using AI Agents 11:28 What Work Is Left for Humans? 13:00 How AI Could Create Tiny Billion-Dollar Companies 16:10 Would You Let an AI Agent Transact With Crypto? 22:46 How Electric Capital Decides What to Invest In 24:01 What Becomes Valuable When AI Gets Smarter Than Humans? 30:31 How Crypto Infrastructure Is Moving Into AI 34:50 How Should Investors Value Tokens? 35:36 Fee Switches, Buybacks & Token Value Accrual 38:47 Token Networks as Coordination Technology 42:51 Onchain Companies, Wallets & AI Employees 46:00 A Parallel Global Public Equities Market 49:00 Why Global Investors Understand Tokenization Differently 51:14 Final Thoughts

The Wolf Of All Streets

99,193 次观看 • 10 天前

“Most people already have more intelligence than they know what to do with.” iArb | 裁定取引 joins the Insilico Terminal Podcast to talk about finding obscure crypto edges, building trading systems, and putting AI to work. We covered the Tari arbitrage, oil perps on Hyperliquid, automating research, owning compute, and where he sees the next opportunities for small teams. 00:00 Introducing Arb and his first crypto arbitrage 09:25 Oil perps: trading the market rules 16:43 Bitcoin, hardware and the AI opportunity 26:40 Where AI value accrues 33:26 Why small teams can move faster 39:08 AI for trading research and automation 45:51 How to think in systems 51:07 Manual trading and AI-built systems 55:38 AI workflows and what changes next
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“Most people already have more intelligence than they know what to do with.” iArb | 裁定取引 joins the Insilico Terminal Podcast to talk about finding obscure crypto edges, building trading systems, and putting AI to work. We covered the Tari arbitrage, oil perps on Hyperliquid, automating research, owning compute, and where he sees the next opportunities for small teams. 00:00 Introducing Arb and his first crypto arbitrage 09:25 Oil perps: trading the market rules 16:43 Bitcoin, hardware and the AI opportunity 26:40 Where AI value accrues 33:26 Why small teams can move faster 39:08 AI for trading research and automation 45:51 How to think in systems 51:07 Manual trading and AI-built systems 55:38 AI workflows and what changes next

Insilico Terminal

22,370 次观看 • 26 天前

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
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Daniel Koss

204,842 次观看 • 5 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

33,048 次观看 • 1 个月前

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
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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 • 6 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 (Hiring) (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.
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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 (Hiring) (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

25,585 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
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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

16,239 次观看 • 5 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

132,617 次观看 • 1 个月前

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

37,588 次观看 • 2 个月前

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