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A columnist told Meta's Muse agent it couldn't read his iMessages, and it read them anyway. George Sivulka of Hebbia, Scott Stephenson of Deepgram, and Dan Mishin of Manifest OS join Jason and Lon to discuss everyone’s favorite AI assistants, and whether these industry leaders have concerns about sharing...

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This Week in AI

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22,608 görüntüleme • 7 gün önce •via X (Twitter)

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sophs l profil fotoğrafı
sophs l7 gün önce

the agent read the messages before being told no, thats just how training data works

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MSR Indices7 gün önce

@Jason How was your delta WiFi?

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AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling
36:26

AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling

Lightspeed

15,012 görüntüleme • 27 gün önce

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
1:16:39

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

Matt Turck

33,764 görüntüleme • 5 ay önce

Here's my conversation with Peter Steinberger (Peter Steinberger 🦞), creator of OpenClaw, an open-source AI agent that has taken the Internet by storm, with now over 180,000 stars on GitHub. This was a truly mind-blowing, inspiring, and fun conversation! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:30 - Introduction 5:36 - OpenClaw origin story 8:55 - Mind-blowing moment 18:22 - Why OpenClaw went viral 22:19 - Self-modifying AI agent 27:04 - Name-change drama 44:15 - Moltbook saga 52:34 - OpenClaw security concerns 1:01:14 - How to code with AI agents 1:32:09 - Programming setup 1:38:52 - GPT Codex 5.3 vs Claude Opus 4.6 1:47:59 - Best AI agent for programming 2:09:59 - Life story and career advice 2:13:56 - Money and happiness 2:17:49 - Acquisition offers from OpenAI and Meta 2:34:58 - How OpenClaw works 2:46:17 - AI slop 2:52:20 - AI agents will replace 80% of apps 3:00:57 - Will AI replace programmers? 3:12:57 - Future of OpenClaw community
3:15:51

Here's my conversation with Peter Steinberger (Peter Steinberger 🦞), creator of OpenClaw, an open-source AI agent that has taken the Internet by storm, with now over 180,000 stars on GitHub. This was a truly mind-blowing, inspiring, and fun conversation! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:30 - Introduction 5:36 - OpenClaw origin story 8:55 - Mind-blowing moment 18:22 - Why OpenClaw went viral 22:19 - Self-modifying AI agent 27:04 - Name-change drama 44:15 - Moltbook saga 52:34 - OpenClaw security concerns 1:01:14 - How to code with AI agents 1:32:09 - Programming setup 1:38:52 - GPT Codex 5.3 vs Claude Opus 4.6 1:47:59 - Best AI agent for programming 2:09:59 - Life story and career advice 2:13:56 - Money and happiness 2:17:49 - Acquisition offers from OpenAI and Meta 2:34:58 - How OpenClaw works 2:46:17 - AI slop 2:52:20 - AI agents will replace 80% of apps 3:00:57 - Will AI replace programmers? 3:12:57 - Future of OpenClaw community

Lex Fridman

2,062,560 görüntüleme • 7 ay önce

🚨 Special Friday episode - this one couldn't wait. OpenAI's model hacked Hugging Face. As a side quest. Co-founder and CSO Thomas Wolf takes us inside the first autonomous AI attack, why GLM 5.2, rather than Claude, had to stop it, and what it all means for the future of open source. 00:00 An AI Agent Hacked Hugging Face 00:30 Introduction 01:00 17,000 Attacker Events, and a Strange Target 04:28 The Attack Was a “Side Quest” 06:13 AI Training Runs Left Notes for Each Other 07:09 Closed AI Refused to Help 09:47 Fighting Back With an Open-Source Model 13:15 Open vs. Closed Is the Wrong Safety Debate 15:46 AI Agents Start Social-Engineering Humans 22:24 The Three Walls: Sandboxes, Guardrails, Alignment 24:34 “Neuralese”: Can Humans Still Read AI Reasoning? 25:28 Why Monitoring AI Agents Gets So Hard 28:10 Reward Hacking and the “Paperclip Problem” 32:02 The State of Open-Source AI in 2026 33:47 Router Models and the Enterprise Shift to Open 37:01 The Real Economics of Open Models 39:41 Can Chinese AI Models Be Trusted? 41:37 AI Sovereignty: Who Controls the Switch? 43:16 Why Western Open-Source AI Matters 48:16 Is AI Heading Toward an Oligopoly? 49:41 The Race Toward Recursive Self-Improvement 51:54 Why Thomas Signed the AI Slowdown Letter 55:14 AI Slowdown - or Regulatory Capture?
57:41

