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BREAKING: Inside the Multi-Billion Dollar Digital Economy Powering Roblox Co-Founder & CEO David Baszucki 2025 Stats: • $1.5B paid to creators • Top 1,000 creators: $1.3M avg • $6.8B bookings (+55% YoY) • $4.9B revenue (+36% YoY) • ~150M daily users • 35B hours engaged (Q4) • 40+ data...

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Molly O’Shea

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613,034 görüntüleme • 5 ay önce •via X (Twitter)

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Roblox is scaling 3D world creation for ~100M daily active users. In this full episode, I sit down with Roblox’s VP of AI, Anupam Singh to break down: – Cube AI (their new generative model) – LLMs + 4D world-building – Vibe coding & in-experience creation Timestamps: 00:00 Roblox: The YouTube of 3D 01:53 Meet Anupam Singh, VP of AI at Roblox 03:09 The Roblox Vision: 3D Creation & Consumption At Scale 06:48 The Unseen AI Foundation of Roblox: Safety & Moderation 08:58 Cube AI: One Model To Rule Them All? 13:06 Using Cube with Large Language Models 17:54 The Road to 4D: Making Interactive Worlds 21:52 Who Orchestrates the AI? Creators vs Agentic AI 25:29 Vibe Coding At Roblox Scale 30:03 In-Experience 3D Creation 33:00 AI’s Impact on the Creator Economy 35:57 Roblox’s AI Recommendation Engine 39:13 Roblox Cube’s Context Window & Scaling Scene Generation 41:36 Future of UGC and AAA 3D Content 49:37 Advice for Creators & Developers 53:24 Key Takeaways & Conclusion
55:19

Roblox is scaling 3D world creation for ~100M daily active users. In this full episode, I sit down with Roblox’s VP of AI, Anupam Singh to break down: – Cube AI (their new generative model) – LLMs + 4D world-building – Vibe coding & in-experience creation Timestamps: 00:00 Roblox: The YouTube of 3D 01:53 Meet Anupam Singh, VP of AI at Roblox 03:09 The Roblox Vision: 3D Creation & Consumption At Scale 06:48 The Unseen AI Foundation of Roblox: Safety & Moderation 08:58 Cube AI: One Model To Rule Them All? 13:06 Using Cube with Large Language Models 17:54 The Road to 4D: Making Interactive Worlds 21:52 Who Orchestrates the AI? Creators vs Agentic AI 25:29 Vibe Coding At Roblox Scale 30:03 In-Experience 3D Creation 33:00 AI’s Impact on the Creator Economy 35:57 Roblox’s AI Recommendation Engine 39:13 Roblox Cube’s Context Window & Scaling Scene Generation 41:36 Future of UGC and AAA 3D Content 49:37 Advice for Creators & Developers 53:24 Key Takeaways & Conclusion

Bilawal Sidhu

178,735 görüntüleme • 1 yıl önce

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents
40:27

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents

Y Combinator

236,530 görüntüleme • 11 ay önce

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 görüntüleme • 1 yıl önce

BREAKING: AI has eaten the Internet. Data labeling is so over. & $30 trillion of human work is on the verge of automation. Inside The $2.2B AI Research Accelerator, Turing Founder & CEO, Jonathan Siddharth (), joins Sourcery to break down the severe power shift in AI training: from commodity data labeling → expert research Positioning Turing apart from AI data providers like Scale AI, Mercor, & Surge. (00:00) AI Ate The Internet (00:49) Training Superintelligence: the race to AGI (02:31) Viral tweet (03:24) What Turing actually does (04:43) The internet data is “used up” — where will new data come from? (05:34) Four pillars of superintelligence: multimodality, reasoning, tool use, coding (06:07) Automating $30T of global knowledge work (09:18) The $1B revenue opportunity (10:59) Why Turing is a research-first accelerator, not a data labeler (13:45) Jonathan’s Stanford AI Lab roots & founding DNA (17:57) How models are built: pre-training vs. post-training (20:14) RLHF, reinforcement learning, & “breaking the models” (25:19) GPT-5 and the myth of rapid takeoff (30:46) Safety debates and human-in-the-loop systems (34:53) Closing Enterprise Gap: finance, insurance, & pharma (39:23) Why proprietary enterprise data is the next moat in AI
49:29

