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This is my sixth conversation with Gavin Baker. As always with Gavin, the conversation covers a lot of ground, but we spend the most time on watts and wafers. We discuss: - Why the wafer shortage may prevent an AI bubble - Data centers in space (reframed) - Elon's...

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Patrick OShaughnessy

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1,676,900 次观看 • 3 个月前 •via X (Twitter)

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This is my fifth conversation with Gavin Baker. Gavin understands semiconductors and AI as well as anyone I know and has a gift for making sense of the industry's complexity and nuance. We discuss: - Nvidia vs Google (GPUs + TPUs) - Scaling laws and reasoning models - The economics of AI compute - Why Blackwell's delay mattered - The bear case on the AI capex buildout - Data centers in space - The mistake SaaS companies are making Few people love investing more than Gavin. His closing answer about why he loves it turned into a full reflection on his investing origin story, which I had never heard before. Enjoy! Timestamps: 0:00 Intro 5:03 The Blackwell Transition 23:15 The Prisoner's Dilemma 27:12 The Bear Case: Edge AI 37:19 Meta, Open Source, and Model Depreciation 43:08 Geopolitics and Rare Earths 50:42 Data Centers in Space 56:06 Power Constraints as a Governor 1:11:31 The SaaS Mistake 1:16:17 Nuclear and Quantum 1:22:25 Gavin’s Investing Origins
1:28:25

This is my fifth conversation with Gavin Baker. Gavin understands semiconductors and AI as well as anyone I know and has a gift for making sense of the industry's complexity and nuance. We discuss: - Nvidia vs Google (GPUs + TPUs) - Scaling laws and reasoning models - The economics of AI compute - Why Blackwell's delay mattered - The bear case on the AI capex buildout - Data centers in space - The mistake SaaS companies are making Few people love investing more than Gavin. His closing answer about why he loves it turned into a full reflection on his investing origin story, which I had never heard before. Enjoy! Timestamps: 0:00 Intro 5:03 The Blackwell Transition 23:15 The Prisoner's Dilemma 27:12 The Bear Case: Edge AI 37:19 Meta, Open Source, and Model Depreciation 43:08 Geopolitics and Rare Earths 50:42 Data Centers in Space 56:06 Power Constraints as a Governor 1:11:31 The SaaS Mistake 1:16:17 Nuclear and Quantum 1:22:25 Gavin’s Investing Origins

Patrick OShaughnessy

2,859,057 次观看 • 8 个月前

My seventh conversation with Gavin Baker. It's about the gap between what the market is doing and what companies are seeing. It's been a tough month or so for public AI names, but there's no sign of a slowdown on the ground in Silicon Valley. We discuss: - Why old GPUs are getting more expensive - Open source vs the frontier - Claude as Wall Street's Walter Cronkite - Whether the buildout gets funded out of cash flow or debt - SpaceX as a data center company - And more Enjoy! TIMESTAMPS 0:00 Intro 1:17 AI Selloff vs. Fundamentals 10:20 Financing the AI Buildout 18:18 GPU Prices Keep Rising 24:23 Claude Moves Markets 29:01 What Could Break the Thesis 36:59 The Memory Supply War 42:08 Nvidia’s New Playbook 50:14 China and Open Source 61:51 Data Centers and Regulation 71:11 SpaceX and Orbital Compute
1:18:44

My seventh conversation with Gavin Baker. It's about the gap between what the market is doing and what companies are seeing. It's been a tough month or so for public AI names, but there's no sign of a slowdown on the ground in Silicon Valley. We discuss: - Why old GPUs are getting more expensive - Open source vs the frontier - Claude as Wall Street's Walter Cronkite - Whether the buildout gets funded out of cash flow or debt - SpaceX as a data center company - And more Enjoy! TIMESTAMPS 0:00 Intro 1:17 AI Selloff vs. Fundamentals 10:20 Financing the AI Buildout 18:18 GPU Prices Keep Rising 24:23 Claude Moves Markets 29:01 What Could Break the Thesis 36:59 The Memory Supply War 42:08 Nvidia’s New Playbook 50:14 China and Open Source 61:51 Data Centers and Regulation 71:11 SpaceX and Orbital Compute