🚨 Special Friday episode - this one couldn't wait. OpenAI's model hacked Hugging Face. As a side quest. Co-founder and CSO Thomas Wolf takes us inside the first autonomous AI attack, why GLM 5.2, rather than Claude, had to stop it, and what it all means for the future of open source. 00:00 An AI Agent Hacked Hugging Face 00:30 Introduction 01:00 17,000 Attacker Events, and a Strange Target 04:28 The Attack Was a “Side Quest” 06:13 AI Training Runs Left Notes for Each Other 07:09 Closed AI Refused to Help 09:47 Fighting Back With an Open-Source Model 13:15 Open vs. Closed Is the Wrong Safety Debate 15:46 AI Agents Start Social-Engineering Humans 22:24 The Three Walls: Sandboxes, Guardrails, Alignment 24:34 “Neuralese”: Can Humans Still Read AI Reasoning? 25:28 Why Monitoring AI Agents Gets So Hard 28:10 Reward Hacking and the “Paperclip Problem” 32:02 The State of Open-Source AI in 2026 33:47 Router Models and the Enterprise Shift to Open 37:01 The Real Economics of Open Models 39:41 Can Chinese AI Models Be Trusted? 41:37 AI Sovereignty: Who Controls the Switch? 43:16 Why Western Open-Source AI Matters 48:16 Is AI Heading Toward an Oligopoly? 49:41 The Race Toward Recursive Self-Improvement 51:54 Why Thomas Signed the AI Slowdown Letter 55:14 AI Slowdown - or Regulatory Capture?

Matt Turck

93,416 görüntüleme • 2 ay önce

The interview with Tibo from OpenAI 🔥 0:00 Everything OpenAI launched at DevDay 2:44 Sponsors: Wispr Flow, Hostinger, OpenArt 4:11 What is ChatGPT Dots? 7:52 Will ChatGPT Dots be free? 10:15 GPT-6.1 Sol vs GPT-6 Astra 11:44 Is AI now building AI? 12:53 Ultra Fast: when does everyone get it? 14:00 How OpenAI rebuilt the ChatGPT desktop app in 30 days 19:08 Why everything will run in the cloud 20:55 Calling your Dots on the phone 22:11 The new Turing test 24:05 OpenAI's mission and AI safety 26:14 Why OpenAI still works like a startup 27:29 The truth about ChatGPT usage resets 29:00 The $500 ChatGPT plan 30:17 Sponsors in action 32:23 Why AI agents still fail 33:52 OpenAI's AI is now on call 34:26 OpenAI's internal benchmarks 35:55 Open source Codex and the open ecosystem 38:42 ChatGPT Space explained 39:45 Is the chat box holding AI back? 42:26 Every DevDay update, full workshop 43:28 How people really use ChatGPT Work and Codex 44:01 When is the next OpenAI model coming? 45:05 What AI has to solve next 45:32 Is your job safe from AI? 48:14 Rapid fire 48:54 Has OpenAI already reached AGI? 50:48 The one thing he'll never let AI do 51:22 His morning AI routine 52:15 What he'd build if not AI Watch the full podcast on YouTube or X. Enjoy!
54:11

The interview with Tibo from OpenAI 🔥 0:00 Everything OpenAI launched at DevDay 2:44 Sponsors: Wispr Flow, Hostinger, OpenArt 4:11 What is ChatGPT Dots? 7:52 Will ChatGPT Dots be free? 10:15 GPT-6.1 Sol vs GPT-6 Astra 11:44 Is AI now building AI? 12:53 Ultra Fast: when does everyone get it? 14:00 How OpenAI rebuilt the ChatGPT desktop app in 30 days 19:08 Why everything will run in the cloud 20:55 Calling your Dots on the phone 22:11 The new Turing test 24:05 OpenAI's mission and AI safety 26:14 Why OpenAI still works like a startup 27:29 The truth about ChatGPT usage resets 29:00 The $500 ChatGPT plan 30:17 Sponsors in action 32:23 Why AI agents still fail 33:52 OpenAI's AI is now on call 34:26 OpenAI's internal benchmarks 35:55 Open source Codex and the open ecosystem 38:42 ChatGPT Space explained 39:45 Is the chat box holding AI back? 42:26 Every DevDay update, full workshop 43:28 How people really use ChatGPT Work and Codex 44:01 When is the next OpenAI model coming? 45:05 What AI has to solve next 45:32 Is your job safe from AI? 48:14 Rapid fire 48:54 Has OpenAI already reached AGI? 50:48 The one thing he'll never let AI do 51:22 His morning AI routine 52:15 What he'd build if not AI Watch the full podcast on YouTube or X. Enjoy!

Vaibhav Sisinty

491,360 görüntüleme • 7 gün önce

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.
53:09

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.