BREAKING: AI has eaten the Internet. Data labeling is so over. & $30 trillion of human work is on the verge of automation. Inside The $2.2B AI Research Accelerator, Turing Founder & CEO, Jonathan Siddharth (), joins Sourcery to break down the severe power shift in AI training: from commodity data labeling → expert research Positioning Turing apart from AI data providers like Scale AI, Mercor, & Surge. (00:00) AI Ate The Internet (00:49) Training Superintelligence: the race to AGI (02:31) Viral tweet (03:24) What Turing actually does (04:43) The internet data is “used up” — where will new data come from? (05:34) Four pillars of superintelligence: multimodality, reasoning, tool use, coding (06:07) Automating $30T of global knowledge work (09:18) The $1B revenue opportunity (10:59) Why Turing is a research-first accelerator, not a data labeler (13:45) Jonathan’s Stanford AI Lab roots & founding DNA (17:57) How models are built: pre-training vs. post-training (20:14) RLHF, reinforcement learning, & “breaking the models” (25:19) GPT-5 and the myth of rapid takeoff (30:46) Safety debates and human-in-the-loop systems (34:53) Closing Enterprise Gap: finance, insurance, & pharma (39:23) Why proprietary enterprise data is the next moat in AI

Molly O’Shea

70,007 görüntüleme • 10 ay önce

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:
1:11:41

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

Shane Parrish

450,952 görüntüleme • 4 ay önce

From a Thai prison cell to a fintech empire processing $1.6B in international payments across 40+ banks and 250M+ users. Jonathan Low (Jonathan Low). Forbes 40 Under 40. Author of "Cell to CEO." We covered prison, banking for AI agents, RWA projects, the future of crypto in banking, vibe coding for trading, and the businesses that win the next 5 years. ⏱ Timestamps: 00:00:00 — Teaser 00:00:46 — Who is Jonathan Low 00:01:35 — What Jonathan's life was like before prison 00:02:13 — How and why Jonathan ended up in prison 00:02:57 — Prison conditions: expectations vs reality 00:07:33 — Prison became the greatest blessing 00:09:12 — How the entrepreneurial journey began after prison 00:10:34 — Why social capital matters 00:11:06 — Launched own club and took it to the top in 3 months 00:12:09 — Built an Axie Infinity gaming guild during COVID 00:13:49 — The beginning of the BipTap Group journey 00:17:23 — How Jonathan built his own banking system 00:20:07 — How to get a crypto card 00:22:03 — How much it costs to launch a white-label solution with BipTap 00:22:58 — Banking for AI agents 00:25:57 — How to build an RWA project 00:27:45 — Future of cryptocurrencies in banking 00:32:08 — The business verticals within Empire Group 00:32:48 — What Jonathan invests his money in 00:33:54 — How relationships with regulators are built 00:34:43 — Implementing AI in business 00:36:28 — Vibe coding in trading 00:40:06 — Advice for first-time founders 00:43:36 — From construction to trading: Ruslan Khairullin's journey 00:44:57 — Inner peace: why calmness is essential for founders 00:50:39 — Work-life balance for entrepreneurs 00:53:47 — $1.5 million in 24 hours on TST coin 00:55:11 — The best way to capture a market 00:55:57 — Banking for nations Watch the full conversation and let me know which part you liked the most 👇
58:52

From a Thai prison cell to a fintech empire processing $1.6B in international payments across 40+ banks and 250M+ users. Jonathan Low (Jonathan Low). Forbes 40 Under 40. Author of "Cell to CEO." We covered prison, banking for AI agents, RWA projects, the future of crypto in banking, vibe coding for trading, and the businesses that win the next 5 years. ⏱ Timestamps: 00:00:00 — Teaser 00:00:46 — Who is Jonathan Low 00:01:35 — What Jonathan's life was like before prison 00:02:13 — How and why Jonathan ended up in prison 00:02:57 — Prison conditions: expectations vs reality 00:07:33 — Prison became the greatest blessing 00:09:12 — How the entrepreneurial journey began after prison 00:10:34 — Why social capital matters 00:11:06 — Launched own club and took it to the top in 3 months 00:12:09 — Built an Axie Infinity gaming guild during COVID 00:13:49 — The beginning of the BipTap Group journey 00:17:23 — How Jonathan built his own banking system 00:20:07 — How to get a crypto card 00:22:03 — How much it costs to launch a white-label solution with BipTap 00:22:58 — Banking for AI agents 00:25:57 — How to build an RWA project 00:27:45 — Future of cryptocurrencies in banking 00:32:08 — The business verticals within Empire Group 00:32:48 — What Jonathan invests his money in 00:33:54 — How relationships with regulators are built 00:34:43 — Implementing AI in business 00:36:28 — Vibe coding in trading 00:40:06 — Advice for first-time founders 00:43:36 — From construction to trading: Ruslan Khairullin's journey 00:44:57 — Inner peace: why calmness is essential for founders 00:50:39 — Work-life balance for entrepreneurs 00:53:47 — $1.5 million in 24 hours on TST coin 00:55:11 — The best way to capture a market 00:55:57 — Banking for nations Watch the full conversation and let me know which part you liked the most 👇

