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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...

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Patrick OShaughnessy

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2,856,425 views • 7 months ago •via X (Twitter)

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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 Terafab and the new chip companies challenging Nvidia - Usage-based pricing - The disaggregation of GPUs - DRAM, frontier tokens, and open source Enjoy! Timestamps: 0:00 Intro 7:55 Anthropic and OpenAI Valuations 12:58 Watts, Wafers, and Infrastructure 14:39 Orbital Compute and Data Centers in Space 22:49 Avoiding the AI Bubble 28:26 Terafab and the Future of US Manufacturing 32:16 Returns to the Frontier 37:23 Continual Learning 42:03 New Chip Companies 48:52 Extending GPU Lifespans and Private Credit 51:22 The Application Layer 57:32 The Token Path and Open-Source Dynamics 1:01:37 Cybersecurity 1:05:46 Diversity Breakdown 1:11:59 Assessing the Big Tech Players in AI 1:19:02 Geopolitics, Personal Safety, and the AI Horizon
1:22:10

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 Terafab and the new chip companies challenging Nvidia - Usage-based pricing - The disaggregation of GPUs - DRAM, frontier tokens, and open source Enjoy! Timestamps: 0:00 Intro 7:55 Anthropic and OpenAI Valuations 12:58 Watts, Wafers, and Infrastructure 14:39 Orbital Compute and Data Centers in Space 22:49 Avoiding the AI Bubble 28:26 Terafab and the Future of US Manufacturing 32:16 Returns to the Frontier 37:23 Continual Learning 42:03 New Chip Companies 48:52 Extending GPU Lifespans and Private Credit 51:22 The Application Layer 57:32 The Token Path and Open-Source Dynamics 1:01:37 Cybersecurity 1:05:46 Diversity Breakdown 1:11:59 Assessing the Big Tech Players in AI 1:19:02 Geopolitics, Personal Safety, and the AI Horizon

Patrick OShaughnessy

1,657,625 views • 1 month ago

“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

92,096 views • 8 months ago

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

41,368 views • 5 months ago

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
2:02:21

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

548,353 views • 9 months ago

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 views • 27 days ago

ALL-IN POD IS LIVE! 🚨 Massive show Gavin Baker (Gavin Baker) subs in for Sacks to talk: -- Andrej Karpathy Joining Anthropic: Impact on the AI Race? -- SpaceX S-1 Breakdown: The $2T Case, Elon Web Services, Datacenters in Space -- Nvidia’s Big Beat and Shock Selloff -- Why America Has Turned on AI -- Trump Pulls AI Order -- Market Update: Inflation, Bond Crisis? -- Did the US-China Summit Flop? (0:00) Gavin Baker joins the show! (0:30) Andrej Karpathy joins Anthropic; hypergrowth and profitability (12:42) Why Americans have turned on AI, anti-human perception (27:22) Trump pulls AI EO, US-China AI relationship, dystopian AI layoffs (45:19) SpaceX S-1 tear down! Three major businesses and the case for $2T (1:11:22) Nvidia smashes earnings but stock falls, why people are shorting chips (1:22:25) Market update: Flashing red signals, oil, inflation, yields up (1:32:45) China trip flops, or was progress made behind the scenes?
1:41:59

ALL-IN POD IS LIVE! 🚨 Massive show Gavin Baker (Gavin Baker) subs in for Sacks to talk: -- Andrej Karpathy Joining Anthropic: Impact on the AI Race? -- SpaceX S-1 Breakdown: The $2T Case, Elon Web Services, Datacenters in Space -- Nvidia’s Big Beat and Shock Selloff -- Why America Has Turned on AI -- Trump Pulls AI Order -- Market Update: Inflation, Bond Crisis? -- Did the US-China Summit Flop? (0:00) Gavin Baker joins the show! (0:30) Andrej Karpathy joins Anthropic; hypergrowth and profitability (12:42) Why Americans have turned on AI, anti-human perception (27:22) Trump pulls AI EO, US-China AI relationship, dystopian AI layoffs (45:19) SpaceX S-1 tear down! Three major businesses and the case for $2T (1:11:22) Nvidia smashes earnings but stock falls, why people are shorting chips (1:22:25) Market update: Flashing red signals, oil, inflation, yields up (1:32:45) China trip flops, or was progress made behind the scenes?