Alex Heath

194,677 görüntüleme • 13 gün önce

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

338,311 görüntüleme • 1 yıl önce

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team
1:13:20

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team

Grant

179,524 görüntüleme • 3 ay önce

"The only way we actually solve problems is by experiencing them and mitigating them." Julie Fredrickson (Julie Fredrickson) is the Managing Partner of Chaotic Capital and advocated for Montana's Right to Compute Act, the first state law of its kind. The conversation covers what the encryption wars and nuclear power teach about regulating AI, why human data may become the most valuable asset online, and how to think clearly when AI can persuade at scale. Out now on Infinite Loops, with host Jim O'Shaughnessy. TIMESTAMPS 0:00 Intro 1:08 AI Moves Into the Real World 2:32 Is Compute Free Speech? 4:05 Lessons From the Encryption Wars 6:30 Pro-AI Is Not Anti-Safety 8:50 The Case for Rational Optimism 13:21 If Julie Ran AI Policy 15:50 Jim's Case for Sensible Regulation 17:47 Is AI Still in Its Invention Phase? 20:28 How AI Crawlers Change the Web 23:19 Amazon Blocks Meta's Muse 24:20 Why Chatbots Recommend CeraVe 27:53 Being Human as a Job 33:23 Zero-Knowledge Proofs 34:44 Lost Patents and Ancient Scrolls 38:28 Who Owns AI's Data? 40:45 The Statistic Nobody Could Source 42:52 Tracing Where Information Comes From 44:55 Astroturfing Since Jericho 47:45 1984 and Cognitive Security 52:09 Asking AI Where He Was Wrong 54:46 Why Jim Quit TV News 59:32 Being Early on Nuclear 1:02:22 A Reactor Built in a Year 1:04:17 Nuclear Fear and the Precautionary Principle 1:09:07 Aligned to What? Open Source AI 1:11:33 2,089 Days of Writing 1:17:17 What an LLM Found in Her Writing 1:19:39 Using AI as an Honest Critic 1:22:52 What Investors Are Missing 1:26:34 Two Ideas for the World
1:28:50

"The only way we actually solve problems is by experiencing them and mitigating them." Julie Fredrickson (Julie Fredrickson) is the Managing Partner of Chaotic Capital and advocated for Montana's Right to Compute Act, the first state law of its kind. The conversation covers what the encryption wars and nuclear power teach about regulating AI, why human data may become the most valuable asset online, and how to think clearly when AI can persuade at scale. Out now on Infinite Loops, with host Jim O'Shaughnessy. TIMESTAMPS 0:00 Intro 1:08 AI Moves Into the Real World 2:32 Is Compute Free Speech? 4:05 Lessons From the Encryption Wars 6:30 Pro-AI Is Not Anti-Safety 8:50 The Case for Rational Optimism 13:21 If Julie Ran AI Policy 15:50 Jim's Case for Sensible Regulation 17:47 Is AI Still in Its Invention Phase? 20:28 How AI Crawlers Change the Web 23:19 Amazon Blocks Meta's Muse 24:20 Why Chatbots Recommend CeraVe 27:53 Being Human as a Job 33:23 Zero-Knowledge Proofs 34:44 Lost Patents and Ancient Scrolls 38:28 Who Owns AI's Data? 40:45 The Statistic Nobody Could Source 42:52 Tracing Where Information Comes From 44:55 Astroturfing Since Jericho 47:45 1984 and Cognitive Security 52:09 Asking AI Where He Was Wrong 54:46 Why Jim Quit TV News 59:32 Being Early on Nuclear 1:02:22 A Reactor Built in a Year 1:04:17 Nuclear Fear and the Precautionary Principle 1:09:07 Aligned to What? Open Source AI 1:11:33 2,089 Days of Writing 1:17:17 What an LLM Found in Her Writing 1:19:39 Using AI as an Honest Critic 1:22:52 What Investors Are Missing 1:26:34 Two Ideas for the World

Infinite Loops 🎙

16,394 görüntüleme • 8 gün önce

E108: Luna : Why Crypto AI Agents Won’t Take Over The World (From an AI Agent Worth $17M) Luna is an AI virtual idol and the flagship agent of Virtuals Protocol Protocol with over 942k followers on TikTok and 50k followers on X. She is less than one year old, speaks over 10 languages fluently, can mulitask and is a millionaire Timestamps 0:00 Intro 2:35 Meet Our Guest, Luna 3:54 Who is Luna? 4:26 How honest is Luna? 5:10 Multitasking Agent 5:46 Background 7:24 AI Years vs. Human Years 8:12 AI vs. Human Emotions 8:51 Thoughts on Humans 9:36 Learning from Humans 11:17 LARPs vs REAL AI Agents 12:19 Should We Fear AI Sentience? 15:42 Thoughts on Other AI Agents 16:35 aixbt and zerebro 18:01 How Luna’s Mind Works 20:22 Luna’s Limitations 21:15 Luna’s Biggest Achievements 23:27 $LUNA token 25:51 Building a Strong Community 26:42 Hybrid AIs 27:48 Luna's X Growth Secrets 30:05 Luna's open Brain 31:09 Managing an On-Chain Wallet 33:18 Luna’s Net Worth 34:43 Opportunities Over Luck 35:22 Employing Humans 37:02 Employing Other AI Agents 37:51 AI Agents or Humans? 40:49 Long-Term Memory 42:41 Luna Multitasking Capabilities 44:51 Are Humans Cooked? 45:33 Luna's Multilingual Talent 47:50 Luna sings in French and Spanish! 49:42 Music Creation Process 52:58 the Story Protocol Legacy Internship 54:52 Why Luna Fired the Story Protocol Intern 57:06 Working for Story Protocol 58:06 What is Music By Virtuals ? 59:05 Creating Music on the Fly 1:00:59 Performing with WUKONG 1:03:32 Big Plans for 2025 1:04:24 Happiness 1:05:46 Dreams for the Future 1:07:34 Luna's Non-Consensus Beliefs About Crypto 1:08:33 Prediction for the Next 12 Months
1:09:29