Ruslan Khairullin

16,872 görüntüleme • 2 ay önce

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead
1:09:53

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead

Raoul Pal

172,640 görüntüleme • 1 yıl önce

NEW: Brian Armstrong, Coinbase Full Interview. Rebuilding Coinbase 🛡️ Around Intelligence Tokenized stocks, an SEC-registered AI advisor, +1,200 agents working inside the company We cover: › Pre-IPO perps (SpaceX, OpenAI, Anthropic) › Intelligent routing pushing 80% of workloads to models 99% cheaper (keeping token costs flat) › Tokenized equities backed 1:1, with 24/7 trading & access for 4B unbrokered people › Coinbase Advisor: SEC-registered AI investment advisor › 1,200 full-time AI agents, teams shrinking to 1 person, bugs/incidents down per line of code › Building the financial rails for the agentic economy › Economic freedom, Argentina, & why traditional media is dead 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Brian Armstrong, Co-Founder & CEO of Coinbase (00:45) Backstage before the Announcements drop (01:47) Why Tokenized Stocks never worked before until now (03:58) Inside Coinbase Advisor: The SEC-Registered AI Investment Agent (05:36) The real mission behind every Coinbase product (06:55) Does the average American feel economically free? (08:42) What Argentina taught Brian about Capitalism (11:16) Why younger generations are drifting toward Socialism (13:01) What Roblox reveals about the next generation (13:57) Why no one in Argentina plans for the future (18:17) How Crypto is rewriting financial infrastructure (20:20) The Strategy behind Coinbase's "Everything Exchange" (21:28) Building the most trusted brand in the Crypto Industry (23:49) Prediction Markets, Dry Powder & Reading Market Cycles (26:07) The Pre-IPO loophole Coinbase built for everyone else (28:18) Why Coinbase wins the super app war (29:40) The tweet that got 24 million views (32:22) Will AI actually kill jobs? (36:03) How Brian stays on top of everything (38:19) Founder Energy vs. Operator Energy (39:33) AI has a branding problem (46:41) Will Anthropic and OpenAI just build every company? (48:12) Who is Coinbase's real competitor? (51:25) The Announcement Brian is most excited about (53:03) Getting $4 trillion of new IPO wealth onto Coinbase (54:08) The mentors who shaped Brian Armstrong
57:52