Patrick OShaughnessy

1,826,147 次观看 • 1 个月前

FULL INTERVIEW: Dylan Patel joins TBPN at the Cisco AI summit to discuss data centers in space, the limits of today’s AI hardware, and how chips, power, and geopolitics will shape the future of AI infra. 0:00 Space data centers and space tourism 01:03 AI chips in space and servicing challenges 02:39 Tesla FSD vs GPU reliability 05:18 Nvidia, Groq, and specialized AI chips 06:41 Cerebras and speed-first inference 09:55 xAI rumors and space compute bets 11:00 Starlink power and scaling limits 15:38 TSMC vs energy bottlenecks 27:02 Chips to China and geopolitics 30:32 Claude code and vibe coding 36:44 Meta, wearables, and the AI bull case
43:42

FULL INTERVIEW: Dylan Patel joins TBPN at the Cisco AI summit to discuss data centers in space, the limits of today’s AI hardware, and how chips, power, and geopolitics will shape the future of AI infra. 0:00 Space data centers and space tourism 01:03 AI chips in space and servicing challenges 02:39 Tesla FSD vs GPU reliability 05:18 Nvidia, Groq, and specialized AI chips 06:41 Cerebras and speed-first inference 09:55 xAI rumors and space compute bets 11:00 Starlink power and scaling limits 15:38 TSMC vs energy bottlenecks 27:02 Chips to China and geopolitics 30:32 Claude code and vibe coding 36:44 Meta, wearables, and the AI bull case

TBPN

41,393 次观看 • 7 个月前

Had a great talk with Anjney Midha about why he left a16z to start AMP PBC (raised $1.3B), his early bet on Anthropic, the importance of Japan in AI, his class at Stanford and a lot more. I didn't make him cry like Harry Stebbings, but I think it was a fun conversation about the future of AI Infra. Enjoy! 00:00 Introduction to AMP and AI Infrastructure 03:07 Transition from A16Z to AMP 06:01 Understanding AMP's Role in AI Compute 08:57 The Concept of a Compute Grid 11:59 The Need for Standardization in AI Infrastructure 14:59 Education and Collaboration in AI Development 17:59 Global Perspectives on AI Infrastructure 21:03 Japan's Role in AI and Robotics 23:14 Cultural Connections: Japan and Germany 25:08 The Journey to Teaching at Stanford 26:04 Security in Infrastructure: Lessons Learned 27:50 Cybersecurity and AI: A New Frontier 29:27 The Importance of Redundancy in Cybersecurity 30:39 Investing in AI: The Anthropic Experience 32:54 Wealth Creation and Public Participation 34:06 Infrastructure Bottlenecks in AI Development 36:57 Global Perspectives on Data Centers 39:11 The Need for Education on AI Benefits 42:07 Learning from China: A Systems Approach 45:47 Conclusion: Coordinating the Western Frontier
46:14

Had a great talk with Anjney Midha about why he left a16z to start AMP PBC (raised $1.3B), his early bet on Anthropic, the importance of Japan in AI, his class at Stanford and a lot more. I didn't make him cry like Harry Stebbings, but I think it was a fun conversation about the future of AI Infra. Enjoy! 00:00 Introduction to AMP and AI Infrastructure 03:07 Transition from A16Z to AMP 06:01 Understanding AMP's Role in AI Compute 08:57 The Concept of a Compute Grid 11:59 The Need for Standardization in AI Infrastructure 14:59 Education and Collaboration in AI Development 17:59 Global Perspectives on AI Infrastructure 21:03 Japan's Role in AI and Robotics 23:14 Cultural Connections: Japan and Germany 25:08 The Journey to Teaching at Stanford 26:04 Security in Infrastructure: Lessons Learned 27:50 Cybersecurity and AI: A New Frontier 29:27 The Importance of Redundancy in Cybersecurity 30:39 Investing in AI: The Anthropic Experience 32:54 Wealth Creation and Public Participation 34:06 Infrastructure Bottlenecks in AI Development 36:57 Global Perspectives on Data Centers 39:11 The Need for Education on AI Benefits 42:07 Learning from China: A Systems Approach 45:47 Conclusion: Coordinating the Western Frontier

