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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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2,859,057 views • 8 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

1,676,900 views • 3 months ago

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

1,825,740 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

92,161 views • 10 months ago

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

1,919,731 views • 2 days 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

548,858 views • 11 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 • 2 months ago

I spoke with Nick Grossman about his "Rebel Alliance" thesis for AI. He believes the industry is too big for one or two companies to dominate. We also discuss USV's internal multi-agent platform, model routing economics, AI's growing role in venture capital and financial markets, data privacy risks, and what happens to jobs and society as agents get smarter. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:42 - The "Rebel Alliance" thesis: why one company won't dominate AI 7:15 - General-purpose vs. specialized models in USV's portfolio 8:40 - Compute costs & the rise of model routing 11:14 - Inside USV's internal multi-agent system 16:25 - AI's role in venture capital & autonomous investing 22:46 - How AI reshapes market signals & information edges 27:02 - Apps building models & the fight over your data 35:26 - Five-year outlook for the AI stack 37:53 - US vs. China: the "philosophy" of AI models 40:26 - Personalized AI & where the Rebel Alliance thesis plays 43:49 - The dark side: jobs, data centers & society 47:40 - AI as a personal superpower & neural implants
51:37

I spoke with Nick Grossman about his "Rebel Alliance" thesis for AI. He believes the industry is too big for one or two companies to dominate. We also discuss USV's internal multi-agent platform, model routing economics, AI's growing role in venture capital and financial markets, data privacy risks, and what happens to jobs and society as agents get smarter. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:42 - The "Rebel Alliance" thesis: why one company won't dominate AI 7:15 - General-purpose vs. specialized models in USV's portfolio 8:40 - Compute costs & the rise of model routing 11:14 - Inside USV's internal multi-agent system 16:25 - AI's role in venture capital & autonomous investing 22:46 - How AI reshapes market signals & information edges 27:02 - Apps building models & the fight over your data 35:26 - Five-year outlook for the AI stack 37:53 - US vs. China: the "philosophy" of AI models 40:26 - Personalized AI & where the Rebel Alliance thesis plays 43:49 - The dark side: jobs, data centers & society 47:40 - AI as a personal superpower & neural implants

Anthony Pompliano 🌪

63,209 views • 1 month 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

403,731 views • 3 months 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

28,872 views • 4 months ago

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!
1:13:04

My conversation with Tarun Chitra As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi. We spend time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate. At the center of the conversation is the belief that AI’s unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain. We discuss: - The current state of crypto as TradFi+ and the decline of speculative narratives - Why AI is killing Bitcoin mining economics and weakening ETH value accrual - The architectural parallel between AI stacks and DeFi (Harnesses = Wallets, Routers = DEX aggregators, Models = Protocols, Inference Providers = LPs) - Why open source models are unbundling faster than traditional software - Agents as the next interface layer and the potential unbundling of ETFs -Cryptography, verifiable compute, and turning GPUs into digital assets - Onchain compute trading as the real crypto × AI opportunity - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of the Crypto Market 2:00 – Speculative Narratives Fade, Trading & Payments Remain 7:00 – AI’s Impact on Bitcoin Economics & Data Center Opportunity Cost 9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability 15:00 – Trading Design Space & On-Chain Volume Upside 25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers 35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference) 48:00 – Agents, Preference Expression & Unbundling Traditional Products 1:00:00 – Real-Time Harness Generation & Active Learning 1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets 1:10:00 – Closing Thoughts: Where Value Accrues Next Enjoy!

