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BREAKING: Merge Launches ‘Agent Handler’ Control AI Access, Tokenmaxxed $$$ Bills, & Stop Mass Data Leaks "We don't trust agents" "The second you connect it to tools, that's where everything goes wrong." OpenAI. Perplexity. Netflix. Uber. Mistral. Dropbox. JPMorgan.. all quietly run on Merge Co-Founders CEO Shensi Ding Ding...

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Molly O’Shea

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111,027 次观看 • 1 个月前 •via X (Twitter)

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Merge Agent Handler went from zero to enterprise-ready in 6 months. Most of it was vibe coded... But not in the way you might think. Co-founder and CEO Shensi Ding gives us a peak under the hood on what building with AI actually looks like. ↓
3:26

Merge Agent Handler went from zero to enterprise-ready in 6 months. Most of it was vibe coded... But not in the way you might think. Co-founder and CEO Shensi Ding gives us a peak under the hood on what building with AI actually looks like. ↓

Merge

192,892 次观看 • 2 个月前

One of the most foundational things is the Economic Singularity and the fact that you have ~5 years to unfuck your future... The world will change dramatically by 2030, and we don't have much time left to build wealth! Can't stress enough how important this is... the apex of everything I'm doing.... Enjoy! Timestamps: 00:00 Intro 00:48 2030 Will Change Everything 01:41 Retirement Crisis Looms 03:02 AI & Robots Take Over 03:54 The GDP Formula 04:45 Demographics Collapse 06:27 Robots Replace Labor 07:34 AI Disrupts Knowledge 08:19 From Scarcity to Abundance 09:06 Cheap Energy Boom 10:21 Renewables & Grids 11:43 Nuclear = Free Power 12:45 Infinite Humans + Output 13:50 AI Agents + Crypto 14:58 AI Builds Products Fast 15:41 1-Person Billionaires 16:41 AGI vs. Markets 17:54 Universal Basic Equity 19:10 Adapt or Die 20:47 Human-AI Merge 22:58 Tech & Blockchain Win 25:42 Communities Win 26:31 Deflation Shock 27:48 AI Solves Itself 28:38 RV’s AI & Blockchain Plan 30:14 Human-Safe Industries 31:23 AI Companions Rise 35:00 Closing Thoughts
39:29

One of the most foundational things is the Economic Singularity and the fact that you have ~5 years to unfuck your future... The world will change dramatically by 2030, and we don't have much time left to build wealth! Can't stress enough how important this is... the apex of everything I'm doing.... Enjoy! Timestamps: 00:00 Intro 00:48 2030 Will Change Everything 01:41 Retirement Crisis Looms 03:02 AI & Robots Take Over 03:54 The GDP Formula 04:45 Demographics Collapse 06:27 Robots Replace Labor 07:34 AI Disrupts Knowledge 08:19 From Scarcity to Abundance 09:06 Cheap Energy Boom 10:21 Renewables & Grids 11:43 Nuclear = Free Power 12:45 Infinite Humans + Output 13:50 AI Agents + Crypto 14:58 AI Builds Products Fast 15:41 1-Person Billionaires 16:41 AGI vs. Markets 17:54 Universal Basic Equity 19:10 Adapt or Die 20:47 Human-AI Merge 22:58 Tech & Blockchain Win 25:42 Communities Win 26:31 Deflation Shock 27:48 AI Solves Itself 28:38 RV’s AI & Blockchain Plan 30:14 Human-Safe Industries 31:23 AI Companions Rise 35:00 Closing Thoughts