NEW: Brian Armstrong, Coinbase Full Interview. Rebuilding Coinbase 🛡️ Around Intelligence Tokenized stocks, an SEC-registered AI advisor, +1,200 agents working inside the company We cover: › Pre-IPO perps (SpaceX, OpenAI, Anthropic) › Intelligent routing pushing 80% of workloads to models 99% cheaper (keeping token costs flat) › Tokenized equities backed 1:1, with 24/7 trading & access for 4B unbrokered people › Coinbase Advisor: SEC-registered AI investment advisor › 1,200 full-time AI agents, teams shrinking to 1 person, bugs/incidents down per line of code › Building the financial rails for the agentic economy › Economic freedom, Argentina, & why traditional media is dead 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Brian Armstrong, Co-Founder & CEO of Coinbase (00:45) Backstage before the Announcements drop (01:47) Why Tokenized Stocks never worked before until now (03:58) Inside Coinbase Advisor: The SEC-Registered AI Investment Agent (05:36) The real mission behind every Coinbase product (06:55) Does the average American feel economically free? (08:42) What Argentina taught Brian about Capitalism (11:16) Why younger generations are drifting toward Socialism (13:01) What Roblox reveals about the next generation (13:57) Why no one in Argentina plans for the future (18:17) How Crypto is rewriting financial infrastructure (20:20) The Strategy behind Coinbase's "Everything Exchange" (21:28) Building the most trusted brand in the Crypto Industry (23:49) Prediction Markets, Dry Powder & Reading Market Cycles (26:07) The Pre-IPO loophole Coinbase built for everyone else (28:18) Why Coinbase wins the super app war (29:40) The tweet that got 24 million views (32:22) Will AI actually kill jobs? (36:03) How Brian stays on top of everything (38:19) Founder Energy vs. Operator Energy (39:33) AI has a branding problem (46:41) Will Anthropic and OpenAI just build every company? (48:12) Who is Coinbase's real competitor? (51:25) The Announcement Brian is most excited about (53:03) Getting $4 trillion of new IPO wealth onto Coinbase (54:08) The mentors who shaped Brian Armstrong

Molly O’Shea

568,245 görüntüleme • 2 ay önce

Filevine and its founder Ryanfilevine may be the most successful AI company you haven't heard of. Filevine is a legal tech platform on an incredible run - serving 6,000 customers and generating +$200 million in annual revenue. Divot chat below. Timestamps: 02:42 — What Filevine Actually Does (Legal AI Explained) 04:08 — The Problem That Inspired Filevine 05:03 — The Risk Conversation With His Wife 09:03 — Meeting the Engineer Who Built the Vision 11:56 — The Founder Mindset: “I’ll Figure It Out” 18:20 — The Day Ryan Quit His Job 22:14 — Rewriting Filevine for the AI Era 25:41 — How AI Is Changing Software Teams 31:28 — Why the Legal Industry Could Grow 100x 44:55 — The Future of Law: AI Running Legal Work 55:20 — The Mindset to Build a Billion-Dollar Company 01:06:10 — Ryan’s Real Definition of Success Hashtags: #RyanAnderson #LegalAI #LegalTech #Entrepreneurship #SaaS #ArtificialIntelligence #Leadership #Justice #Innovation #DivotPodcast
1:07:40

Filevine and its founder Ryanfilevine may be the most successful AI company you haven't heard of. Filevine is a legal tech platform on an incredible run - serving 6,000 customers and generating +$200 million in annual revenue. Divot chat below. Timestamps: 02:42 — What Filevine Actually Does (Legal AI Explained) 04:08 — The Problem That Inspired Filevine 05:03 — The Risk Conversation With His Wife 09:03 — Meeting the Engineer Who Built the Vision 11:56 — The Founder Mindset: “I’ll Figure It Out” 18:20 — The Day Ryan Quit His Job 22:14 — Rewriting Filevine for the AI Era 25:41 — How AI Is Changing Software Teams 31:28 — Why the Legal Industry Could Grow 100x 44:55 — The Future of Law: AI Running Legal Work 55:20 — The Mindset to Build a Billion-Dollar Company 01:06:10 — Ryan’s Real Definition of Success Hashtags: #RyanAnderson #LegalAI #LegalTech #Entrepreneurship #SaaS #ArtificialIntelligence #Leadership #Justice #Innovation #DivotPodcast

Derek Andersen

13,507 görüntüleme • 5 ay önce

BREAKING: Public Co-CEO Leif Abraham (Leif Abraham) Says Their AI Plan is Seriously Working Millions of users, billions in assets, billions in trading volume, + revenue doubling annually Recorded at NYSE 🏛 this is one of the more fun chats on finance & how Public is building the next-gen investing platform “for those who take it seriously." Public represents the first modern alternative to Schwab, Fidelity, & Vanguard — platforms built on decades-old infrastructure that haven't kept pace with today's investors or technology. Financial advisors are cooked. Public's difference: - Top 25% of wealth w/ real assets to compound - AI Agents automating investment workflows - "Generated Assets" creating custom indices — defense index up 350% in a month - Multi-asset trading (stocks, crypto, options, bonds - all in one place) 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Leif Abraham, Co-Founder & Co-CEO at Public (01:10) Competing with traditional brokers (03:45) AI agents for investing (05:22) Are Public’s videos AI or real? (06:31) Why the co-CEO model works (09:34) The evolution of Public (15:06) Growth, scale, and market cycles (17:59) Breaking down the product ecosystem (20:45) Public's design philosophy (22:59) Building portfolios with AI (26:33) Ideal customers (30:20) The decline of financial advisors (33:00) What AI replaces in wealth management (35:45) Risks and limits of AI agents (37:32) The “financial super app” debate (42:39) Prediction markets vs real investing (45:04) Will everything become tradable? (46:22) Tokenization: the hype vs. the reality (50:37) The future of financial platforms (55:56) VCX, closed-end funds & speculation risk (59:09) Would Public go public? (01:02:22) What’s next for Public (01:04:08) The dark AI prediction (01:06:52) Wealth taxes vs. UBI
1:09:17