The All-In Podcast

400,609 views • 1 month ago

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

28,786 views • 2 months ago

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

2,525,729 views • 3 months ago

Why AI Progress Suddenly Feels Real - my conversation with Yann Dubois, who co-leads the Post-Training Frontiers team at OpenAI 00:00 - Intro 01:30 - Why recent AI progress feels like a step function 04:13 - Model reliability & the emotional rollercoaster of shipping GPT-5.5 07:33 - How OpenAI structures vertical and horizontal teams 09:49 - Improving model efficiency and test-time compute 12:32 - Yann's journey from Switzerland to OpenAI 15:37 - Reasoning in 2026: Real-world utility vs verifiable rewards 18:34 - GPT-5.5 Thinking vs Pro: Scaling test-time compute 20:09 - How reasoning models become more efficient 23:23 - Pre-training scaling and overcoming the data wall 27:03 - Multimodal data, synthetic data, and embodied AI 31:05 - Demystifying mid-training and post-training 37:21 - Does RL create new capabilities in AI? 38:53 - The challenges and frontier of scaling RL 43:09 - Is building AI models a craft or a strict science 48:21 - How AI models generalize across different domains 54:18 - How reinforcement learning cures AI hallucinations 56:04 - Negative generalization and conflicting instructions 58:05 - Can RL scale to law, medicine, and the broader economy? 1:00:19 - The evaluation bottleneck and Model as a Judge 1:04:21 - Continuous AI progress & continual learning 1:08:49 - Will foundation models eat the agent harness 1:11:23 - Why startups should focus on the last mile of AI
1:13:56

Why AI Progress Suddenly Feels Real - my conversation with Yann Dubois, who co-leads the Post-Training Frontiers team at OpenAI 00:00 - Intro 01:30 - Why recent AI progress feels like a step function 04:13 - Model reliability & the emotional rollercoaster of shipping GPT-5.5 07:33 - How OpenAI structures vertical and horizontal teams 09:49 - Improving model efficiency and test-time compute 12:32 - Yann's journey from Switzerland to OpenAI 15:37 - Reasoning in 2026: Real-world utility vs verifiable rewards 18:34 - GPT-5.5 Thinking vs Pro: Scaling test-time compute 20:09 - How reasoning models become more efficient 23:23 - Pre-training scaling and overcoming the data wall 27:03 - Multimodal data, synthetic data, and embodied AI 31:05 - Demystifying mid-training and post-training 37:21 - Does RL create new capabilities in AI? 38:53 - The challenges and frontier of scaling RL 43:09 - Is building AI models a craft or a strict science 48:21 - How AI models generalize across different domains 54:18 - How reinforcement learning cures AI hallucinations 56:04 - Negative generalization and conflicting instructions 58:05 - Can RL scale to law, medicine, and the broader economy? 1:00:19 - The evaluation bottleneck and Model as a Judge 1:04:21 - Continuous AI progress & continual learning 1:08:49 - Will foundation models eat the agent harness 1:11:23 - Why startups should focus on the last mile of AI

Matt Turck

100,493 views • 1 month ago

I sat down with Keith Rabois (Keith Rabois), General Partner Founders Fund and CEO of OpenStore. We spoke about spotting talent, the intricacies of founding vs investing, companies as cults, why you shouldn’t stretch, Keith’s requests for startups, and much more. 0:00 - Intro 2:35 - Bomb-Building and the PayPal Mafia 5:10 - Spotting Talent 11:32 - Where Keith is 1000:1 16:14 - PayPal, Regulation, and Law 22:00 - Regulatory Arbitrage 25:03 - AI 27:46 - Keith’s 5 Bosses 31:04 - How to Operate 34:16 - OpenStore 39:33 - Founding vs Investing 42:48 - Requests for Startups 47:39 - Early-Stage Investing 53:46 - Companies as Cults 56:42 - The Future of Venture 1:00:56 - Not Stretching, Engineering Serendipity, and How to Ask Better Questions 1:06:40 - On Keith 1:08:45 - Time Allocation, Self-Grading, Values, Reading and Legacy 1:16:11 - What Should More People be Thinking About?
1:16:57