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336,732 次观看 • 11 个月前

Deeply thoughtful conversation with Zico Kolter, board member at OpenAI and head of the machine learning department at Carnegie Mellon University, about AI safety, AI security, agents and frontier AI 00:00 Intro 01:32 OpenAI board role and Safety & Security Committee 03:53 How OpenAI reviews major model releases 05:33 OpenAI’s preparedness framework explained 09:46 Are frontier AI models getting safer? 12:33 Why AI safety does not come from scale 15:23 The four categories of AI risk 19:38 Doomerism vs accelerationism in AI 24:11 The six-month AI pause debate 26:20 AI safety as a global effort 28:04 How Zico Kolter got into machine learning 31:05 OpenAI in the early days 34:14 Why Carnegie Mellon became an AI powerhouse 38:43 What Gray Swan does in AI security 40:44 AI safety vs AI security 43:15 The GCG jailbreak paper 49:19 How AI labs responded to jailbreak research 50:19 State-of-the-art AI defenses 52:32 State-of-the-art AI attacks 54:22 Why AI agents expand the attack surface 58:39 Are AI agents ready for production? 59:40 Mechanistic interpretability explained 1:02:31 Will AI be safer in two years? 1:03:46 Reinforcement learning and self-improving models 1:08:09 Do post-transformer architectures matter 1:09:29 Best research directions in AI now 1:11:00 Zico Kolter’s Intro to Modern AI course 1:14:53 Why modern AI is simpler than people think
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Deeply thoughtful conversation with Zico Kolter, board member at OpenAI and head of the machine learning department at Carnegie Mellon University, about AI safety, AI security, agents and frontier AI 00:00 Intro 01:32 OpenAI board role and Safety & Security Committee 03:53 How OpenAI reviews major model releases 05:33 OpenAI’s preparedness framework explained 09:46 Are frontier AI models getting safer? 12:33 Why AI safety does not come from scale 15:23 The four categories of AI risk 19:38 Doomerism vs accelerationism in AI 24:11 The six-month AI pause debate 26:20 AI safety as a global effort 28:04 How Zico Kolter got into machine learning 31:05 OpenAI in the early days 34:14 Why Carnegie Mellon became an AI powerhouse 38:43 What Gray Swan does in AI security 40:44 AI safety vs AI security 43:15 The GCG jailbreak paper 49:19 How AI labs responded to jailbreak research 50:19 State-of-the-art AI defenses 52:32 State-of-the-art AI attacks 54:22 Why AI agents expand the attack surface 58:39 Are AI agents ready for production? 59:40 Mechanistic interpretability explained 1:02:31 Will AI be safer in two years? 1:03:46 Reinforcement learning and self-improving models 1:08:09 Do post-transformer architectures matter 1:09:29 Best research directions in AI now 1:11:00 Zico Kolter’s Intro to Modern AI course 1:14:53 Why modern AI is simpler than people think

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State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, The Rise of Headless, and AI-Proofing Your Job 00:00 Intro 01:18 Silicon Valley engineering vs. everyone else 05:35 Are enterprise CIOs actually bullish on AI? 08:51 Tokenmaxxing & why your AI bill is about to explode 11:34 The myth of falling token costs and AI spend escaping IT budgets 17:37 The $5B startup hiding in AI compute 18:14 The mosaic of models inside every enterprise 21:28 Why coding works and the rest of knowledge work doesn't 25:53 The Bob and Sally problem: access control breaks agents 30:31 Will enterprise AI really take 10 years to roll out 32:24 The capability overhang: why faster models slow diffusion 34:23 Data is the bottleneck (it always was) 39:02 The rise of internal forward-deployed engineers 41:23 Why the AI doomers are wrong about jobs 43:43 Headless software is inevitable 46:14 What replaces per-seat pricing 47:37 How Box itself is going headless 49:42 How the org chart actually evolves 1:00:33 Future-proofing yourself as an enterprise employee 1:06:40 Are we all just going to work for OpenAI and Anthropic? 1:07:11 Where startups can still win as the labs move up
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State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, The Rise of Headless, and AI-Proofing Your Job 00:00 Intro 01:18 Silicon Valley engineering vs. everyone else 05:35 Are enterprise CIOs actually bullish on AI? 08:51 Tokenmaxxing & why your AI bill is about to explode 11:34 The myth of falling token costs and AI spend escaping IT budgets 17:37 The $5B startup hiding in AI compute 18:14 The mosaic of models inside every enterprise 21:28 Why coding works and the rest of knowledge work doesn't 25:53 The Bob and Sally problem: access control breaks agents 30:31 Will enterprise AI really take 10 years to roll out 32:24 The capability overhang: why faster models slow diffusion 34:23 Data is the bottleneck (it always was) 39:02 The rise of internal forward-deployed engineers 41:23 Why the AI doomers are wrong about jobs 43:43 Headless software is inevitable 46:14 What replaces per-seat pricing 47:37 How Box itself is going headless 49:42 How the org chart actually evolves 1:00:33 Future-proofing yourself as an enterprise employee 1:06:40 Are we all just going to work for OpenAI and Anthropic? 1:07:11 Where startups can still win as the labs move up