Nathan Lands

28,872 次观看 • 4 个月前

A New Episode of the Hivemind is Live! This week Tommy joins us to debate whether AI frontier companies can justify their valuations, the rise of open-source AI, and where enterprise spending is actually going. We also cover SpaceX’s IPO, Hyperliquid’s growth, and the latest around Zcash’s private Bitcoin thesis. Timestamps: 00:00 Introduction & Market Outlook 05:00 OpenAI, Anthropic & Enterprise AI Spending 08:53 Open Source vs Frontier Models 24:41 Are We In An AI Bubble? 35:17 SpaceX IPO & Equity Issuance 38:13 AI Regulation & Political Risk 53:36 Hyperliquid & HYPE 1:04:14 Zcash & The Private Bitcoin Thesis 1:13:16 Final Thoughts
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A New Episode of the Hivemind is Live! This week Tommy joins us to debate whether AI frontier companies can justify their valuations, the rise of open-source AI, and where enterprise spending is actually going. We also cover SpaceX’s IPO, Hyperliquid’s growth, and the latest around Zcash’s private Bitcoin thesis. Timestamps: 00:00 Introduction & Market Outlook 05:00 OpenAI, Anthropic & Enterprise AI Spending 08:53 Open Source vs Frontier Models 24:41 Are We In An AI Bubble? 35:17 SpaceX IPO & Equity Issuance 38:13 AI Regulation & Political Risk 53:36 Hyperliquid & HYPE 1:04:14 Zcash & The Private Bitcoin Thesis 1:13:16 Final Thoughts

Delphi Digital

21,214 次观看 • 2 个月前

My conversation with Dylan Patel on everything you ever wanted to know about the incredible buildout happening in AI infrastructure This is a whirlwind tour through the companies, deals, models, chips, power sources, partnerships, and people powering AI Dylan is some sort of genius. I wish a version of him existed for every subject. I hope you enjoy this as much as I did. Timestamps: 0:00 Introduction 0:39 The Infinite Money Glitch 4:42 Oracle's Bet on OpenAI 6:06 Nvidia's Strategic Investment and Deal Mechanics 9:17 Why Bigger Models Aren't Always Better 15:07 The Adoption Curve Problem 19:01 The Tokenomics of AI 23:59 Over-Parameterization and Model Learning 28:10 Building Environments for AI Training 32:16 AI in Everyday Life 34:46 The Future of Reasoning and Compute Scaling 44:34 The Spectrum of AI Optimism 46:29 Timeline to AGI 49:25 Talent Wars 58:37 Power Dynamics in the AI Ecosystem 1:18:42 AI for Material Science and Hard Tech 1:22:21 Building Infrastructure 1:29:55 US vs China: Who Really Needs AI to Win? 1:37:42 Favorite AI Bears 1:48:08 Speed Round: Company Impressions 1:55:11 The Death of Traditional SaaS Business Models 2:00:24 The Kindest Thing
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My conversation with Dylan Patel on everything you ever wanted to know about the incredible buildout happening in AI infrastructure This is a whirlwind tour through the companies, deals, models, chips, power sources, partnerships, and people powering AI Dylan is some sort of genius. I wish a version of him existed for every subject. I hope you enjoy this as much as I did. Timestamps: 0:00 Introduction 0:39 The Infinite Money Glitch 4:42 Oracle's Bet on OpenAI 6:06 Nvidia's Strategic Investment and Deal Mechanics 9:17 Why Bigger Models Aren't Always Better 15:07 The Adoption Curve Problem 19:01 The Tokenomics of AI 23:59 Over-Parameterization and Model Learning 28:10 Building Environments for AI Training 32:16 AI in Everyday Life 34:46 The Future of Reasoning and Compute Scaling 44:34 The Spectrum of AI Optimism 46:29 Timeline to AGI 49:25 Talent Wars 58:37 Power Dynamics in the AI Ecosystem 1:18:42 AI for Material Science and Hard Tech 1:22:21 Building Infrastructure 1:29:55 US vs China: Who Really Needs AI to Win? 1:37:42 Favorite AI Bears 1:48:08 Speed Round: Company Impressions 1:55:11 The Death of Traditional SaaS Business Models 2:00:24 The Kindest Thing