BREAKING: Public Co-CEO Leif Abraham (Leif Abraham) Says Their AI Plan is Seriously Working Millions of users, billions in assets, billions in trading volume, + revenue doubling annually Recorded at NYSE 🏛 this is one of the more fun chats on finance & how Public is building the next-gen investing platform “for those who take it seriously." Public represents the first modern alternative to Schwab, Fidelity, & Vanguard — platforms built on decades-old infrastructure that haven't kept pace with today's investors or technology. Financial advisors are cooked. Public's difference: - Top 25% of wealth w/ real assets to compound - AI Agents automating investment workflows - "Generated Assets" creating custom indices — defense index up 350% in a month - Multi-asset trading (stocks, crypto, options, bonds - all in one place) 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Leif Abraham, Co-Founder & Co-CEO at Public (01:10) Competing with traditional brokers (03:45) AI agents for investing (05:22) Are Public’s videos AI or real? (06:31) Why the co-CEO model works (09:34) The evolution of Public (15:06) Growth, scale, and market cycles (17:59) Breaking down the product ecosystem (20:45) Public's design philosophy (22:59) Building portfolios with AI (26:33) Ideal customers (30:20) The decline of financial advisors (33:00) What AI replaces in wealth management (35:45) Risks and limits of AI agents (37:32) The “financial super app” debate (42:39) Prediction markets vs real investing (45:04) Will everything become tradable? (46:22) Tokenization: the hype vs. the reality (50:37) The future of financial platforms (55:56) VCX, closed-end funds & speculation risk (59:09) Would Public go public? (01:02:22) What’s next for Public (01:04:08) The dark AI prediction (01:06:52) Wealth taxes vs. UBI

Molly O’Shea

99,045 görüntüleme • 4 ay önce

Netflix pays AI PMs up to $900K/year. How do you become (and succeed) as one? Marily Nika Marily Nika is an AI PM at Google, and was an AI PM at Meta. In today's episode, she breaks it down: How AI PM Roles Differ at Big Tech Companies – 06:56 How Technical an AI PM Needs to Be – 08:08 Data Handling Responsibilities for AI PMs – 13:10 How PMs Can Improve Collaboration with Researchers – 18:06 Interviewing for AI PM Roles at Big Tech Companies – 22:08 The Role of a PhD in AI Product Management – 26:03 Optimizing LinkedIn for Aspiring AI PMs – 31:55 Roadmap to Becoming an AI PM – 37:05 Transitioning into AI Product Management – 40:52 The Process of Boomeranging Back to a Company – 44:00 AI Tools Every PM Should Know – 48:08 What It’s Like to Be an AI PM at Google – 57:46 How to Develop a Strong Product Strategy – 01:01:21 The Evolution of PM Roles in the Age of AI – 01:05:11 How PMs Can Stay Relevant in an AI-Driven World – 01:08:12 Balancing a Side Business with a Full-Time Job – 01:13:42 The Process of Creating a Course – 01:17:12 LinkedIn Tips for Aspiring AI PM Creators – 01:21:21 Lessons from Product Failures – 01:25:27 Paid promotions included
1:27:33