I sat down with Keith Rabois (Keith Rabois), General Partner Founders Fund and CEO of OpenStore. We spoke about spotting talent, the intricacies of founding vs investing, companies as cults, why you shouldn’t stretch, Keith’s requests for startups, and much more. 0:00 - Intro 2:35 - Bomb-Building and the PayPal Mafia 5:10 - Spotting Talent 11:32 - Where Keith is 1000:1 16:14 - PayPal, Regulation, and Law 22:00 - Regulatory Arbitrage 25:03 - AI 27:46 - Keith’s 5 Bosses 31:04 - How to Operate 34:16 - OpenStore 39:33 - Founding vs Investing 42:48 - Requests for Startups 47:39 - Early-Stage Investing 53:46 - Companies as Cults 56:42 - The Future of Venture 1:00:56 - Not Stretching, Engineering Serendipity, and How to Ask Better Questions 1:06:40 - On Keith 1:08:45 - Time Allocation, Self-Grading, Values, Reading and Legacy 1:16:11 - What Should More People be Thinking About?

Alex LaBossiere

344,898 views • 2 years ago

Cliff Sosin has run one of the most interesting portfolios in public markets—nearly $2B concentrated in just a few companies, which he always knows better than anyone. Over many years, I’ve enjoyed conversations with him on a million topics, and finally convinced him to talk about investing with me for everyone to hear. We start talking about investing overall, and then spend a large part of the conversation hearing his side of the Carvana investing story—one for the ages. Enjoy Timestamps 0:32 Early Career & Discovering Investing 1:49 Starting the Firm 7:23 Defining a Good Business 12:31 Contained vs. Uncontained Businesses 15:30 Mental Models & Market Insights 30:13 The Role of ESG in Investing 34:26 The Carvana Investment Story 41:01 The Complexity of Car Transactions 46:43 Economies of Scale and Trust 49:40 Management Insights 59:07 Operational Issues & Market Challenges 1:19:17 The Role of Word of Mouth in Carvana's Growth 1:20:28 Identifying Early Adopters 1:27:19 The Apollo Deal and Debt Restructuring 1:28:23 Personal Reflections on Investment Decision 1:34:21 The Psychological Toll of Investment 1:45:16 Future Investment Strategies and AI 1:54:51 The Kindest Thing Anyone Has Ever Done For Cliff
1:56:58

Cliff Sosin has run one of the most interesting portfolios in public markets—nearly $2B concentrated in just a few companies, which he always knows better than anyone. Over many years, I’ve enjoyed conversations with him on a million topics, and finally convinced him to talk about investing with me for everyone to hear. We start talking about investing overall, and then spend a large part of the conversation hearing his side of the Carvana investing story—one for the ages. Enjoy Timestamps 0:32 Early Career & Discovering Investing 1:49 Starting the Firm 7:23 Defining a Good Business 12:31 Contained vs. Uncontained Businesses 15:30 Mental Models & Market Insights 30:13 The Role of ESG in Investing 34:26 The Carvana Investment Story 41:01 The Complexity of Car Transactions 46:43 Economies of Scale and Trust 49:40 Management Insights 59:07 Operational Issues & Market Challenges 1:19:17 The Role of Word of Mouth in Carvana's Growth 1:20:28 Identifying Early Adopters 1:27:19 The Apollo Deal and Debt Restructuring 1:28:23 Personal Reflections on Investment Decision 1:34:21 The Psychological Toll of Investment 1:45:16 Future Investment Strategies and AI 1:54:51 The Kindest Thing Anyone Has Ever Done For Cliff