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Claude Cowork, Mythos, and the Future of Software: my conversation with Felix Rieseberg, who leads Cowork at Anthropic 00:00 Intro 01:53 Claude Mythos Preview and the “step-function change” 06:16 Why Anthropic is treating Mythos differently 11:19 The real story behind Claude Cowork’s “10-day” build 12:42 Why Anthropic realized Claude Code needed a non-technical version 15:44 What Claude Cowork actually is 17:03 Under the hood: virtual machines, tools, skills 18:36 Where Cowork’s memory actually lives 19:26 How Cowork connects to files, apps, and the internet 20:45 Why Felix thinks the local computer is under-appreciated 24:49 Trust: how do you get users comfortable with AI agents? 28:45 What UX actually means for AI agents 31:27 Anthropic Cowork's roadmap is only one month long 34:12 Building 100 prototypes 35:10 If execution is free, what becomes the bottleneck? 37:25 Does it come down to taste? 40:12 The hardest part of building Claude Cowork 41:43 Advice for founders building AI agents 44:21 SaaSpocalypse: what’s left for software startups 49:30 Where AI agents are going next 51:20 Regulated industries and enterprise adoption 54:15 Hot takes: what's underrated, overrated, and what Felix would build today

Matt Turck

80,519 次观看 • 3 个月前

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My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:

Shane Parrish

450,952 次观看 • 2 个月前

Today, I’m excited to announce our new product: Merge Agent Handler! With the growth of AI, we've seen demand for both synced connectors to power enterprise search and deterministic use cases, and live connectors that let agents take real-time actions. And now, with Merge, you can have both. Merge Agent Handler securely connects your AI agents to thousands of pre-built tools via MCP. The platform also comes with authentication, credential management, monitoring, logging, and enterprise-grade security. Huge shout out to the team who worked tirelessly to bring this to life.
1:06

Today, I’m excited to announce our new product: Merge Agent Handler! With the growth of AI, we've seen demand for both synced connectors to power enterprise search and deterministic use cases, and live connectors that let agents take real-time actions. And now, with Merge, you can have both. Merge Agent Handler securely connects your AI agents to thousands of pre-built tools via MCP. The platform also comes with authentication, credential management, monitoring, logging, and enterprise-grade security. Huge shout out to the team who worked tirelessly to bring this to life.

Shensi Ding

45,064 次观看 • 9 个月前

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.
49:12

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.

Mario Nawfal

338,140 次观看 • 1 年前

E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?
1:45:11

E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?