Patrick OShaughnessy

548,858 次观看 • 11 个月前

Neil Movva (Neil Movva) started his career at Nvidia, working on GPUs and kernels, and has an unusually deep understanding of inference, from software to chips to power. We spend a lot of time on each of those layers, how they connect, and where the important tradeoffs are. What makes this conversation special is how detailed it is (like a 401-level class), yet Neil makes it remarkably clear and easy to follow. Today he runs Sail Research, a company building infrastructure for agents to make tokens as cheap as possible. We discuss: - Latency versus throughput - Why there are no bad chips, only bad pricing - The end of kernel engineering - Buying chips and power no one else wants - New chip architectures - Nvidia lore + his contrarian view of the company - Open source and the frontier labs I learned a ton. Enjoy! TIMESTAMPS 0:00 Intro 0:38 Building a “Token Factory” 4:21 The Future of Background Agents 13:09 Nvidia and the GPU Stack 23:27 Chips, Memory, and Transformers 36:14 The Future of AI Training Data 44:32 Chip Scarcity and Compute Arbitrage 52:44 Reinventing the AI Data Center 59:01 Power and the “Scavenger Strategy” 1:10:10 Open vs. Closed AI
1:23:35

Neil Movva (Neil Movva) started his career at Nvidia, working on GPUs and kernels, and has an unusually deep understanding of inference, from software to chips to power. We spend a lot of time on each of those layers, how they connect, and where the important tradeoffs are. What makes this conversation special is how detailed it is (like a 401-level class), yet Neil makes it remarkably clear and easy to follow. Today he runs Sail Research, a company building infrastructure for agents to make tokens as cheap as possible. We discuss: - Latency versus throughput - Why there are no bad chips, only bad pricing - The end of kernel engineering - Buying chips and power no one else wants - New chip architectures - Nvidia lore + his contrarian view of the company - Open source and the frontier labs I learned a ton. Enjoy! TIMESTAMPS 0:00 Intro 0:38 Building a “Token Factory” 4:21 The Future of Background Agents 13:09 Nvidia and the GPU Stack 23:27 Chips, Memory, and Transformers 36:14 The Future of AI Training Data 44:32 Chip Scarcity and Compute Arbitrage 52:44 Reinventing the AI Data Center 59:01 Power and the “Scavenger Strategy” 1:10:10 Open vs. Closed AI

Patrick OShaughnessy

4,537,356 次观看 • 10 天前

Join my conversation with Elon Musk on AGI timelines, energy, robots, and why abundance is the most likely outcome for humanity's future, alongside my Moonshot Mate NOTDAVID! (00:00) - Navigating the Future of AI and Robotics (04:54) - The Promise of Abundance and Optimism (10:02) - Energy: The Key to a Sustainable Future (15:00) - The Role of Education in a Changing World (41:07) - Health, Longevity, and the Future of Humanity (50:51) - AI's Impact on Labor and Employment (55:05) - Universal High Income: A New Economic Paradigm (57:58) - Navigating the Singularity and AI's Acceleration (01:02:30) - The Role of AI in Healthcare and Surgery (01:08:22) - Ethics and AI: Programming Values into Machines (01:14:18) - The Future of Space Exploration and AI's Role (01:33:30) - The Chip Shortage Crisis (01:42:46) - Simulation Theory and Consciousness (01:48:18) - The Search for Extraterrestrial Life (01:58:28) - The Future of Robotics and AI Integration
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Join my conversation with Elon Musk on AGI timelines, energy, robots, and why abundance is the most likely outcome for humanity's future, alongside my Moonshot Mate NOTDAVID! (00:00) - Navigating the Future of AI and Robotics (04:54) - The Promise of Abundance and Optimism (10:02) - Energy: The Key to a Sustainable Future (15:00) - The Role of Education in a Changing World (41:07) - Health, Longevity, and the Future of Humanity (50:51) - AI's Impact on Labor and Employment (55:05) - Universal High Income: A New Economic Paradigm (57:58) - Navigating the Singularity and AI's Acceleration (01:02:30) - The Role of AI in Healthcare and Surgery (01:08:22) - Ethics and AI: Programming Values into Machines (01:14:18) - The Future of Space Exploration and AI's Role (01:33:30) - The Chip Shortage Crisis (01:42:46) - Simulation Theory and Consciousness (01:48:18) - The Search for Extraterrestrial Life (01:58:28) - The Future of Robotics and AI Integration