Patrick OShaughnessy

193,789 views • 1 year ago

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 views • 1 year ago

BG2. All things AI w Sam Altman & Satya Nadella. A Halloween Special. 🎃🔥Bg2 Pod Brad Gerstner -- (00:00) Intro (02:28) Microsoft’s Investment in OpenAI (03:19) The Nonprofit Structure and Its Impact (05:46) Health, AI Security, and Resilience (07:50) Models, Exclusivity, and Distribution (08:58) Revenue Sharing and AGI Milestones (11:38) OpenAI’s Growth and Compute Commitments (15:21) Compute Constraints and Scaling (21:27) The Future of AI Devices and Consumer Use (24:31) Regulation and the Patchwork Problem (28:01) Looking Ahead to 2026 and Beyond (37:10) Microsoft’s Strategic Value from OpenAI (57:15) The Economics of AI and SaaS (1:04:28) Productivity, Jobs, and the Age of AI (1:10:43) Reindustrialization of America
1:14:20

BG2. All things AI w Sam Altman & Satya Nadella. A Halloween Special. 🎃🔥Bg2 Pod Brad Gerstner -- (00:00) Intro (02:28) Microsoft’s Investment in OpenAI (03:19) The Nonprofit Structure and Its Impact (05:46) Health, AI Security, and Resilience (07:50) Models, Exclusivity, and Distribution (08:58) Revenue Sharing and AGI Milestones (11:38) OpenAI’s Growth and Compute Commitments (15:21) Compute Constraints and Scaling (21:27) The Future of AI Devices and Consumer Use (24:31) Regulation and the Patchwork Problem (28:01) Looking Ahead to 2026 and Beyond (37:10) Microsoft’s Strategic Value from OpenAI (57:15) The Economics of AI and SaaS (1:04:28) Productivity, Jobs, and the Age of AI (1:10:43) Reindustrialization of America

Bg2 Pod

556,925 views • 8 months ago

My guests on Uncapped this week are Kevin Hartz and Bennett Siegel, co-founders of the early stage VC firm A*. They've backed companies like Notion, Mercor, Ramp, Decagon, Similie, and many more. They also announced a new $450m fund today. We discussed the state of venture capital firms in the current AI cycle, what it means for seed specialists, trends with great founders, and what they're seeing in AI. Timestamps: (0:00) Intro (0:25) The A* Capital story (1:16) Why big funds went into seed (7:50) The mother of all bubbles (10:46) Why founders are getting younger (13:00) Mapping talent, not markets (16:31) The rise of AI researcher founders (19:16) Why seed investing is so hard (22:54) Concentration and venture returns (27:34) The AI rollup craze (31:15) AI vs traditional software (33:15) Robotics and the future of AI (35:39) What’s next for A*
36:59

My guests on Uncapped this week are Kevin Hartz and Bennett Siegel, co-founders of the early stage VC firm A*. They've backed companies like Notion, Mercor, Ramp, Decagon, Similie, and many more. They also announced a new $450m fund today. We discussed the state of venture capital firms in the current AI cycle, what it means for seed specialists, trends with great founders, and what they're seeing in AI. Timestamps: (0:00) Intro (0:25) The A* Capital story (1:16) Why big funds went into seed (7:50) The mother of all bubbles (10:46) Why founders are getting younger (13:00) Mapping talent, not markets (16:31) The rise of AI researcher founders (19:16) Why seed investing is so hard (22:54) Concentration and venture returns (27:34) The AI rollup craze (31:15) AI vs traditional software (33:15) Robotics and the future of AI (35:39) What’s next for A*

Jack Altman

57,229 views • 1 month ago

I went to Miami to chat with dax, co-founder of OpenCode. We talked about the future of software engineering, coding agents, and why open source matters more now than ever. Timestamps: 0:00 Intro 5:30 Miami vs San Francisco tech scene 15:05 OpenCode origin story, scaling while open-source 25:03 OpenCode vs. Anthropic: owning models, open-source AI 33:36 AI hardware shortages, predicting the future 42:15 The bet of open-weight models, China vs. US 48:34 Why inference is hard, economics of intelligence 55:36 Will developers be automated? Software engineering as a craft 1:11:02 Advice to founders, building in public, marketing I had so much fun making this with Lan. Enjoy!
1:29:53