Netflix pays AI PMs up to $900K/year. How do you become (and succeed) as one? Marily Nika Marily Nika is an AI PM at Google, and was an AI PM at Meta. In today's episode, she breaks it down: How AI PM Roles Differ at Big Tech Companies – 06:56 How Technical an AI PM Needs to Be – 08:08 Data Handling Responsibilities for AI PMs – 13:10 How PMs Can Improve Collaboration with Researchers – 18:06 Interviewing for AI PM Roles at Big Tech Companies – 22:08 The Role of a PhD in AI Product Management – 26:03 Optimizing LinkedIn for Aspiring AI PMs – 31:55 Roadmap to Becoming an AI PM – 37:05 Transitioning into AI Product Management – 40:52 The Process of Boomeranging Back to a Company – 44:00 AI Tools Every PM Should Know – 48:08 What It’s Like to Be an AI PM at Google – 57:46 How to Develop a Strong Product Strategy – 01:01:21 The Evolution of PM Roles in the Age of AI – 01:05:11 How PMs Can Stay Relevant in an AI-Driven World – 01:08:12 Balancing a Side Business with a Full-Time Job – 01:13:42 The Process of Creating a Course – 01:17:12 LinkedIn Tips for Aspiring AI PM Creators – 01:21:21 Lessons from Product Failures – 01:25:27 Paid promotions included

Aakash Gupta

42,853 görüntüleme • 1 yıl önce

. OpenLedger x : The full episode Our core contributor Ram sat down with Sreeram Kannan (founder ) to discuss verifiable AI, crypto's app problem, AI's trust problem and much more Check out the video below to learn more Timestamps: 00:00 Sreeram's introduction 00:29 How to build verification for AI systems 01:27 The Crypto and AI problem 03:10 Unstoppable AGI 05:08 What is Verifiable AI 06:05 The Verifiability Problem with Centralized AI 07:15 The current state of AI and its future 08:48 How humans are getting better at intelligence extraction 10:31 What is OpenLedger doing 11:50 Where LLMs fall short and how co-ordination helps 12:50 SLMs are already there 13:29 Crypto as an incentivisation mechanism 15:38 Apps with commitments, achieving product market fit 16:50 Existing examples of commitments in society 18:24 Investable AI 19:00 Data contributors as co-owner 21:30 The solution for the incentivisation problem 22:25 Explaining explainable AI 23:58 Trusting the trustless way 25:07 Data is the new oil 25:40 The idea of openledger is very crypto native 26:50 David v Goliath (in the data perspective) 28:03 What Eigen is working on 29:06 Making unstoppable verifiable AI practically possible 32:20 What Sreeram uses for productivity 33:30 Make Eigen Labs agentic 34:16 (community question) How Sreeram frames his prompts 36:08 (community question) What's the momentum driver for blockchain apps and what is Sreeram most excited about? (ZkTLS) 38:54 (community question) Where is attribution and verification really needed in AI?
39:43

. OpenLedger x : The full episode Our core contributor Ram sat down with Sreeram Kannan (founder ) to discuss verifiable AI, crypto's app problem, AI's trust problem and much more Check out the video below to learn more Timestamps: 00:00 Sreeram's introduction 00:29 How to build verification for AI systems 01:27 The Crypto and AI problem 03:10 Unstoppable AGI 05:08 What is Verifiable AI 06:05 The Verifiability Problem with Centralized AI 07:15 The current state of AI and its future 08:48 How humans are getting better at intelligence extraction 10:31 What is OpenLedger doing 11:50 Where LLMs fall short and how co-ordination helps 12:50 SLMs are already there 13:29 Crypto as an incentivisation mechanism 15:38 Apps with commitments, achieving product market fit 16:50 Existing examples of commitments in society 18:24 Investable AI 19:00 Data contributors as co-owner 21:30 The solution for the incentivisation problem 22:25 Explaining explainable AI 23:58 Trusting the trustless way 25:07 Data is the new oil 25:40 The idea of openledger is very crypto native 26:50 David v Goliath (in the data perspective) 28:03 What Eigen is working on 29:06 Making unstoppable verifiable AI practically possible 32:20 What Sreeram uses for productivity 33:30 Make Eigen Labs agentic 34:16 (community question) How Sreeram frames his prompts 36:08 (community question) What's the momentum driver for blockchain apps and what is Sreeram most excited about? (ZkTLS) 38:54 (community question) Where is attribution and verification really needed in AI?