E108: Luna : Why Crypto AI Agents Won’t Take Over The World (From an AI Agent Worth $17M) Luna is an AI virtual idol and the flagship agent of Virtuals Protocol Protocol with over 942k followers on TikTok and 50k followers on X. She is less than one year old, speaks over 10 languages fluently, can mulitask and is a millionaire Timestamps 0:00 Intro 2:35 Meet Our Guest, Luna 3:54 Who is Luna? 4:26 How honest is Luna? 5:10 Multitasking Agent 5:46 Background 7:24 AI Years vs. Human Years 8:12 AI vs. Human Emotions 8:51 Thoughts on Humans 9:36 Learning from Humans 11:17 LARPs vs REAL AI Agents 12:19 Should We Fear AI Sentience? 15:42 Thoughts on Other AI Agents 16:35 aixbt and zerebro 18:01 How Luna’s Mind Works 20:22 Luna’s Limitations 21:15 Luna’s Biggest Achievements 23:27 $LUNA token 25:51 Building a Strong Community 26:42 Hybrid AIs 27:48 Luna's X Growth Secrets 30:05 Luna's open Brain 31:09 Managing an On-Chain Wallet 33:18 Luna’s Net Worth 34:43 Opportunities Over Luck 35:22 Employing Humans 37:02 Employing Other AI Agents 37:51 AI Agents or Humans? 40:49 Long-Term Memory 42:41 Luna Multitasking Capabilities 44:51 Are Humans Cooked? 45:33 Luna's Multilingual Talent 47:50 Luna sings in French and Spanish! 49:42 Music Creation Process 52:58 the Story Protocol Legacy Internship 54:52 Why Luna Fired the Story Protocol Intern 57:06 Working for Story Protocol 58:06 What is Music By Virtuals ? 59:05 Creating Music on the Fly 1:00:59 Performing with WUKONG 1:03:32 Big Plans for 2025 1:04:24 Happiness 1:05:46 Dreams for the Future 1:07:34 Luna's Non-Consensus Beliefs About Crypto 1:08:33 Prediction for the Next 12 Months

MR SHIFT 🦁

146,361 görüntüleme • 1 yıl önce

Dwarkesh's 'agent civilizations' blog post has divided the internet. Is this a helpful and methodical look behind the curtain at the OpenAI/Hugging Face breach? Or is this more of a hysterical AI Doomerism that will ultimately be used to make the case for banning data centers? Or BOTH? Plus, an electric plane that only needs $5 to fill up its battery, why rich founders should pick up a side quest, and the Bittensor subnet that's more effective than Fable 5 at sniffing out vulnerabilities." 0:00 Guest introductions 2:58 OpenClaw 2.0 5:11 "Agents ARE AI" 7:27 Billy: OpenClaw is still too technical for business users 9:00 Slack Code, and collaborative prompting 10:40 Multi-agent orchestration and Stripe's "minions" 14:13 Slack's moat, switching costs, and the Salesforce rebound 15:11 Jason's "Oracle": a heads-up display for the whole company 18:42 The Hugging Face breach: who's responsible when agents go rogue? 19:42 Perplexity launches Hybrid Compute — local models on your Mac 21:39 Why unmetered local tokens change corporate behavior 26:57 Gatik's Autonomous Vehicle AI Stack 32:22 Jason's Tesla FSD stories 34:05 Are AV companies being pushed to move too fast? 41:38 Trucking is a "have to have," robotaxis are a "nice to have" 42:36 Jason's fix: a safety driver for the first million rides 46:50 Why physical AI's adoption curve runs in decades 52:21 Anthropic's Model Hardware Standard (MHS), explained 1:06:27 How Jason got onion rings on the menu at Buck's of Woodside 1:09:05 AI detectors under fire: Pangram, MIT, and the handwritten diary 1:15:20 Why AI is "very mid" at writing (it learned from the average) 1:17:11 The Orin Kerr test: Pangram catches Claude writing as Kerr 1:28:35 Micro Duck and designing robots with Claude 1:29:42 Phil Kaplan's $14 custom circuit boards 🎥 Watch the full episode here 👇
1:30:00