MR SHIFT 🦁

284,090 次观看 • 1 年前

Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack
1:05:15

Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack

Matt Turck

11,908 次观看 • 1 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

Can AI agents automate all work? What happens to white collar jobs? I sat down with Aaron Levie (Aaron Levie), Founder and CEO of to talk about agents, deploying AI, the future of white collar jobs, the future of SaaS, and so much more. 0:00 Intro 1:02 AI at Box 2:59 New tools 5:26 Embracing AI at Box 8:13 Using AI to do more 11:09 White collar collapse? 14:51 How does demand scale? 19:29 Managing AI 25:51 Companies with too much power 29:58 Personal vs Work agents 35:37 What if AI makes a big mistake? 41:23 Who will own the agents? 43:37 SaaS is dead 48:40 Future of the web 57:23 Using AI on socials
59:27

Can AI agents automate all work? What happens to white collar jobs? I sat down with Aaron Levie (Aaron Levie), Founder and CEO of to talk about agents, deploying AI, the future of white collar jobs, the future of SaaS, and so much more. 0:00 Intro 1:02 AI at Box 2:59 New tools 5:26 Embracing AI at Box 8:13 Using AI to do more 11:09 White collar collapse? 14:51 How does demand scale? 19:29 Managing AI 25:51 Companies with too much power 29:58 Personal vs Work agents 35:37 What if AI makes a big mistake? 41:23 Who will own the agents? 43:37 SaaS is dead 48:40 Future of the web 57:23 Using AI on socials

Matthew Berman

91,581 次观看 • 1 年前

The 2026 Jensen Huang No Priors interview: 00:17 2025 surprises 04:12 AI is job creation 12:31 Robotics for labor shortages 15:14 Open source, layer cake of making money in AI 21:52 The myth of "God AI" 23:54 Doomers and regulation 29:25 Jensen teaches Tokenomics 35:09 The return to research 37:49 Future of engineering 43:20 Next ChatGPT moment 46:00 Self driving 54:06 We need energy 58:49 US-China relations in '26 1:04:43 Is there an AI bubble?
1:16:20

The 2026 Jensen Huang No Priors interview: 00:17 2025 surprises 04:12 AI is job creation 12:31 Robotics for labor shortages 15:14 Open source, layer cake of making money in AI 21:52 The myth of "God AI" 23:54 Doomers and regulation 29:25 Jensen teaches Tokenomics 35:09 The return to research 37:49 Future of engineering 43:20 Next ChatGPT moment 46:00 Self driving 54:06 We need energy 58:49 US-China relations in '26 1:04:43 Is there an AI bubble?

No Priors

40,265 次观看 • 6 个月前

Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI
1:06:29

Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI

Matt Turck

11,971 次观看 • 11 个月前

We asked a dozen DevTool founders from companies like RevenueCat, Greptile, Firecrawl, Infisical, ollama, Resend, Mintlify, Unsloth AI, Porter, and recall.ai, about the state of AI agents and the future of software engineering. In this episode of Founder FAQ, we covered everything from agents as customers and the end of coding, to advice for founders starting out and what they're most excited about going forward. Their answers might surprise you. 00:00 – Meet the Founders 03:00 – Building for Agents First 04:22 – Biggest Early Mistakes 07:15 – Do Founders Still Write Code? 09:22 – Most Unexpected AI Discoveries 12:09 – What's Underrated Right Now 14:38 – Predictions & What's Next
20:29

We asked a dozen DevTool founders from companies like RevenueCat, Greptile, Firecrawl, Infisical, ollama, Resend, Mintlify, Unsloth AI, Porter, and recall.ai, about the state of AI agents and the future of software engineering. In this episode of Founder FAQ, we covered everything from agents as customers and the end of coding, to advice for founders starting out and what they're most excited about going forward. Their answers might surprise you. 00:00 – Meet the Founders 03:00 – Building for Agents First 04:22 – Biggest Early Mistakes 07:15 – Do Founders Still Write Code? 09:22 – Most Unexpected AI Discoveries 12:09 – What's Underrated Right Now 14:38 – Predictions & What's Next

Y Combinator

27,515 次观看 • 1 个月前

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self
1:45:40

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self

Matt Turck

86,153 次观看 • 1 年前

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion
1:10:03

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion

Matt Turck

93,678 次观看 • 9 个月前