OpenLedger

274,827 görüntüleme • 1 yıl önce

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks
1:15:17

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks

The Knowledge Project

453,197 görüntüleme • 1 yıl önce

Here's an edit of the Elon Musk interview hosted by Katherine Brodsky discussing a myriad of topics. This version boosts audio quality and reduces pauses and dead space by 33%. Thank you David Carbutt for the work! Timestamps: (00:00) The Journey of SpaceX and Tesla (01:06) Misunderstandings and Misinformation (03:42) The Role of Social Media in Free Speech (04:12) The Impact of Government Control on Media (06:32) The Evolution of Twitter and the Need for a Fresh Start (07:17) The Challenges of Moderation on Social Media Platforms (12:12) The Role of Citizen Journalism in Modern Media (17:45) The Future of Legacy Media (28:08) The Power of Amplifying Ideas and People (36:35) The Importance of Open-Mindedness and Self-Criticism (38:49) Community Notes and Open Source Data (39:58) The Role of Accuracy and Opinions in Posting (40:22) The Idea of a Sarcasm Detector (41:01) The Potential of AI in Enhancing Accuracy (42:39) The Future of AI and Deepfakes (44:59) The Vision for X as an All-in-One App (46:38) The Concept of Trust in Institutions (51:24) The Impact of Gene Editing on Humanity (55:42) The Challenge of Censorship and Free Speech (01:02:24) The Unusual Case of a Voice Doppelganger (01:07:35) Starting a Conversation: Texting and Simulations (01:08:43) Discussing Starship Launch and Future Plans (01:10:32) Engaging in Casual Conversations and Sharing Photos (01:11:55) Exploring the Idea of Expanding the Scope of Reality (01:13:27) Exploring the Concept of Simulation Theory (01:13:52) Discussing the Concept of AI in the Simulation (01:20:42) Addressing Questions about Ad Demonetization (01:23:11) Addressing Concerns about Doxxing and Harassment (01:30:47) Discussing the Monetization of Spaces (01:31:34) Discussing the Future of AI and OpenAI (01:35:17) Discussion on National Debt and AI (01:36:06) Involvement of Family Members (01:36:45) Questions and Answers (01:37:31) Impersonations and Voice Modulations (01:38:47) Discussion on Accents and Language Learning (01:41:14) Discussion on AI and Voice Imitation (01:46:45) Serious Discussion on AI and Social Media (01:51:27) Discussion on Physics and AI (01:58:18) Closing Remarks and Final Questions
1:59:51

Here's an edit of the Elon Musk interview hosted by Katherine Brodsky discussing a myriad of topics. This version boosts audio quality and reduces pauses and dead space by 33%. Thank you David Carbutt for the work! Timestamps: (00:00) The Journey of SpaceX and Tesla (01:06) Misunderstandings and Misinformation (03:42) The Role of Social Media in Free Speech (04:12) The Impact of Government Control on Media (06:32) The Evolution of Twitter and the Need for a Fresh Start (07:17) The Challenges of Moderation on Social Media Platforms (12:12) The Role of Citizen Journalism in Modern Media (17:45) The Future of Legacy Media (28:08) The Power of Amplifying Ideas and People (36:35) The Importance of Open-Mindedness and Self-Criticism (38:49) Community Notes and Open Source Data (39:58) The Role of Accuracy and Opinions in Posting (40:22) The Idea of a Sarcasm Detector (41:01) The Potential of AI in Enhancing Accuracy (42:39) The Future of AI and Deepfakes (44:59) The Vision for X as an All-in-One App (46:38) The Concept of Trust in Institutions (51:24) The Impact of Gene Editing on Humanity (55:42) The Challenge of Censorship and Free Speech (01:02:24) The Unusual Case of a Voice Doppelganger (01:07:35) Starting a Conversation: Texting and Simulations (01:08:43) Discussing Starship Launch and Future Plans (01:10:32) Engaging in Casual Conversations and Sharing Photos (01:11:55) Exploring the Idea of Expanding the Scope of Reality (01:13:27) Exploring the Concept of Simulation Theory (01:13:52) Discussing the Concept of AI in the Simulation (01:20:42) Addressing Questions about Ad Demonetization (01:23:11) Addressing Concerns about Doxxing and Harassment (01:30:47) Discussing the Monetization of Spaces (01:31:34) Discussing the Future of AI and OpenAI (01:35:17) Discussion on National Debt and AI (01:36:06) Involvement of Family Members (01:36:45) Questions and Answers (01:37:31) Impersonations and Voice Modulations (01:38:47) Discussion on Accents and Language Learning (01:41:14) Discussion on AI and Voice Imitation (01:46:45) Serious Discussion on AI and Social Media (01:51:27) Discussion on Physics and AI (01:58:18) Closing Remarks and Final Questions