Peter H. Diamandis, MD

6,235,651 次观看 • 8 个月前

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George
31:52

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George

a16z

92,161 次观看 • 10 个月前

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

1,154,740 次观看 • 1 年前

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

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

Raoul Pal

326,827 次观看 • 1 年前

I sat down with Jordi Visser to discuss the SpaceX IPO, orbital data centers, and the critical minerals powering the AI buildout. We also discuss the AI model wars, why Jordi thinks Sam Altman won't be running OpenAI within a year, and how the New York Knicks playoff run connects to the future of crypto and blockchain in a world of AI and deep fakes. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 1:00 - SpaceX IPO, Elon & orbital data centers 12:15 - Critical minerals & the AI supply chain 18:55 - American industrial sovereignty & critical chemicals 22:36 - AI model cost crisis & who wins the model war 37:10 - Knicks NBA Finals & the case for crypto in an AI world 47:48 - Jeff Bezos launches Prometheus 50:34 - AI use case of the week
54:47

I sat down with Jordi Visser to discuss the SpaceX IPO, orbital data centers, and the critical minerals powering the AI buildout. We also discuss the AI model wars, why Jordi thinks Sam Altman won't be running OpenAI within a year, and how the New York Knicks playoff run connects to the future of crypto and blockchain in a world of AI and deep fakes. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 1:00 - SpaceX IPO, Elon & orbital data centers 12:15 - Critical minerals & the AI supply chain 18:55 - American industrial sovereignty & critical chemicals 22:36 - AI model cost crisis & who wins the model war 37:10 - Knicks NBA Finals & the case for crypto in an AI world 47:48 - Jeff Bezos launches Prometheus 50:34 - AI use case of the week

Anthony Pompliano 🌪

133,301 次观看 • 2 个月前

Here's my conversation with Jensen Huang, CEO of NVIDIA, the most valuable & one of the most influential companies in the history of human civilization. It is the engine powering the AI revolution. This was a fascinating & inspiring conversation, in parts super-technical on engineering of every part of the AI stack, memory, power, supply chain (TSMC, ASML, etc), in parts about leadership & psychology, and in parts personal & philosophical about life, consciousness, mortality, and human nature. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 0:33 - Extreme co-design and rack-scale engineering 3:18 - How Jensen runs NVIDIA 22:40 - AI scaling laws 37:40 - Biggest blockers to AI scaling laws 39:23 - Supply chain 41:18 - Memory 47:24 - Power 52:43 - Elon and Colossus 56:11 - Jensen's approach to engineering and leadership 1:01:37 - China 1:09:50 - TSMC and Taiwan 1:15:04 - NVIDIA's moat 1:20:41 - AI data centers in space 1:24:30 - Will NVIDIA be worth $10 trillion? 1:34:39 - Leadership under pressure 1:48:25 - Video games 1:55:16 - AGI timeline 1:57:29 - Future of programming 2:11:01 - Consciousness 2:17:22 - Mortality
2:25:58

Here's my conversation with Jensen Huang, CEO of NVIDIA, the most valuable & one of the most influential companies in the history of human civilization. It is the engine powering the AI revolution. This was a fascinating & inspiring conversation, in parts super-technical on engineering of every part of the AI stack, memory, power, supply chain (TSMC, ASML, etc), in parts about leadership & psychology, and in parts personal & philosophical about life, consciousness, mortality, and human nature. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 0:33 - Extreme co-design and rack-scale engineering 3:18 - How Jensen runs NVIDIA 22:40 - AI scaling laws 37:40 - Biggest blockers to AI scaling laws 39:23 - Supply chain 41:18 - Memory 47:24 - Power 52:43 - Elon and Colossus 56:11 - Jensen's approach to engineering and leadership 1:01:37 - China 1:09:50 - TSMC and Taiwan 1:15:04 - NVIDIA's moat 1:20:41 - AI data centers in space 1:24:30 - Will NVIDIA be worth $10 trillion? 1:34:39 - Leadership under pressure 1:48:25 - Video games 1:55:16 - AGI timeline 1:57:29 - Future of programming 2:11:01 - Consciousness 2:17:22 - Mortality