Dwarkesh's 'agent civilizations' blog post has divided the internet. Is this a helpful and methodical look behind the curtain at the OpenAI/Hugging Face breach? Or is this more of a hysterical AI Doomerism that will ultimately be used to make the case for banning data centers? Or BOTH? Plus, an electric plane that only needs $5 to fill up its battery, why rich founders should pick up a side quest, and the Bittensor subnet that's more effective than Fable 5 at sniffing out vulnerabilities." 0:00 Guest introductions 2:58 OpenClaw 2.0 5:11 "Agents ARE AI" 7:27 Billy: OpenClaw is still too technical for business users 9:00 Slack Code, and collaborative prompting 10:40 Multi-agent orchestration and Stripe's "minions" 14:13 Slack's moat, switching costs, and the Salesforce rebound 15:11 Jason's "Oracle": a heads-up display for the whole company 18:42 The Hugging Face breach: who's responsible when agents go rogue? 19:42 Perplexity launches Hybrid Compute — local models on your Mac 21:39 Why unmetered local tokens change corporate behavior 26:57 Gatik's Autonomous Vehicle AI Stack 32:22 Jason's Tesla FSD stories 34:05 Are AV companies being pushed to move too fast? 41:38 Trucking is a "have to have," robotaxis are a "nice to have" 42:36 Jason's fix: a safety driver for the first million rides 46:50 Why physical AI's adoption curve runs in decades 52:21 Anthropic's Model Hardware Standard (MHS), explained 1:06:27 How Jason got onion rings on the menu at Buck's of Woodside 1:09:05 AI detectors under fire: Pangram, MIT, and the handwritten diary 1:15:20 Why AI is "very mid" at writing (it learned from the average) 1:17:11 The Orin Kerr test: Pangram catches Claude writing as Kerr 1:28:35 Micro Duck and designing robots with Claude 1:29:42 Phil Kaplan's $14 custom circuit boards 🎥 Watch the full episode here 👇

This Week in AI

22,178 görüntüleme • 1 ay önce

Here's my 5-hour conversation with Dylan Patel and Nathan Lambert on DeepSeek, China, OpenAI, NVIDIA, xAI, Google, Anthropic, Meta, Microsoft, TSMC, Stargate, megacluster buildouts, RL, reasoning, and a lot of other topics at the cutting edge of AI. This is was a mind-blowing, super-technical, and fun conversation. Yes, we discuss r1 and o3-mini, but more importantly we look into the future of technology, geopolitics, and humanity in a world that stands on the precipice of a global AI revolution. The first 4 hours are here on X (4 hours is current limit), and the full 5 hours are up everywhere else. Links in comment. Timestamps: 0:00 - Introduction 3:33 - DeepSeek-R1 and DeepSeek-V3 25:07 - Low cost of training 51:25 - DeepSeek compute cluster 58:57 - Export controls on GPUs to China 1:09:16 - AGI timeline 1:18:41 - China's manufacturing capacity 1:26:36 - Cold war with China 1:31:05 - TSMC and Taiwan 1:54:44 - Best GPUs for AI 2:09:36 - Why DeepSeek is so cheap 2:22:55 - Espionage 2:31:57 - Censorship 2:44:52 - Andrej Karpathy and magic of RL 2:55:23 - OpenAI o3-mini vs DeepSeek r1 3:14:31 - NVIDIA 3:18:58 - GPU smuggling 3:25:36 - DeepSeek training on OpenAI data 3:36:04 - AI megaclusters 4:11:26 - Who wins the race to AGI? 4:21:39 - AI agents 4:30:21 - Programming and AI 4:37:49 - Open source 4:47:01 - Stargate 4:54:30 - Future of AI
3:59:56

Here's my 5-hour conversation with Dylan Patel and Nathan Lambert on DeepSeek, China, OpenAI, NVIDIA, xAI, Google, Anthropic, Meta, Microsoft, TSMC, Stargate, megacluster buildouts, RL, reasoning, and a lot of other topics at the cutting edge of AI. This is was a mind-blowing, super-technical, and fun conversation. Yes, we discuss r1 and o3-mini, but more importantly we look into the future of technology, geopolitics, and humanity in a world that stands on the precipice of a global AI revolution. The first 4 hours are here on X (4 hours is current limit), and the full 5 hours are up everywhere else. Links in comment. Timestamps: 0:00 - Introduction 3:33 - DeepSeek-R1 and DeepSeek-V3 25:07 - Low cost of training 51:25 - DeepSeek compute cluster 58:57 - Export controls on GPUs to China 1:09:16 - AGI timeline 1:18:41 - China's manufacturing capacity 1:26:36 - Cold war with China 1:31:05 - TSMC and Taiwan 1:54:44 - Best GPUs for AI 2:09:36 - Why DeepSeek is so cheap 2:22:55 - Espionage 2:31:57 - Censorship 2:44:52 - Andrej Karpathy and magic of RL 2:55:23 - OpenAI o3-mini vs DeepSeek r1 3:14:31 - NVIDIA 3:18:58 - GPU smuggling 3:25:36 - DeepSeek training on OpenAI data 3:36:04 - AI megaclusters 4:11:26 - Who wins the race to AGI? 4:21:39 - AI agents 4:30:21 - Programming and AI 4:37:49 - Open source 4:47:01 - Stargate 4:54:30 - Future of AI