I went to Miami to chat with dax, co-founder of OpenCode. We talked about the future of software engineering, coding agents, and why open source matters more now than ever. Timestamps: 0:00 Intro 5:30 Miami vs San Francisco tech scene 15:05 OpenCode origin story, scaling while open-source 25:03 OpenCode vs. Anthropic: owning models, open-source AI 33:36 AI hardware shortages, predicting the future 42:15 The bet of open-weight models, China vs. US 48:34 Why inference is hard, economics of intelligence 55:36 Will developers be automated? Software engineering as a craft 1:11:02 Advice to founders, building in public, marketing I had so much fun making this with Lan. Enjoy!

Madison Kanna

250,679 views • 4 days ago

Gavin explains that the bear case for AI capex spend is on-device inference: "In three years, on a bigger phone, you'll be able to run a pruned-down version of Gemini 5, Grok 4, or ChatGPT. And that's free. This is clearly Apple's strategy - we're going to make it privacy-safe and run on the phone. Other than scaling laws breaking, edge AI is by far the most plausible and scariest bear case."
1:20

Gavin explains that the bear case for AI capex spend is on-device inference: "In three years, on a bigger phone, you'll be able to run a pruned-down version of Gemini 5, Grok 4, or ChatGPT. And that's free. This is clearly Apple's strategy - we're going to make it privacy-safe and run on the phone. Other than scaling laws breaking, edge AI is by far the most plausible and scariest bear case."

Patrick OShaughnessy

516,795 views • 7 months ago

Every conversation I have with Dylan Patel, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of that equation. We discuss: - The infinite demand for the newest models - SemiAnalysis going from $10K on AI spend to $7M - Mythos and Anthropic's compute problem - Why TSMC spending $100B on CapEx could cause a shortage - Robotics as next demand wave - Why memory prices will double again This is my second conversation with Dylan and find myself needing to speak with him more and more often to make sense of it all. Enjoy! Timestamps: 0:00 Intro 1:00 Surging AI Spend 10:27 Token Demand 16:21 When Ideas Are Cheap and Execution is Easy 20:46 Model Hoarding 22:34 Robotics 27:03 The Compute Bottleneck 30:26 The AI Permanent Underclass 31:39 Supply Chain Reality 37:47 CPUs 42:54 Predictions: Public Backlash
45:33

Every conversation I have with Dylan Patel, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of that equation. We discuss: - The infinite demand for the newest models - SemiAnalysis going from $10K on AI spend to $7M - Mythos and Anthropic's compute problem - Why TSMC spending $100B on CapEx could cause a shortage - Robotics as next demand wave - Why memory prices will double again This is my second conversation with Dylan and find myself needing to speak with him more and more often to make sense of it all. Enjoy! Timestamps: 0:00 Intro 1:00 Surging AI Spend 10:27 Token Demand 16:21 When Ideas Are Cheap and Execution is Easy 20:46 Model Hoarding 22:34 Robotics 27:03 The Compute Bottleneck 30:26 The AI Permanent Underclass 31:39 Supply Chain Reality 37:47 CPUs 42:54 Predictions: Public Backlash

Patrick OShaughnessy

892,921 views • 2 months ago

Here's my conversation with Demis Hassabis, CEO of Google DeepMind, all about the future of AI & AGI, simulating biology & physics, video games, programming, video generation, world models, Gemini 3, scaling laws, compute, P vs NP, complexity, energy (solar & fusion), and much more. This was a fun & fascinating super-technical conversation. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:21 - Introduction 2:06 - Learnable patterns in nature 5:48 - Computation and P vs NP 14:26 - Veo 3 and understanding reality 18:50 - Video games 30:52 - AlphaEvolve 36:53 - AI research 41:17 - Simulating a biological organism 46:00 - Origin of life 52:15 - Path to AGI 1:03:01 - Scaling laws 1:06:17 - Compute 1:09:04 - Future of energy 1:13:00 - Human nature 1:17:54 - Google and the race to AGI 1:35:53 - Competition and AI talent 1:42:27 - Future of programming 1:48:53 - John von Neumann 1:58:07 - p(doom) 2:02:50 - Humanity 2:05:56 - Consciousness and quantum computation 2:12:06 - David Foster Wallace 2:19:20 - Education and research
2:28:14