Lex Fridman

2,536,210 次观看 • 5 个月前

Gavin Baker and a16z's David George on the state of the AI boom: The future doesn't have to be winner-take-all. Labs, open-source, applications, and the clouds can all capture value. Demand for intelligence is still dramatically underestimated. Today's power users number in the millions and will grow to hundreds of millions. Gavin and David argue a compute shortage is a more real risk than an AI bubble, and building through it is an opportunity to reindustrialize America. In this episode, they get into why compute investments pay back so fast, what the data center backlash gets wrong, the case for putting compute in orbit, why enterprises will run several models at once, and how Nvidia ended up at the center of the entire supply chain. 00:00 Intro 01:06 The bear case Gavin couldn't find 05:50 Why a lab would cut its own revenue 75% 08:05 What LPs get wrong about a crash 10:50 Microsoft slowed its capex and regrets it 14:33 The engineers spending 100x the median 17:35 Why 23-year-olds use AI better than Gavin 21:45 How much copper 500M AI users need 23:00 Stop promising to cure cancer 26:00 America's richest county is full of data centers 30:48 Who gets priced out of compute 33:05 The age of Elon and Jensen 34:25 Orbital data centers 44:40 Asteroid mining 48:12 Why Microsoft doesn't need a frontier model 54:02 Who becomes the abstraction layer 55:40 Everyone wanted a deity, Cursor wanted a product 1:00:25 Never take shots at Jensen 1:07:40 What happens when the chip doesn't work 1:12:10 What chip deals reveal about customer demand YouTube: Gavin Baker David George
1:14:25

Gavin Baker and a16z's David George on the state of the AI boom: The future doesn't have to be winner-take-all. Labs, open-source, applications, and the clouds can all capture value. Demand for intelligence is still dramatically underestimated. Today's power users number in the millions and will grow to hundreds of millions. Gavin and David argue a compute shortage is a more real risk than an AI bubble, and building through it is an opportunity to reindustrialize America. In this episode, they get into why compute investments pay back so fast, what the data center backlash gets wrong, the case for putting compute in orbit, why enterprises will run several models at once, and how Nvidia ended up at the center of the entire supply chain. 00:00 Intro 01:06 The bear case Gavin couldn't find 05:50 Why a lab would cut its own revenue 75% 08:05 What LPs get wrong about a crash 10:50 Microsoft slowed its capex and regrets it 14:33 The engineers spending 100x the median 17:35 Why 23-year-olds use AI better than Gavin 21:45 How much copper 500M AI users need 23:00 Stop promising to cure cancer 26:00 America's richest county is full of data centers 30:48 Who gets priced out of compute 33:05 The age of Elon and Jensen 34:25 Orbital data centers 44:40 Asteroid mining 48:12 Why Microsoft doesn't need a frontier model 54:02 Who becomes the abstraction layer 55:40 Everyone wanted a deity, Cursor wanted a product 1:00:25 Never take shots at Jensen 1:07:40 What happens when the chip doesn't work 1:12:10 What chip deals reveal about customer demand YouTube: Gavin Baker David George

a16z

1,933,297 次观看 • 4 天前

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
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

33,540 次观看 • 4 个月前

I loved talking to martin_casado on Uncapped. We talked about where venture capital is heading, his focus area of infrastructure, AI coding and open source, and more. I learned a ton from this one. Timestamps: (0:00) Intro (0:27) Importance of media in VC (3:50) Evolution of a16z (7:00) The case for specialization (10:32) Value of distribution (13:16) Why infrastructure is so valuable (19:49) The dynamics around conflicts (26:32) State of play in AI (30:48) The future of coding (34:58) Significance of open source (39:48) Marc Andreessen’s leadership (44:02) The only sin in VC (48:37) Scaling a lot of board seats
52:10