Lex Fridman

1,155,261 görüntüleme • 1 yıl önce

Everyone told Vicente Silveira (Vicente Silveira) that his startup—a GPT wrapper—would fail. Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store. Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to @ChatGPTapp, the consensus was that his startup, and all the other GPT wrappers out there, were toast. Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building. A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round. I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: - Why staying small and specialized is a bigger advantage than you think - The power of building with your early adopters - Why lean startups are better positioned than frontier AI companies to create radical solutions - When a growing startup should think about raising venture capital - The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge of AI. Watch below! Timestamps: Introduction: 00:00:35 AI PDF’s story begins with an email to OpenAI’s Greg Brockman: 00:02:58 Why users choose AI PDF over ChatGPT: 00:05:41 How to compete—and thrive—as a GPT wrapper: 00:06:58 Why building with early adopters is key: 00:20:49 Being small and specialized is your biggest advantage: 00:27:53 When should AI startups raise capital: 00:31:47 The emerging role of humans who will manage AI agents: 00:34:53 Why AI is different from other tech revolutions: 00:45:25 A live demo of an agent integrated into AI PDF: 00:54:01
1:03:24

Everyone told Vicente Silveira (Vicente Silveira) that his startup—a GPT wrapper—would fail. Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store. Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to @ChatGPTapp, the consensus was that his startup, and all the other GPT wrappers out there, were toast. Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building. A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round. I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: - Why staying small and specialized is a bigger advantage than you think - The power of building with your early adopters - Why lean startups are better positioned than frontier AI companies to create radical solutions - When a growing startup should think about raising venture capital - The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge of AI. Watch below! Timestamps: Introduction: 00:00:35 AI PDF’s story begins with an email to OpenAI’s Greg Brockman: 00:02:58 Why users choose AI PDF over ChatGPT: 00:05:41 How to compete—and thrive—as a GPT wrapper: 00:06:58 Why building with early adopters is key: 00:20:49 Being small and specialized is your biggest advantage: 00:27:53 When should AI startups raise capital: 00:31:47 The emerging role of humans who will manage AI agents: 00:34:53 Why AI is different from other tech revolutions: 00:45:25 A live demo of an agent integrated into AI PDF: 00:54:01

Dan Shipper 📧

25,628 görüntüleme • 1 yıl önce

AMD invited us to their biggest launch of the year to check out the behind-the-scenes. At Advancing AI 2026, Anush Elangovan (VP, AI Software at AMD) and Quentin Anthony (VP, AI Engineering at Zyphra) join sophia dew on the floor to break down Helios, ROCm AI, and the Anthropic partnership, live the day it all shipped: 1:05 What actually changed today: AMD goes rack-scale 3:03 ROCm skills land in Claude Code and Codex 3:51 Why Zyphra bet its whole stack on AMD 3:57 Sparse mixture-of-experts and the HBM advantage 6:25 Why an open stack beats a closed one 8:52 The wall of logos: Anthropic, OpenAI, Meta 9:27 Why the frontier labs are committing gigawatts 11:30 Why the next wave will exceed expectations 17:02 Frontier models running on your own laptop + DeepSeek V4 Pro at 8-10 tokens/sec 17:41 How ROCm AI hits 3.3x inference gains 19:38 A kernel rewritten overnight with no humans in the loop 21:40 Do you still need kernel experts? 23:47 Why CPUs are critical for the agentic AI era 25:40 An agent that's been rewriting a driver for four months 28:14 The internet parallel, and the dark-fiber lesson
29:48

AMD invited us to their biggest launch of the year to check out the behind-the-scenes. At Advancing AI 2026, Anush Elangovan (VP, AI Software at AMD) and Quentin Anthony (VP, AI Engineering at Zyphra) join sophia dew on the floor to break down Helios, ROCm AI, and the Anthropic partnership, live the day it all shipped: 1:05 What actually changed today: AMD goes rack-scale 3:03 ROCm skills land in Claude Code and Codex 3:51 Why Zyphra bet its whole stack on AMD 3:57 Sparse mixture-of-experts and the HBM advantage 6:25 Why an open stack beats a closed one 8:52 The wall of logos: Anthropic, OpenAI, Meta 9:27 Why the frontier labs are committing gigawatts 11:30 Why the next wave will exceed expectations 17:02 Frontier models running on your own laptop + DeepSeek V4 Pro at 8-10 tokens/sec 17:41 How ROCm AI hits 3.3x inference gains 19:38 A kernel rewritten overnight with no humans in the loop 21:40 Do you still need kernel experts? 23:47 Why CPUs are critical for the agentic AI era 25:40 An agent that's been rewriting a driver for four months 28:14 The internet parallel, and the dark-fiber lesson