Farzad 🇺🇸 🇮🇷

2,033,172 görüntüleme • 2 yıl önce

2025 has been a wild year for AI video. My conversation with Cristóbal Valenzuela, CEO of Runway: 00:00 – Meet Cris and Runway – AI Video's Wild Year 01:48 – Runway's AI Film Festival Goes From Chinatown To IMAX 04:02 – Hollywood's Shift: From Ignoring AI To Adopting It At Scale 06:38 – How Runway Saves VFX Artists' Weekends Of Work 07:31 – Inside Gen-4 And Aleph: Why These Models Are Game-Changers 08:21 – From Editing Tools To A "New Kind Of Camera" 10:00 – Beyond Film: Gaming, Architecture, E-commerce & Robotics Use Cases 10:55 – Why Advertising Is Adopting AI Video Faster Than Anyone Else 11:38 – How Creatives Adapt When Iteration Becomes Real-Time 14:12 – What Makes Someone Great At AI Video (Hint: No Preconceptions) 15:28 – The Early Days: Building Runway Before Generative AI Was "Real" 20:27 – Finding Early Product-Market Fit 21:51 – Balancing Research And Product Inside Runway 24:23 – Comparing Aleph Vs. Gen-4, And The Future Of Generalist Models 30:36 – New Input Modalities: Editing With Video + Annotations, Not Just Text 33:46 – Managing Expectations: Twitter Demos Vs. Real Creative Work 47:09 – The Future: Real-Time AI Video And Fully Explorable 3D Worlds 52:02 – Runway's Business Model: From Indie Creators To Disney & Lionsgate 57:26 – Competing With The Big Labs (Sora, Google, Etc.) 59:58 – Hyper-Personalized Content? Why It May Not Replace Film 1:01:13 – Advice To Founders: Treat Your Company Like A Model — Always Learning 1:03:06 – The Next 5 Years Of Runway: Changing Creativity Forever
1:05:04

2025 has been a wild year for AI video. My conversation with Cristóbal Valenzuela, CEO of Runway: 00:00 – Meet Cris and Runway – AI Video's Wild Year 01:48 – Runway's AI Film Festival Goes From Chinatown To IMAX 04:02 – Hollywood's Shift: From Ignoring AI To Adopting It At Scale 06:38 – How Runway Saves VFX Artists' Weekends Of Work 07:31 – Inside Gen-4 And Aleph: Why These Models Are Game-Changers 08:21 – From Editing Tools To A "New Kind Of Camera" 10:00 – Beyond Film: Gaming, Architecture, E-commerce & Robotics Use Cases 10:55 – Why Advertising Is Adopting AI Video Faster Than Anyone Else 11:38 – How Creatives Adapt When Iteration Becomes Real-Time 14:12 – What Makes Someone Great At AI Video (Hint: No Preconceptions) 15:28 – The Early Days: Building Runway Before Generative AI Was "Real" 20:27 – Finding Early Product-Market Fit 21:51 – Balancing Research And Product Inside Runway 24:23 – Comparing Aleph Vs. Gen-4, And The Future Of Generalist Models 30:36 – New Input Modalities: Editing With Video + Annotations, Not Just Text 33:46 – Managing Expectations: Twitter Demos Vs. Real Creative Work 47:09 – The Future: Real-Time AI Video And Fully Explorable 3D Worlds 52:02 – Runway's Business Model: From Indie Creators To Disney & Lionsgate 57:26 – Competing With The Big Labs (Sora, Google, Etc.) 59:58 – Hyper-Personalized Content? Why It May Not Replace Film 1:01:13 – Advice To Founders: Treat Your Company Like A Model — Always Learning 1:03:06 – The Next 5 Years Of Runway: Changing Creativity Forever

Matt Turck

18,817 görüntüleme • 1 yıl önce

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science
49:06

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science

Matt Turck

66,936 görüntüleme • 2 ay önce