Here's my conversation with Demis Hassabis, CEO of Google DeepMind, all about the future of AI & AGI, simulating biology & physics, video games, programming, video generation, world models, Gemini 3, scaling laws, compute, P vs NP, complexity, energy (solar & fusion), and much more. This was a fun & fascinating super-technical conversation. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:21 - Introduction 2:06 - Learnable patterns in nature 5:48 - Computation and P vs NP 14:26 - Veo 3 and understanding reality 18:50 - Video games 30:52 - AlphaEvolve 36:53 - AI research 41:17 - Simulating a biological organism 46:00 - Origin of life 52:15 - Path to AGI 1:03:01 - Scaling laws 1:06:17 - Compute 1:09:04 - Future of energy 1:13:00 - Human nature 1:17:54 - Google and the race to AGI 1:35:53 - Competition and AI talent 1:42:27 - Future of programming 1:48:53 - John von Neumann 1:58:07 - p(doom) 2:02:50 - Humanity 2:05:56 - Consciousness and quantum computation 2:12:06 - David Foster Wallace 2:19:20 - Education and research

Lex Fridman

1,454,510 views • 11 months ago

Three years ago, two Harvard dropouts set out to build a better AI chip than the largest companies in the world. Almost everyone I called at the time said it was impossible. Today, Etched (Etched) comes out of stealth with $800M total raised, $1B in signed customer contracts, and a working next-gen AI chip. This was my excuse to ask the two founders, Gavin Uberti and Robert Wachen, every question I have about compute and inference. We discuss: - Why they built an entire rack and not just a chip - The two technical bets behind their architecture no one else has tried - How two founders in their twenties recruited industry legends - The night they nearly ran out of money - Why whoever produces the most tokens wins If you care about the future of compute, Gavin and Rob are two people to know. I think you will find the story of what they have built hard to forget. Enjoy! TIMESTAMPS 0:00 Intro 1:00 Why Nobody Believed Etched Would Work 14:06 Why Inference Is the Bottleneck 22:27 Gavin and Rob’s Origin Stories 33:24 Taking Huge Risks to Move Faster 49:43 Kernels, Compilers, and the AI Stack 1:02:08 Raising $100M to Survive 1:16:00 The Future of Models, Agents, and Intelligence
1:32:31

Three years ago, two Harvard dropouts set out to build a better AI chip than the largest companies in the world. Almost everyone I called at the time said it was impossible. Today, Etched (Etched) comes out of stealth with $800M total raised, $1B in signed customer contracts, and a working next-gen AI chip. This was my excuse to ask the two founders, Gavin Uberti and Robert Wachen, every question I have about compute and inference. We discuss: - Why they built an entire rack and not just a chip - The two technical bets behind their architecture no one else has tried - How two founders in their twenties recruited industry legends - The night they nearly ran out of money - Why whoever produces the most tokens wins If you care about the future of compute, Gavin and Rob are two people to know. I think you will find the story of what they have built hard to forget. Enjoy! TIMESTAMPS 0:00 Intro 1:00 Why Nobody Believed Etched Would Work 14:06 Why Inference Is the Bottleneck 22:27 Gavin and Rob’s Origin Stories 33:24 Taking Huge Risks to Move Faster 49:43 Kernels, Compilers, and the AI Stack 1:02:08 Raising $100M to Survive 1:16:00 The Future of Models, Agents, and Intelligence

Patrick OShaughnessy

1,314,149 views • 10 days ago