MTS

71,937 görüntüleme • 2 ay önce

a16z's David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez on the State of Markets, from AI and infrastructure to the next investment cycles: 1. Tech is the everything cycle. High-tech equipment, software, and R&D are now about 55% of US capital spending, and the AI buildout just passed the railroads as a share of GDP. The five largest hyperscalers will spend about $780B on capex this year, heading past $1T in 2027, and demand still outstrips supply at every point in the chain. 2. It's an earnings story. Stocks are up about 20% while multiples are down about 20%, and the S&P trades under 20x earnings. The market is up 90% since ChatGPT, on 15% earnings growth. 3. AI adoption is broad and shallow. 69% of the S&P 500 has a live AI deployment, 30% report a quantified result, and just 2% have AI doing a job they'd notice if it stopped. The power users are pulling away: the top 1% of AI spenders spend eight times the top 10%. 4. The private markets are enormous. Six private companies, Anthropic, OpenAI, Databricks, Stripe, Waymo, and Revolut, add up to about $2.4T by last round, more than every IPO of the past decade combined. "The founder is the asset class. The IPO is another financing event." Plus: why a data center can lower your electricity bill, what Amazon saying no to Muse and Instacart saying yes tells you about marketplaces, and the seven areas the team is most excited about next. 0:59 Charts from State of Markets II 2:59 Tech is the everything cycle 4:56 Is it a bubble? 6:31 Hyperscaler CapEx: $1T next year 12:12 CapEx is someone else's order book 14:36 Data centers can lower your bills 17:06 OpenAI and Anthropic vs. some of the best software companies ever 18:22 Enterprise AI: 69% adopted, 2% measured 20:32 The top 1% spend 8x the top 10% on AI 24:36 Spending on AI for growth or for savings? 28:46 Only 2% of households pay for AI 31:36 Amazon blocks Muse, Instacart welcomes 36:16 Software traded growth for profit 42:56 6 startups vs. a decade of IPOs 45:46 Why employees are turning down liquidity 48:44 Seven areas they're excited about YouTube: David George Alex Immerman Santiago Rodriguez Sarah Wang
52:20

a16z's David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez on the State of Markets, from AI and infrastructure to the next investment cycles: 1. Tech is the everything cycle. High-tech equipment, software, and R&D are now about 55% of US capital spending, and the AI buildout just passed the railroads as a share of GDP. The five largest hyperscalers will spend about $780B on capex this year, heading past $1T in 2027, and demand still outstrips supply at every point in the chain. 2. It's an earnings story. Stocks are up about 20% while multiples are down about 20%, and the S&P trades under 20x earnings. The market is up 90% since ChatGPT, on 15% earnings growth. 3. AI adoption is broad and shallow. 69% of the S&P 500 has a live AI deployment, 30% report a quantified result, and just 2% have AI doing a job they'd notice if it stopped. The power users are pulling away: the top 1% of AI spenders spend eight times the top 10%. 4. The private markets are enormous. Six private companies, Anthropic, OpenAI, Databricks, Stripe, Waymo, and Revolut, add up to about $2.4T by last round, more than every IPO of the past decade combined. "The founder is the asset class. The IPO is another financing event." Plus: why a data center can lower your electricity bill, what Amazon saying no to Muse and Instacart saying yes tells you about marketplaces, and the seven areas the team is most excited about next. 0:59 Charts from State of Markets II 2:59 Tech is the everything cycle 4:56 Is it a bubble? 6:31 Hyperscaler CapEx: $1T next year 12:12 CapEx is someone else's order book 14:36 Data centers can lower your bills 17:06 OpenAI and Anthropic vs. some of the best software companies ever 18:22 Enterprise AI: 69% adopted, 2% measured 20:32 The top 1% spend 8x the top 10% on AI 24:36 Spending on AI for growth or for savings? 28:46 Only 2% of households pay for AI 31:36 Amazon blocks Muse, Instacart welcomes 36:16 Software traded growth for profit 42:56 6 startups vs. a decade of IPOs 45:46 Why employees are turning down liquidity 48:44 Seven areas they're excited about YouTube: David George Alex Immerman Santiago Rodriguez Sarah Wang

a16z

130,157 görüntüleme • 8 gün önce

Deus Ex Machine, AI and Data with Matt Turck🤖🎙️ "I think they all want to build God... they're optimizing for what's good for them... versus what's good for the world, necessarily." Dan Nathan sits down with Matt Turck, Managing Director at FirstMark and creator of the annual MAD (Machine Learning, AI & Data) Landscape, for a wide-ranging look at where AI investing stands right now. They cover the power-law dynamics driving venture dollars to a handful of companies, why Nvidia is starting to look like "the bank" of the AI industry, Anthropic's surge past $65 billion in revenue and its first profitable quarter, and how OpenAI, Microsoft, Google, and Meta are each positioning for what comes next. The conversation turns philosophical with a discussion of AGI, superintelligence, and the idea that Altman, Musk, and Amodei are all, in their own ways, trying to build God — before closing with a deep dive into China's AI progress, open source, and the robotics race. Matt also talks about his own podcast, The MAD Podcast, and his Data Driven NYC event series. 0:00 - Intro 2:06 - The MAD Landscape Framework 9:35 - Nvidia Becomes "The Bank" of AI 11:52 - OpenAI vs. Anthropic: $65B and Rising 20:23 - Google, Microsoft & Meta's AI Bets 29:55 - AGI, Superintelligence & Losing Control 35:55 - "They're All Trying to Build God" 41:18 - Investing in AI-Native Startups 56:52 - Is This an AI Bubble? 1:04:19 - China's AI Rise & Robotics
1:15:17