I loved talking to martin_casado on Uncapped. We talked about where venture capital is heading, his focus area of infrastructure, AI coding and open source, and more. I learned a ton from this one. Timestamps: (0:00) Intro (0:27) Importance of media in VC (3:50) Evolution of a16z (7:00) The case for specialization (10:32) Value of distribution (13:16) Why infrastructure is so valuable (19:49) The dynamics around conflicts (26:32) State of play in AI (30:48) The future of coding (34:58) Significance of open source (39:48) Marc Andreessen’s leadership (44:02) The only sin in VC (48:37) Scaling a lot of board seats

Jack Altman

124,413 次观看 • 1 年前

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed
1:22:57

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

Matt Turck

56,954 次观看 • 2 个月前

BG2. Ep 17. Double $NVDA! System Level Comp Moat, “Insane Demand”, Inference Explosion 1 B x, Memphis Supercluster, OpenAI, & more. Brad Gerstner Clark Tang Bill Gurley (00:00) Intro (1:50) The Evolution of AGI and Personal Assistants (06:03) NVIDIA's Competitive Moat (15:51 ) The Future of Inference and Training in AI (19:01) Building the AI Infrastructure (31:35) Inventing a New Market in an AI Future (38:40) The Impact of OpenAI (43:25) The Future of AI Models (46.44) and Memphis Supercluster (51:21) Distributed Computing and Inference Scaling (55:54) Inference Time Reasoning and Its Importance (01:00:46) AI's Role in Growing Business and Improving Productivity (01:08:00) Ensuring Safe AI Development (01:12:31) The Balance of Open Source and Closed Source AI
1:21:13

BG2. Ep 17. Double $NVDA! System Level Comp Moat, “Insane Demand”, Inference Explosion 1 B x, Memphis Supercluster, OpenAI, & more. Brad Gerstner Clark Tang Bill Gurley (00:00) Intro (1:50) The Evolution of AGI and Personal Assistants (06:03) NVIDIA's Competitive Moat (15:51 ) The Future of Inference and Training in AI (19:01) Building the AI Infrastructure (31:35) Inventing a New Market in an AI Future (38:40) The Impact of OpenAI (43:25) The Future of AI Models (46.44) and Memphis Supercluster (51:21) Distributed Computing and Inference Scaling (55:54) Inference Time Reasoning and Its Importance (01:00:46) AI's Role in Growing Business and Improving Productivity (01:08:00) Ensuring Safe AI Development (01:12:31) The Balance of Open Source and Closed Source AI

Bg2 Pod

487,379 次观看 • 1 年前

My second conversation with Sarah Guo (sarah guo), founder of Conviction. Sarah's been early to many of this generation's defining companies, and is constantly ranked at the top of the managers LPs most want to invest with. She knows the small group of 250 people pushing the AI frontier and we discuss what she sees from that vantage point: - What the people building AI actually believe right now - How close we are to robots in the home - The case against an AI monopoly - Why she's bullish on bio x AI - Building Conviction Dom Cooke wrote the definitive profile of Sarah and Conviction for Colossus: "Sarah's Wager". Link in comments. Enjoy! TIMESTAMPS 0:00 Intro 1:08 Investing Through the AI Boom 12:06 What AI Researchers Believe 15:44 Compute, Capital & Robotics 24:03 How Sarah Makes Investments 39:24 The Case for Open Source 49:01 America’s Compute Independence 51:32 AI’s New Investment Markets 59:36 Finding Truth & What’s Next
1:10:52

My second conversation with Sarah Guo (sarah guo), founder of Conviction. Sarah's been early to many of this generation's defining companies, and is constantly ranked at the top of the managers LPs most want to invest with. She knows the small group of 250 people pushing the AI frontier and we discuss what she sees from that vantage point: - What the people building AI actually believe right now - How close we are to robots in the home - The case against an AI monopoly - Why she's bullish on bio x AI - Building Conviction Dom Cooke wrote the definitive profile of Sarah and Conviction for Colossus: "Sarah's Wager". Link in comments. Enjoy! TIMESTAMPS 0:00 Intro 1:08 Investing Through the AI Boom 12:06 What AI Researchers Believe 15:44 Compute, Capital & Robotics 24:03 How Sarah Makes Investments 39:24 The Case for Open Source 49:01 America’s Compute Independence 51:32 AI’s New Investment Markets 59:36 Finding Truth & What’s Next

Patrick OShaughnessy

599,751 次观看 • 3 天前