Logan Jastremski

132,018 views • 22 days ago

My conversation with Eric Vishria of Benchmark. Eric has spent a decade investing across software and hardware, backing companies like Fireworks, Sierra, Sunday Robotics, and Cerebras. This one is about what history teaches us about the current moment, and a dispatch from inside the AI buildout through his companies. We discuss: - What AWS tells us about how big AI can get - How the goalposts have moved for every software company - Lessons from a decade with Cerebras - China and the energy bottleneck - Benchmark's return to growth investing - Robotics Enjoy! TIMESTAMPS 0:00 Intro 3:36 What Cloud Teaches Us About AI 12:52 Sierra, Sandcastles, and AI Products 17:35 The New SaaS Competitive Frontier 28:28 AI Demand and the Energy Bottleneck 31:28 The Cerebras Story and AI Chips 45:10 The Future of Robotics 52:53 Eric’s Venture Investing Philosophy 1:07:30 Going Public, AI Value, and Jobs
1:17:52

My conversation with Eric Vishria of Benchmark. Eric has spent a decade investing across software and hardware, backing companies like Fireworks, Sierra, Sunday Robotics, and Cerebras. This one is about what history teaches us about the current moment, and a dispatch from inside the AI buildout through his companies. We discuss: - What AWS tells us about how big AI can get - How the goalposts have moved for every software company - Lessons from a decade with Cerebras - China and the energy bottleneck - Benchmark's return to growth investing - Robotics Enjoy! TIMESTAMPS 0:00 Intro 3:36 What Cloud Teaches Us About AI 12:52 Sierra, Sandcastles, and AI Products 17:35 The New SaaS Competitive Frontier 28:28 AI Demand and the Energy Bottleneck 31:28 The Cerebras Story and AI Chips 45:10 The Future of Robotics 52:53 Eric’s Venture Investing Philosophy 1:07:30 Going Public, AI Value, and Jobs

Patrick OShaughnessy

672,191 views • 23 days ago

Philip Johnston (Philip Johnston) is the co-founder and CEO of Starcloud, the company building data centers in space. In November 2025, Starcloud launched an Nvidia H100 GPU into orbit and trained the first large language model in space. They've since raised $200 million, hit a billion-dollar valuation just 17 months after YC demo day and filed with the FCC to deploy 88,000 more satellites. In this episode of Lightcone Podcast, Philip walks us through their wild origin story, the engineering challenges behind the Starcloud-1, why they booked a SpaceX launch before they even knew what they were building and how data centers in space make sense both economically and politically. 00:39 — Why Build Data Centers in Space? 01:40 — The Insight That Started Starcloud 04:43 — Launching Starcloud-1 09:45 — The Engineering Behind Data Centers in Orbit 13:49 — Why 100 VCs Said No 16:12 — Book the Launch Before You Build the Product 18:32 — The Roadmap to Commercial Space Compute 21:10 — Building NVIDIA GPUs for Space 23:41 — Raising $170M for a Hard Tech Startup 26:37 — Hiring the World's Best Space Engineers 31:25 — Why AI Compute Is Moving to Space 34:49 — Advice for Hard Tech Founders
36:13

Philip Johnston (Philip Johnston) is the co-founder and CEO of Starcloud, the company building data centers in space. In November 2025, Starcloud launched an Nvidia H100 GPU into orbit and trained the first large language model in space. They've since raised $200 million, hit a billion-dollar valuation just 17 months after YC demo day and filed with the FCC to deploy 88,000 more satellites. In this episode of Lightcone Podcast, Philip walks us through their wild origin story, the engineering challenges behind the Starcloud-1, why they booked a SpaceX launch before they even knew what they were building and how data centers in space make sense both economically and politically. 00:39 — Why Build Data Centers in Space? 01:40 — The Insight That Started Starcloud 04:43 — Launching Starcloud-1 09:45 — The Engineering Behind Data Centers in Orbit 13:49 — Why 100 VCs Said No 16:12 — Book the Launch Before You Build the Product 18:32 — The Roadmap to Commercial Space Compute 21:10 — Building NVIDIA GPUs for Space 23:41 — Raising $170M for a Hard Tech Startup 26:37 — Hiring the World's Best Space Engineers 31:25 — Why AI Compute Is Moving to Space 34:49 — Advice for Hard Tech Founders

Y Combinator

229,182 views • 29 days 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

344,926 views • 2 years 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

2,535,643 views • 5 months 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

194,047 views • 1 year 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

101,314 views • 3 months ago

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter
1:32:00

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter

Tommy

24,342 views • 1 month 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

57,630 views • 3 months 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