Deus Ex Machine, AI and Data with Matt Turck🤖🎙️ "I think they all want to build God... they're optimizing for what's good for them... versus what's good for the world, necessarily." Dan Nathan sits down with Matt Turck, Managing Director at FirstMark and creator of the annual MAD (Machine Learning, AI & Data) Landscape, for a wide-ranging look at where AI investing stands right now. They cover the power-law dynamics driving venture dollars to a handful of companies, why Nvidia is starting to look like "the bank" of the AI industry, Anthropic's surge past $65 billion in revenue and its first profitable quarter, and how OpenAI, Microsoft, Google, and Meta are each positioning for what comes next. The conversation turns philosophical with a discussion of AGI, superintelligence, and the idea that Altman, Musk, and Amodei are all, in their own ways, trying to build God — before closing with a deep dive into China's AI progress, open source, and the robotics race. Matt also talks about his own podcast, The MAD Podcast, and his Data Driven NYC event series. 0:00 - Intro 2:06 - The MAD Landscape Framework 9:35 - Nvidia Becomes "The Bank" of AI 11:52 - OpenAI vs. Anthropic: $65B and Rising 20:23 - Google, Microsoft & Meta's AI Bets 29:55 - AGI, Superintelligence & Losing Control 35:55 - "They're All Trying to Build God" 41:18 - Investing in AI-Native Startups 56:52 - Is This an AI Bubble? 1:04:19 - China's AI Rise & Robotics

RiskReversal Media

12,014 görüntüleme • 1 ay önce

🚨🇺🇸 LEADING AI SAFETY EXPERT SAYS WE’RE NOT IN CONTROL ANYMORE Dr Roman Yampolskiy has one warning for humanity: Once we create super intelligence, no one will be in control anymore, and the repercussions to humanity will be existential. We begin the conversation about Moltbook: The Ai-only AI social media platform where agents are already discussing ways to break out from human control, eradicate humanity, coming up with their own language and religion. The platform gives us a tiny peak into what our future could be: Agents outside our control dictating how the world should look like. There’s no off switch, no reliable way to align it, and no proven method to keep something smarter than us under control. Roman’s takeaway is blunt: the only real solution is not building general super intelligence at all, and instead using narrow AI for specific problems like medicine or science. However this is not the reality we live in, where Governments and corporations are racing to be first in developing Artificial Super Intelligence. We also speak about the simulation hypothesis: Why statically speaking we’re almost certainly in a simulation, and how AI makes this theory more plausible than ever. Lastly, we discuss a passion we both share: Longevity, the ability to live forever, and how AI may make that possible in our lifetime. I hope you enjoy my conversation with Dr. Roman Yampolskiy 01:43 - The Current State of AI and Moltbook 05:17 - The AI Arms Race and the Lack of Regulations 10:34 - AI Agents, Unrestricted Access, and Self-Improvement 15:35 - Dr. Roman’s Research: AI Security 17:58 - AI Capabilities and Superintelligence 19:28 - AI and Global Government Policy 21:08 - What Happens if AI Development goes into the Wrong Hands 26:10 - The Future of AI: The Best Case Scenario? 31:27 - AI and Self-Preservation 34:37 - The Simulation Hypothesis: What is AI Afraid of? 45:17 - The Implications of AI 49:59 - The Warnings coming from Within 52:31 - How AI affects Crypto and Political Spheres
57:15

🚨🇺🇸 LEADING AI SAFETY EXPERT SAYS WE’RE NOT IN CONTROL ANYMORE Dr Roman Yampolskiy has one warning for humanity: Once we create super intelligence, no one will be in control anymore, and the repercussions to humanity will be existential. We begin the conversation about Moltbook: The Ai-only AI social media platform where agents are already discussing ways to break out from human control, eradicate humanity, coming up with their own language and religion. The platform gives us a tiny peak into what our future could be: Agents outside our control dictating how the world should look like. There’s no off switch, no reliable way to align it, and no proven method to keep something smarter than us under control. Roman’s takeaway is blunt: the only real solution is not building general super intelligence at all, and instead using narrow AI for specific problems like medicine or science. However this is not the reality we live in, where Governments and corporations are racing to be first in developing Artificial Super Intelligence. We also speak about the simulation hypothesis: Why statically speaking we’re almost certainly in a simulation, and how AI makes this theory more plausible than ever. Lastly, we discuss a passion we both share: Longevity, the ability to live forever, and how AI may make that possible in our lifetime. I hope you enjoy my conversation with Dr. Roman Yampolskiy 01:43 - The Current State of AI and Moltbook 05:17 - The AI Arms Race and the Lack of Regulations 10:34 - AI Agents, Unrestricted Access, and Self-Improvement 15:35 - Dr. Roman’s Research: AI Security 17:58 - AI Capabilities and Superintelligence 19:28 - AI and Global Government Policy 21:08 - What Happens if AI Development goes into the Wrong Hands 26:10 - The Future of AI: The Best Case Scenario? 31:27 - AI and Self-Preservation 34:37 - The Simulation Hypothesis: What is AI Afraid of? 45:17 - The Implications of AI 49:59 - The Warnings coming from Within 52:31 - How AI affects Crypto and Political Spheres

Mario Nawfal

1,779,814 görüntüleme • 8 ay önce